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Membership

How R Consortium membership helps support the R Community

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+

Please share your background and involvement with the RUGS group.

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I have a background in biology. I studied zoology and genetics at the undergraduate level and then pursued a master’s degree in genetic epidemiology, focusing on identifying genes involved in human diseases. Specifically, I worked on complex diseases such as rheumatoid arthritis and related autoimmune diseases initially and breast cancer. During my master’s program, I was taught programming and learned some C, although that was quite a long time ago, around 25 years ago. While I never really took to C programming, I was also introduced to the statistical package Stata, which I found very user-friendly and appreciated its strong community support.

+

As time passed, I began to hear more and more about R. This was around 2000, a few years after R was first released. One of the things I had started doing was writing literate documents in LaTeX. I would write a LaTeX document, and Stata could output tables to LaTeX, which I could then include in my document and render to PDF. I found this a much more efficient way to work reproducibly than traditional word processors and spreadsheets.

+

I was exploring R and discovered Friedrich Liesch’s package Sweave, which interweaved LaTeX and R code. It was really the precursor to RMarkdown. I also started using Linux as my operating system and became interested in the free open source software movement.

+

Around 2004 I made a conscious choice to switch from Stata to R because of its open source licensing and extensibility. While Stata allowed me to write my functions and modules, I found R more open as it isn’t owned by a company, and I didn’t need a license, which I typically relied on my employers to provide.

+

I decided to invest my time learning R for all my work because it would benefit me in the long run, as I could take the knowledge and skills and use them anywhere. When I switched careers from genetic statistician to medical statistician in a clinical trials unit at the University of Sheffield, I continued using R, although I was in a minority, as most colleagues at the time used Stata or SPSS.

+

I continued using R and convinced a few others to join me. We supported each other, and around 2015 the SheffieldR user group was initiated by Anna Krystalli. I attended the meetings and found them really useful as they brought together people from the university and beyond who shared a passion for using R in their research, showing each other how they used R in their work. It was a great way to discover new features. I attended those meetings until around 2019, when I switched jobs to work for a startup tech company and switched to using Python and Java for work. Soon after, SheffieldR fizzled out due to lockdown in 2020.

+

After working for a tech company for a few years, I returned to the University of Sheffield as a Research Software Engineer, where I’m currently employed. This role has given me more opportunities to use R. I have been involved in a Python project from the beginning, but recently, I’ve also had the chance to work on a few R projects. I’ve missed the enjoyable and exciting R user group meetings that I used to attend.

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I was asked to improve Sheffield’s RSE (Research Software Engineering) community. As part of this, I joined the open science community movement, an international initiative that began in the Netherlands. They had an incubator program to establish open science communities in local areas, and I enrolled in that program to start an open science community in Sheffield. I’m quite a practical person and like to take action and help others, so I resolved to revive the Sheffield R user group as I had found it so useful in helping me learn what could be done with R earlier in my career.

+

I briefly worked with Anna, who had started the SheffieldR group, but unfortunately, soon after I started to work with the RSE Team, she moved on and became an R consultant. Still, we had some overlap, and she was happy to share all the materials and the GitHub repository for the website with me. So, I took on the responsibility of organizing the group. I rewrote the website and switched it from R Markdown to Quarto to learn more about using Quarto, which had just been released. It wasn’t too difficult since the languages are pretty similar.

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Sheffield R User Group April 2024 Meetup “Profiling and Optimising your R code,” Speaker: Dan Brady, Research Software Engineer, University of Sheffield.

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I was joined by Grace Accad from the Data Analytics Service at the University of Sheffield to organize SheffieldR. She had been involved in R ladies and attended other R user groups, and I’ve been very grateful to her for her support and help in sharing the workload.

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We have been hosting Sheffield R user group events for over a year, and they have been quite successful. We aim to hold the events every month during term time. I presented at our initial reboot session showing how to use Quarto and GitHub pages to put slides online, but we have been fortunate to find other speakers since then. However, Grace and I are primarily responsible for organizing and setting up the website and booking rooms. It’s not too demanding, but that’s my primary role in the group.

+

Can you share what the R community is like in Sheffield?

+

Sheffield R User Group January 2024 Meetup “Automating Health Economic Evaluation with R,” Speaker: Robert Smith, Dark Peak Analytics.

+

I only have a little industry experience, having only worked for one company. However, I think R is more academic, although that is changing. In Sheffield, the company I worked for had a research department with only two people. So, at least in Sheffield, R is used in the industry. The Sheffield R user group aims to bring together people who use R in the area to create a community where they can ask questions and help each other. A data science learning community in Sheffield used to be more R-oriented but now includes people using pandas. I like that community as well.

+

I strongly believe in the importance of connecting with people in person. The networking effect is natural and very beneficial. Building these connections and networks online while possible is more challenging, so I am focused on creating a local group to foster this. Most participants are from the University of Sheffield. However, there are also individuals from Sheffield Hallam University and outside academia, such as Simon Rolph from the UK Centre for Ecology and Hydrology, who gave an excellent talk on the targets package. We’ve also had talks with Robert Smith and Wael Mohammed of Dark Peak Analytics.

+

One of my challenges is that I have a daughter, so I usually need to be home in the afternoons to take care of her. I appreciate that attending events in the evenings isn’t possible for everyone. Finding a suitable time for everyone is difficult. If we have meetings at lunchtime, we get a lot of university attendees, but only a few from farther away because they would have to travel. You can please some of the people sometimes, but you can’t please all the people all the time.

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Your group recently hosted Hacktoberfest events. Can you share more about the topic covered? Why this topic?

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Hacktoberfest celebrates open source software and encourages people to find their favorite open source project to contribute to. Our first meeting was on October 4th, and then we had one every other Friday throughout October.

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The main objective was to help people get comfortable contributing to open source software, especially those who use R but may not be familiar with version control using Git and GitHub. In the first session, I used material from my job as a research software engineer, where I’ve been teaching a course Anna developed on using Git and GitHub for the past year or two. This course covers the basics of version control and includes a collaborative exercise using a GitHub repository.

+

Participants learned how to fork the repository, make changes locally, push their changes, and create pull requests. The following three weeks were dedicated to providing support, where others and I with experience in version control and using R were available to assist others. The goal was for people to help each other during this time and not rely solely on me or my colleagues as organizers, as some individuals may have more knowledge than others. It was great to see everyone coming together to support one another, as some people may have more expertise in specific areas than I do.

+

Any techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?

+

I have a GitHub issue template in place to help organize our meetings. I use GitHub to plan events because my memory is terrible. I’d likely forget something important if I didn’t have everything written down. Whenever we plan an event, we create a GitHub issue and assign it to me or Grace. It’s a checklist of tasks such as booking a room, setting dates and times, confirming speakers, obtaining consent for photography during the event, and listing places to advertise the event. This checklist helps us keep track of everything that needs to be done for each event.

+

The Sheffield R user group used to meet in a local pub. However, when we restarted the events, we decided that using more neutral spaces would be more inclusive, so we use university buildings now. We want to ensure everyone feels welcome, so we choose accessible venues for people with disabilities. It’s important to me that everyone can attend without any barriers.

+

We also run hybrid meetings, which I find challenging. When I have a group of people in the room, I naturally tend to speak to them. I have to remind myself to pay constant attention to the online participants. It’s helpful to have another organizer keeping an eye on the online side of things when people raise their hands. Despite the challenges, we continue with hybrid meetings because they’re a good way of allowing people to attend if they can’t make it in person.

+

Please share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?

+

I’m working on a project with a PhD student trying to improve thyroid cancer prediction. When he approached me, he used SPSS for his analysis because that’s what one of my old colleagues had taught him. From now on, I encouraged him to switch to using R for all his work, and I’ve helped him set up version control for it.

+

He has learned to write Quarto documents with embedded R code to write the manuscript he wants to create. This has been very useful. He has also learned how to use a multiple imputation package that he hadn’t used before to summarize the results and check their consistency with the observed data. At one point, the PhD student and his supervisor wanted to create a website where people could enter various characteristics about a patient and receive a risk profile indicating whether the lumps in their thyroids were likely to be malignant. To achieve this, he revisited his knowledge of Shiny to get the website up and running. However, he was aware that it might be something they wanted to put into production. Consequently, he discovered the Golem package, which appears to be a handy tool for taking Shiny and developing it more rigorously for deployment to production. This has been the main focus of his recent work with R.

+

I’ve been using Quarto and R for my blog and some small tasks lately. I’ve written several posts about pre-commit for linting code, which is really useful. I’m overdue writing one on how to use the lintr package and should find time to investigate the newer flint package too.

+

I also had a project where the researchers used R and had a lot of code. I convinced them to organize their code into a more structured package format. I found DevTools and the usethis package to be very helpful for that. At the same time, I set up the package repository to use linter to ensure that all coding standards were followed in case they ever decided to release it to CRAN.

+

I feel like a jack of all trades because I use Python, R, and a bit of Bash. I know a little about everything, but I’m not an expert at any one thing!

+

How do I Join?

+

R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.

+

https://r-consortium.org/all-projects/rugsprogram.html

+ + + + ]]> + https://r-consortium.org/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/ + Fri, 01 Nov 2024 00:00:00 GMT + + Streamlining API Integration: Jon Harmon’s Journey with the api2r Package R Consortium @@ -1184,30 +1239,5 @@ font-style: inherit;">TRUE)
Mon, 12 Aug 2024 00:00:00 GMT - - R Consortium Grants Committee Announces New Chair - R Consortium - https://r-consortium.org/posts/rconsortium-grants-comittee-announces-new-chair/ -

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The R Consortium is pleased to announce that Katherine Jeschke has been appointed Chair of the Grants Committee.

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She will oversee day-to-day grant processes for both pre- and post-awards, ensuring grants meet the R Consortium’s strategic objectives. Katherine will report to the Executive Director and work closely with the Infrastructure Steering Committee and the RUGS program to track grants and help improve the effectiveness of R Consortium grants in supporting the R Community.

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Katherine’s non-profit grants and administration skills were honed over more than 25 years of experience in marketing communications, and staff, budget, development, and grants management for non-profits and trade organizations, as well as corporate and public sector consulting organizations.

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She holds an MA degree in American History and Museum Administration from George Washington University and a BA degree in Fine Arts and Art History from the University of Maryland.

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“Getting acquainted with our various grants and procedures while evaluating the strategic effectiveness of R Consortium grants is a big undertaking, but her background and years of experience should ease her way,” said Joseph Rickert, Executive Director of the R Consortium.

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She may be reached at kj.jeschke@posit.co

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+Neil Shephard, co-organizer of the Sheffield R User Group in Sheffield, United Kingdom (also on fosstodon), recently spoke to the R Consortium about his journey from Genetic… +
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Events

Upcoming Events

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diff --git a/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/NeilShephard.png b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/NeilShephard.png new file mode 100644 index 0000000..09f5c10 Binary files /dev/null and b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/NeilShephard.png differ diff --git a/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldJanuary2024.png b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldJanuary2024.png new file mode 100644 index 0000000..f81fca5 Binary files /dev/null and b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldJanuary2024.png differ diff --git a/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldRUGs.png b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldRUGs.png new file mode 100644 index 0000000..4959890 Binary files /dev/null and b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/SheffieldRUGs.png differ diff --git a/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/index.html b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/index.html new file mode 100644 index 0000000..7aa72f8 --- /dev/null +++ b/posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/index.html @@ -0,0 +1,804 @@ + + + + + + + + + + + + +Reviving Sheffield R User Group and Building Tools for Thyroid Cancer Prediction – R Consortium + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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Reviving Sheffield R User Group and Building Tools for Thyroid Cancer Prediction

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+ Neil Shephard, co-organizer of the Sheffield R User Group in Sheffield, United Kingdom (also on fosstodon), recently spoke to the R Consortium about his journey from Genetic Epidemiology to Research Software Engineering with R. +
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November 1, 2024

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Neil Shephard, co-organizer of the Sheffield R User Group in Sheffield, United Kingdom (also on fosstodon), recently spoke to the R Consortium about his journey from Genetic Epidemiology to Research Software Engineering with R. He also discussed the revival of the Sheffield R User group and the challenges of organizing inclusive and hybrid events. Neil also highlighted the group’s successful participation in Hacktoberfest and shared insights into his current R projects, including developing tools for thyroid cancer prediction and deploying Shiny applications.

+

+

Please share your background and involvement with the RUGS group.

+

I have a background in biology. I studied zoology and genetics at the undergraduate level and then pursued a master’s degree in genetic epidemiology, focusing on identifying genes involved in human diseases. Specifically, I worked on complex diseases such as rheumatoid arthritis and related autoimmune diseases initially and breast cancer. During my master’s program, I was taught programming and learned some C, although that was quite a long time ago, around 25 years ago. While I never really took to C programming, I was also introduced to the statistical package Stata, which I found very user-friendly and appreciated its strong community support.

+

As time passed, I began to hear more and more about R. This was around 2000, a few years after R was first released. One of the things I had started doing was writing literate documents in LaTeX. I would write a LaTeX document, and Stata could output tables to LaTeX, which I could then include in my document and render to PDF. I found this a much more efficient way to work reproducibly than traditional word processors and spreadsheets.

+

I was exploring R and discovered Friedrich Liesch’s package Sweave, which interweaved LaTeX and R code. It was really the precursor to RMarkdown. I also started using Linux as my operating system and became interested in the free open source software movement.

+

Around 2004 I made a conscious choice to switch from Stata to R because of its open source licensing and extensibility. While Stata allowed me to write my functions and modules, I found R more open as it isn’t owned by a company, and I didn’t need a license, which I typically relied on my employers to provide.

+

I decided to invest my time learning R for all my work because it would benefit me in the long run, as I could take the knowledge and skills and use them anywhere. When I switched careers from genetic statistician to medical statistician in a clinical trials unit at the University of Sheffield, I continued using R, although I was in a minority, as most colleagues at the time used Stata or SPSS.

+

I continued using R and convinced a few others to join me. We supported each other, and around 2015 the SheffieldR user group was initiated by Anna Krystalli. I attended the meetings and found them really useful as they brought together people from the university and beyond who shared a passion for using R in their research, showing each other how they used R in their work. It was a great way to discover new features. I attended those meetings until around 2019, when I switched jobs to work for a startup tech company and switched to using Python and Java for work. Soon after, SheffieldR fizzled out due to lockdown in 2020.

+

After working for a tech company for a few years, I returned to the University of Sheffield as a Research Software Engineer, where I’m currently employed. This role has given me more opportunities to use R. I have been involved in a Python project from the beginning, but recently, I’ve also had the chance to work on a few R projects. I’ve missed the enjoyable and exciting R user group meetings that I used to attend.

+

I was asked to improve Sheffield’s RSE (Research Software Engineering) community. As part of this, I joined the open science community movement, an international initiative that began in the Netherlands. They had an incubator program to establish open science communities in local areas, and I enrolled in that program to start an open science community in Sheffield. I’m quite a practical person and like to take action and help others, so I resolved to revive the Sheffield R user group as I had found it so useful in helping me learn what could be done with R earlier in my career.

+

I briefly worked with Anna, who had started the SheffieldR group, but unfortunately, soon after I started to work with the RSE Team, she moved on and became an R consultant. Still, we had some overlap, and she was happy to share all the materials and the GitHub repository for the website with me. So, I took on the responsibility of organizing the group. I rewrote the website and switched it from R Markdown to Quarto to learn more about using Quarto, which had just been released. It wasn’t too difficult since the languages are pretty similar.

+

Sheffield R User Group April 2024 Meetup “Profiling and Optimising your R code,” Speaker: Dan Brady, Research Software Engineer, University of Sheffield.

+

I was joined by Grace Accad from the Data Analytics Service at the University of Sheffield to organize SheffieldR. She had been involved in R ladies and attended other R user groups, and I’ve been very grateful to her for her support and help in sharing the workload.

+

We have been hosting Sheffield R user group events for over a year, and they have been quite successful. We aim to hold the events every month during term time. I presented at our initial reboot session showing how to use Quarto and GitHub pages to put slides online, but we have been fortunate to find other speakers since then. However, Grace and I are primarily responsible for organizing and setting up the website and booking rooms. It’s not too demanding, but that’s my primary role in the group.

+

Can you share what the R community is like in Sheffield?

+

Sheffield R User Group January 2024 Meetup “Automating Health Economic Evaluation with R,” Speaker: Robert Smith, Dark Peak Analytics.

+

I only have a little industry experience, having only worked for one company. However, I think R is more academic, although that is changing. In Sheffield, the company I worked for had a research department with only two people. So, at least in Sheffield, R is used in the industry. The Sheffield R user group aims to bring together people who use R in the area to create a community where they can ask questions and help each other. A data science learning community in Sheffield used to be more R-oriented but now includes people using pandas. I like that community as well.

+

I strongly believe in the importance of connecting with people in person. The networking effect is natural and very beneficial. Building these connections and networks online while possible is more challenging, so I am focused on creating a local group to foster this. Most participants are from the University of Sheffield. However, there are also individuals from Sheffield Hallam University and outside academia, such as Simon Rolph from the UK Centre for Ecology and Hydrology, who gave an excellent talk on the targets package. We’ve also had talks with Robert Smith and Wael Mohammed of Dark Peak Analytics.

+

One of my challenges is that I have a daughter, so I usually need to be home in the afternoons to take care of her. I appreciate that attending events in the evenings isn’t possible for everyone. Finding a suitable time for everyone is difficult. If we have meetings at lunchtime, we get a lot of university attendees, but only a few from farther away because they would have to travel. You can please some of the people sometimes, but you can’t please all the people all the time.

+

Your group recently hosted Hacktoberfest events. Can you share more about the topic covered? Why this topic?

+

Hacktoberfest celebrates open source software and encourages people to find their favorite open source project to contribute to. Our first meeting was on October 4th, and then we had one every other Friday throughout October.

+

The main objective was to help people get comfortable contributing to open source software, especially those who use R but may not be familiar with version control using Git and GitHub. In the first session, I used material from my job as a research software engineer, where I’ve been teaching a course Anna developed on using Git and GitHub for the past year or two. This course covers the basics of version control and includes a collaborative exercise using a GitHub repository.

+

Participants learned how to fork the repository, make changes locally, push their changes, and create pull requests. The following three weeks were dedicated to providing support, where others and I with experience in version control and using R were available to assist others. The goal was for people to help each other during this time and not rely solely on me or my colleagues as organizers, as some individuals may have more knowledge than others. It was great to see everyone coming together to support one another, as some people may have more expertise in specific areas than I do.

+

Any techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?

+

I have a GitHub issue template in place to help organize our meetings. I use GitHub to plan events because my memory is terrible. I’d likely forget something important if I didn’t have everything written down. Whenever we plan an event, we create a GitHub issue and assign it to me or Grace. It’s a checklist of tasks such as booking a room, setting dates and times, confirming speakers, obtaining consent for photography during the event, and listing places to advertise the event. This checklist helps us keep track of everything that needs to be done for each event.

+

The Sheffield R user group used to meet in a local pub. However, when we restarted the events, we decided that using more neutral spaces would be more inclusive, so we use university buildings now. We want to ensure everyone feels welcome, so we choose accessible venues for people with disabilities. It’s important to me that everyone can attend without any barriers.

+

We also run hybrid meetings, which I find challenging. When I have a group of people in the room, I naturally tend to speak to them. I have to remind myself to pay constant attention to the online participants. It’s helpful to have another organizer keeping an eye on the online side of things when people raise their hands. Despite the challenges, we continue with hybrid meetings because they’re a good way of allowing people to attend if they can’t make it in person.

+

Please share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?

+

I’m working on a project with a PhD student trying to improve thyroid cancer prediction. When he approached me, he used SPSS for his analysis because that’s what one of my old colleagues had taught him. From now on, I encouraged him to switch to using R for all his work, and I’ve helped him set up version control for it.

+

He has learned to write Quarto documents with embedded R code to write the manuscript he wants to create. This has been very useful. He has also learned how to use a multiple imputation package that he hadn’t used before to summarize the results and check their consistency with the observed data. At one point, the PhD student and his supervisor wanted to create a website where people could enter various characteristics about a patient and receive a risk profile indicating whether the lumps in their thyroids were likely to be malignant. To achieve this, he revisited his knowledge of Shiny to get the website up and running. However, he was aware that it might be something they wanted to put into production. Consequently, he discovered the Golem package, which appears to be a handy tool for taking Shiny and developing it more rigorously for deployment to production. This has been the main focus of his recent work with R.

+

I’ve been using Quarto and R for my blog and some small tasks lately. I’ve written several posts about pre-commit for linting code, which is really useful. I’m overdue writing one on how to use the lintr package and should find time to investigate the newer flint package too.

+

I also had a project where the researchers used R and had a lot of code. I convinced them to organize their code into a more structured package format. I found DevTools and the usethis package to be very helpful for that. At the same time, I set up the package repository to use linter to ensure that all coding standards were followed in case they ever decided to release it to CRAN.

+

I feel like a jack of all trades because I use Python, R, and a bit of Bash. I know a little about everything, but I’m not an expert at any one thing!

+

How do I Join?

+

R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.

+

https://r-consortium.org/all-projects/rugsprogram.html

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© 2024 R Consortium. R Consortium is a non-profit organization, and R Consortium™ is a trademark of R Consortium. All Rights Reserved. This website is built on Quarto, an open-source scientific and technical publishing system. Quarto uses R Markdown and knitr to execute R code.

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+ + + + + \ No newline at end of file diff --git a/search.json b/search.json index 9747cc5..aa796bf 100644 --- a/search.json +++ b/search.json @@ -294,809 +294,746 @@ "text": "Contributed by Charlie Gao, Director at Hibiki AI Limited\n\n\n\n{nanonext} is an R binding to the state of the art C messaging library NNG (Nanomsg Next Generation), created as a successor to ZeroMQ. It was originally developed as a fast and reliable messaging interface for use in machine learning pipelines. With implementations readily available in languages including C++, Go, Python, and Rust, it allowed individual modules to be written in the most appropriate language and for them to be piped together in a single workflow.\n{mirai} is a package that enables asynchronous evaluation in R, built on top of {nanonext}. It was initially created purely as a demonstration of the reliable RPC (remote procedure call) protocol from {nanonext}. However, open-sourcing this project greatly facilitated its discovery and dissemination, eventually leading to a long-term, cross-industry collaboration with Will Landau, a statistician in the life sciences industry, author of the {targets} package for reproducible pipelines. He ended up creating the {crew} package to extend {mirai} to handle the increasingly complex and demanding high-performance computing needs faced by his users.\nAs this work was progressing, security was still a missing piece of the puzzle. The NNG library supported integration with Mbed TLS (a SSL/TLS library developed under the Trusted Firmware Project), however secure connections were not yet a part of the R landscape.\nThe R Consortium, by way of an Infrastructure Steering Committee (ISC) grant, funded the work to implement this functionality from the underlying libraries and to also devise a means of configuring the required certificates in R. The stated intention was to provide a user-friendly interface for doing so. The end result somewhat exceeded these goals, with the default allowing for zero-configuration, single-use certificates to be generated on-the-fly. This affords an unparalleled level of usability, not requiring end users to have any knowledge of the intricacies of TLS.\nWill Landau talks about the impact TLS has had on his work:\n“I sought to extend {mirai} to a wide variety of computing environments through {crew}, from traditional clusters to Amazon Web Services. The integration of TLS into {nanonext} increases the confidence with which {mirai} can be deployed in these powerful environments, accelerating downstream applications and {targets} pipelines.”\nThe project to extend {mirai} to high-performance computing environments was featured in a workshop on simulation workflows in the life sciences, given at R/Pharma in October 2023 (video and materials accessible from https://github.com/wlandau/rpharma2023).\nWith the seed planted in {nanonext}, {mirai} and {crew} have grown to form an elegant and performant foundation for an emerging landscape of asynchronous and parallel programming tools. They already provide new back-ends for {parallel}, {promises}, {plumber}, {targets}, and Shiny, as well as high-level interfaces such as {crew.cluster} for traditional clusters and {crew.aws.batch} for the cloud.\n\n\n\nCharlie Gao, Director at Hibiki AI Limited" }, { - "objectID": "posts/recap-r-validation-hub-community-meeting/index.html#key-insights", - "href": "posts/recap-r-validation-hub-community-meeting/index.html#key-insights", - "title": "Recap: R Validation Hub Community Meeting", - "section": "Key Insights:", - "text": "Key Insights:\n\nValidation Perspectives: The meeting underscored the need for each organization to define “validation” in a way that suits its context, while the R Validation Hub offers a baseline for common understanding.\nStatistical Methodology Challenges: Discussions acknowledged the challenges in achieving exact results across different programming languages due to inherent differences in statistical methodologies.\nOpen Source Contributions: The importance of returning testing code to package developers was highlighted, reinforcing the open-source ethos of collaboration and quality enhancement.\nResource Availability: The slides from the meeting are accessible on GitHub here. Although the meeting wasn’t recorded, the community is encouraged to join the R Validation Hub mailing list for future updates and meeting invites here." - }, - { - "objectID": "posts/recap-r-validation-hub-community-meeting/index.html#looking-forward", - "href": "posts/recap-r-validation-hub-community-meeting/index.html#looking-forward", - "title": "Recap: R Validation Hub Community Meeting", - "section": "Looking Forward:", - "text": "Looking Forward:\nThe meeting reiterated the significance of the R Validation Hub as a central point for validation discussions and resources. Future community meetings are tentatively scheduled for May 21, August 20, and November 19, offering opportunities for further engagement and contribution to the evolving conversation around R validation.\n\nJoin the R Validation Hub mailing list!" + "objectID": "posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/index.html", + "href": "posts/reviving-sheffield-r-user-group-and-building-tools-for-thyroid-cancer-prediction/index.html", + "title": "Reviving Sheffield R User Group and Building Tools for Thyroid Cancer Prediction", + "section": "", + "text": "Neil Shephard, co-organizer of the Sheffield R User Group in Sheffield, United Kingdom (also on fosstodon), recently spoke to the R Consortium about his journey from Genetic Epidemiology to Research Software Engineering with R. He also discussed the revival of the Sheffield R User group and the challenges of organizing inclusive and hybrid events. Neil also highlighted the group’s successful participation in Hacktoberfest and shared insights into his current R projects, including developing tools for thyroid cancer prediction and deploying Shiny applications.\n\nPlease share your background and involvement with the RUGS group.\nI have a background in biology. I studied zoology and genetics at the undergraduate level and then pursued a master’s degree in genetic epidemiology, focusing on identifying genes involved in human diseases. Specifically, I worked on complex diseases such as rheumatoid arthritis and related autoimmune diseases initially and breast cancer. During my master’s program, I was taught programming and learned some C, although that was quite a long time ago, around 25 years ago. While I never really took to C programming, I was also introduced to the statistical package Stata, which I found very user-friendly and appreciated its strong community support.\nAs time passed, I began to hear more and more about R. This was around 2000, a few years after R was first released. One of the things I had started doing was writing literate documents in LaTeX. I would write a LaTeX document, and Stata could output tables to LaTeX, which I could then include in my document and render to PDF. I found this a much more efficient way to work reproducibly than traditional word processors and spreadsheets.\nI was exploring R and discovered Friedrich Liesch’s package Sweave, which interweaved LaTeX and R code. It was really the precursor to RMarkdown. I also started using Linux as my operating system and became interested in the free open source software movement.\nAround 2004 I made a conscious choice to switch from Stata to R because of its open source licensing and extensibility. While Stata allowed me to write my functions and modules, I found R more open as it isn’t owned by a company, and I didn’t need a license, which I typically relied on my employers to provide.\nI decided to invest my time learning R for all my work because it would benefit me in the long run, as I could take the knowledge and skills and use them anywhere. When I switched careers from genetic statistician to medical statistician in a clinical trials unit at the University of Sheffield, I continued using R, although I was in a minority, as most colleagues at the time used Stata or SPSS.\nI continued using R and convinced a few others to join me. We supported each other, and around 2015 the SheffieldR user group was initiated by Anna Krystalli. I attended the meetings and found them really useful as they brought together people from the university and beyond who shared a passion for using R in their research, showing each other how they used R in their work. It was a great way to discover new features. I attended those meetings until around 2019, when I switched jobs to work for a startup tech company and switched to using Python and Java for work. Soon after, SheffieldR fizzled out due to lockdown in 2020.\nAfter working for a tech company for a few years, I returned to the University of Sheffield as a Research Software Engineer, where I’m currently employed. This role has given me more opportunities to use R. I have been involved in a Python project from the beginning, but recently, I’ve also had the chance to work on a few R projects. I’ve missed the enjoyable and exciting R user group meetings that I used to attend.\nI was asked to improve Sheffield’s RSE (Research Software Engineering) community. As part of this, I joined the open science community movement, an international initiative that began in the Netherlands. They had an incubator program to establish open science communities in local areas, and I enrolled in that program to start an open science community in Sheffield. I’m quite a practical person and like to take action and help others, so I resolved to revive the Sheffield R user group as I had found it so useful in helping me learn what could be done with R earlier in my career.\nI briefly worked with Anna, who had started the SheffieldR group, but unfortunately, soon after I started to work with the RSE Team, she moved on and became an R consultant. Still, we had some overlap, and she was happy to share all the materials and the GitHub repository for the website with me. So, I took on the responsibility of organizing the group. I rewrote the website and switched it from R Markdown to Quarto to learn more about using Quarto, which had just been released. It wasn’t too difficult since the languages are pretty similar.\n Sheffield R User Group April 2024 Meetup “Profiling and Optimising your R code,” Speaker: Dan Brady, Research Software Engineer, University of Sheffield.\nI was joined by Grace Accad from the Data Analytics Service at the University of Sheffield to organize SheffieldR. She had been involved in R ladies and attended other R user groups, and I’ve been very grateful to her for her support and help in sharing the workload.\nWe have been hosting Sheffield R user group events for over a year, and they have been quite successful. We aim to hold the events every month during term time. I presented at our initial reboot session showing how to use Quarto and GitHub pages to put slides online, but we have been fortunate to find other speakers since then. However, Grace and I are primarily responsible for organizing and setting up the website and booking rooms. It’s not too demanding, but that’s my primary role in the group.\nCan you share what the R community is like in Sheffield? \n Sheffield R User Group January 2024 Meetup “Automating Health Economic Evaluation with R,” Speaker: Robert Smith, Dark Peak Analytics.\nI only have a little industry experience, having only worked for one company. However, I think R is more academic, although that is changing. In Sheffield, the company I worked for had a research department with only two people. So, at least in Sheffield, R is used in the industry. The Sheffield R user group aims to bring together people who use R in the area to create a community where they can ask questions and help each other. A data science learning community in Sheffield used to be more R-oriented but now includes people using pandas. I like that community as well.\nI strongly believe in the importance of connecting with people in person. The networking effect is natural and very beneficial. Building these connections and networks online while possible is more challenging, so I am focused on creating a local group to foster this. Most participants are from the University of Sheffield. However, there are also individuals from Sheffield Hallam University and outside academia, such as Simon Rolph from the UK Centre for Ecology and Hydrology, who gave an excellent talk on the targets package. We’ve also had talks with Robert Smith and Wael Mohammed of Dark Peak Analytics.\nOne of my challenges is that I have a daughter, so I usually need to be home in the afternoons to take care of her. I appreciate that attending events in the evenings isn’t possible for everyone. Finding a suitable time for everyone is difficult. If we have meetings at lunchtime, we get a lot of university attendees, but only a few from farther away because they would have to travel. You can please some of the people sometimes, but you can’t please all the people all the time.\nYour group recently hosted Hacktoberfest events. Can you share more about the topic covered? Why this topic? \nHacktoberfest celebrates open source software and encourages people to find their favorite open source project to contribute to. Our first meeting was on October 4th, and then we had one every other Friday throughout October.\nThe main objective was to help people get comfortable contributing to open source software, especially those who use R but may not be familiar with version control using Git and GitHub. In the first session, I used material from my job as a research software engineer, where I’ve been teaching a course Anna developed on using Git and GitHub for the past year or two. This course covers the basics of version control and includes a collaborative exercise using a GitHub repository.\nParticipants learned how to fork the repository, make changes locally, push their changes, and create pull requests. The following three weeks were dedicated to providing support, where others and I with experience in version control and using R were available to assist others. The goal was for people to help each other during this time and not rely solely on me or my colleagues as organizers, as some individuals may have more knowledge than others. It was great to see everyone coming together to support one another, as some people may have more expertise in specific areas than I do.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future? \nI have a GitHub issue template in place to help organize our meetings. I use GitHub to plan events because my memory is terrible. I’d likely forget something important if I didn’t have everything written down. Whenever we plan an event, we create a GitHub issue and assign it to me or Grace. It’s a checklist of tasks such as booking a room, setting dates and times, confirming speakers, obtaining consent for photography during the event, and listing places to advertise the event. This checklist helps us keep track of everything that needs to be done for each event.\nThe Sheffield R user group used to meet in a local pub. However, when we restarted the events, we decided that using more neutral spaces would be more inclusive, so we use university buildings now. We want to ensure everyone feels welcome, so we choose accessible venues for people with disabilities. It’s important to me that everyone can attend without any barriers.\nWe also run hybrid meetings, which I find challenging. When I have a group of people in the room, I naturally tend to speak to them. I have to remind myself to pay constant attention to the online participants. It’s helpful to have another organizer keeping an eye on the online side of things when people raise their hands. Despite the challenges, we continue with hybrid meetings because they’re a good way of allowing people to attend if they can’t make it in person.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nI’m working on a project with a PhD student trying to improve thyroid cancer prediction. When he approached me, he used SPSS for his analysis because that’s what one of my old colleagues had taught him. From now on, I encouraged him to switch to using R for all his work, and I’ve helped him set up version control for it.\nHe has learned to write Quarto documents with embedded R code to write the manuscript he wants to create. This has been very useful. He has also learned how to use a multiple imputation package that he hadn’t used before to summarize the results and check their consistency with the observed data. At one point, the PhD student and his supervisor wanted to create a website where people could enter various characteristics about a patient and receive a risk profile indicating whether the lumps in their thyroids were likely to be malignant. To achieve this, he revisited his knowledge of Shiny to get the website up and running. However, he was aware that it might be something they wanted to put into production. Consequently, he discovered the Golem package, which appears to be a handy tool for taking Shiny and developing it more rigorously for deployment to production. This has been the main focus of his recent work with R.\nI’ve been using Quarto and R for my blog and some small tasks lately. I’ve written several posts about pre-commit for linting code, which is really useful. I’m overdue writing one on how to use the lintr package and should find time to investigate the newer flint package too.\nI also had a project where the researchers used R and had a lot of code. I convinced them to organize their code into a more structured package format. I found DevTools and the usethis package to be very helpful for that. At the same time, I set up the package repository to use linter to ensure that all coding standards were followed in case they ever decided to release it to CRAN.\nI feel like a jack of all trades because I use Python, R, and a bit of Bash. I know a little about everything, but I’m not an expert at any one thing!\nHow do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nhttps://r-consortium.org/all-projects/rugsprogram.html" }, { - "objectID": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html", - "href": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html", - "title": "Kolkata R User Group: A Rich History with Statistics", + "objectID": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html", + "href": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html", + "title": "Full-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks", "section": "", - "text": "The R Consortium recently spoke with Samrit Pramanik of the Kolkata R User Group about his experience starting a new R User Group in India. Samrit highlighted Kolkata’s rich history with statistics and talked about the diverse local R community.\nThe Kolkata R User group is organizing its second online event titled “A New Approach for Teaching Data Analytics with R” on July 13th. R users from around the world are invited to join this event.\nPlease share your background and involvement with the RUGS group.\nMy name is Samrit Pramanik. I work as a data scientist at a US-based private firm and have a post-graduate degree in statistics from the University of Calcutta. I have been using R since my post-graduate days in 2018 and used it extensively in various projects during my studies. Since 2022, I have also been an R instructor for a non-profit organization. Additionally, I have been involved in several short projects working with R. Since April 2024, I have managed the Kolkata R User group.\nThis is the third city-based R user group in India that is affiliated with the R Consortium. I plan to arrange virtual meetups monthly and in-person meetups annually. I enjoy helping and teaching people from diverse backgrounds, not only in statistics, mathematics, and data science but also in other areas. I want to teach them to use R language to add value to their professional and personal projects.\nCan you share what the R community is like in Kolkata?\nThe Kolkata User Group has been formed with a broader perspective that I would like to share with you. Kolkata is known for its reputation in statistical research and education. The city is recognized as the birthplace of modern statistics in India, with the establishment of the Indian Statistical Institute (ISI) in 1931 by a prominent figure in statistics. The University of Calcutta, where I graduated, was the first in Asia to offer a post-graduate degree in statistics in 1941. This rich history made the formation of the Kolkata R User Group inevitable. Our community consists of academics and professionals from diverse fields such as life sciences, healthcare, the public sector, physics, astrophysics, and other industries. This diverse background facilitates robust exchanges of ideas and techniques related to R and data, making our R community in Kolkata truly unique.\nPlease tell us about your recent and upcoming events?\nI would like to highlight a recent event. Last month, in June, we had our inaugural session where we introduced Quarto, a recently released reporting tool by Posit. Our goal was to make the participants aware of this tool and its outstanding features, such as website building, ebook writing, creating thesis papers, manuscripts, and blogging sites. We aimed to show participants, including early graduate students, professionals in the industry, and researchers from academia, that they can use Quarto in their projects and studies for reporting. This was our first organized session.\nThe upcoming session is scheduled for July 13th. It will focus on a new approach to teaching R to students with non-technical backgrounds such as business students. Dr. Abhimanyu Gupta from Saint Louis University will be the speaker at this event.\nWe have received very positive feedback and responses from the participants who are showing interest in the upcoming events. They want us to organize such events frequently. People are very much aware of these events and this community. They are very responsive, and we have received positive responses. Two esteemed Economics professors have expressed interest in joining our organizing team and working with us.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nCurrently, I am working on two projects. The first project involves cricket analytics, where I extensively use R for cleaning up messy raw data and conducting exploratory data analysis at both the team and individual player levels and published a shiny dashboard on performance analysis of T20I players. I’m also building a statistical model to predict the total score of an innings, the winner of the match, and the tournament. Lastly, I aim to compile all the findings into an ebook format.\nCricket Performance Analysis Shiny Dashboard\nThe second project revolves around converting the functions and features of AstroPy, an open source software package for astronomy and astrophysics, into R. Our goal is to enhance its popularity among researchers and scientists in the astronomy, astrophysics, and cosmology domains. I am collaborating with another individual from a physics background on this open source project, and we plan to publish it on GitHub soon for public access." + "text": "The R Consortium recently interviewed Victor Lee, organizer of the Korea R User Group, about his role establishing and expanding the Korean R community. Victor shared his journey, beginning with an introduction to R and open source programming languages while working at the Hyundai Motor Company, and later, his efforts in establishing the tidyverse community in Korea. He highlighted his extensive experience with R, including writing blog posts, publishing Quarto books, and building websites for the Korea R User Group. Victor will be a Software Carpentry instructor at the Software Carpentry Workshops at Sejong University.\nPlease share about your background and your involvement in the R Community.\nMy first introduction to our community was about 10 years ago, and it wasn’t a good experience. I used to work at the Hyundai Motor Company at that time and was intrigued by the software carpentry led by Greg Wilson. I also delved into statistics and open-source programming languages, particularly S and R programming. I was heavily involved in posting about tidyverse, which was my entry point into the community environment. In Korea, I sought out the Korean community, which mainly focused on the basics. This made me realize the need for a community in Korea based on tidyverse principles, and that’s why I started the tidyverse community in Korea 10 years ago.\nI was first introduced to S-PLUS during my undergraduate years as a statistics major, and I was fascinated by its superior graphics compared to SAS/SPSS. After majoring in computer engineering and working at Hyundai Motor Company for 10 years, I obtained a Software Carpentry Instructor certification and translated “Python for Informatics” into a Korean book. I became captivated by the Hadleyverse, and Since 2016, I have been co-organizing the Seoul R Meetup, sponsored by Kyobo DPLANEX (a continuous sponsor and is currently the largest sponsor of the Seoul R Meetup, representing one of South Korea’s leading insurance companies) alongside Choonghyun Ryu, the founder of the Korea R User Group. In 2021, we hosted the Korea R Conference, and in 2021, we established the Korea R User Group as a non-profit organization, transitioning from a community to an official organization.\nWhat is your level of experience with the R language?\nWith the support of the R community, ChatGPT, and Copilot AI, I now confidently tackle any data science problem using R. For about 10 years, I’ve consistently written blog posts using R Markdown and now Quarto. Upgrading my e-books with Bookdown led to the publication of five Quarto books on data science. Using the Quarto framework, I also built the Korea R User Group and R Conference websites. As a civic data journalist, I’ve written around 100 articles utilizing R’s visualization capabilities. Reflecting on my journey, I see how effectively I’ve applied the R language in various fields.\nWhat industry are you currently in? How do you use R in your work?\nI originally set up the Korean R community 10 years ago and am a founding member of the nonprofit Korea R User Group, established three years ago. I left KPMG to dedicate my time to running the Korea R User Group. This year, I have been fully involved in managing the organization and leading several projects, including two major abandoned projects, focusing on them for the past few months.\nCurrently, I am focusing on publishing and developing open statistical packages at a non-profit public interest corporation. In 2020, with good intentions, I started the “Open Statistical Package” project to independently develop statistical packages like SAS, SPSS, and Minitab. However, some Shiny developers without a strong background in statistics took the project in their direction, causing it to lose steam. It felt as though they had hijacked the project and the hard work the Korea R User Group put in, leaving us frustrated and disappointed.\nTo prevent this kind of thing from happening again, we’re beefing up our license policy, including trademark registration for BitStat[1]. We’re also switching up our development engines to webr and shinylive and are in the process of creating BitStat2[2].\n[1]: https://github.com/bit2r/BitStat [2]: https://github.com/bit2r/BitStat2\nWe also established a publishing company named “BitStat” as the Korea R User Group promoted Quarto digital writing as a new open source project. Recently, we have published and released five data science books, expanding the base of R users. While writing the sixth book on probability and statistics, I restarted the development of open statistical packages using Web-R and Shinylive.\nR has evolved from a simple data analysis and statistical language to a tool that can replace office software. I now use Quarto to create almost all documents, and R is the first language I use in developing the open statistical package that I am currently working on.\nWhy do industry professionals come to your user group? What is the benefit for attending?\nIn Korea, about 20 to 30 years ago, R was the number one programming language for data science and statistics, particularly in areas like machine learning. However, with the rise of Python, many R users transitioned to Python due to its increasing popularity. Despite this shift, R remains significant in Korea, with many people continuing to use both R and Python.\nFor my day-to-day work, I find R quite convenient and easy to use, especially for therapeutic data and open-source case studies. This year, I’ve noticed that users who join the Korea R User Group come from diverse backgrounds, including drug discovery, regulatory agency, and real estate.\nOver the past decade, many users joined the group to determine whether Python or R was better suited for their work. However, the recent trend clearly leans towards artificial intelligence development, such as LLM (Large Language Model) development. Participants from various industries with an interest in quantitative analysis are now attending the user group.\nTheir motivation for attending, apart from AI fields represented by LLM, is to acquire the latest technology in other data science areas and to gain knowledge from diverse, in-depth analysis experiences and model development. Additionally, many people come to obtain information about Quarto, ggplot, gt, and shiny, seeking business opportunities related to these tools.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nThis year, our community in Korea is focusing on Quarto due to upcoming government policy changes. Analog methods are expected to disappear within five years, so the government is funding the development of AI digital textbooks. I believe Quarto technology, the next generation of R Markdown, is perfect for this purpose.\nAs generative artificial intelligence (AI) has gained significant attention in Korea, there is growing interest in using R and Python together with generative AI to solve data science problems and increase productivity, rather than focusing on the languages themselves. When using generative AI with languages such as R, Python, and SQL, it becomes necessary to find tools that can automate and store the outputs, inevitably leading to increased interest in Quarto.\nThis perspective has been reinforced by my experience using Quarto in various ways, starting from R Markdown. I have come to realize that Quarto is truly well-suited for generative AI and data science. If other countries are developing AI texts using Quarto or R Markdown, we could introduce this technology to the Korean market and the Korean government.\nHaving written five books – plus a sixth on probability and statistics – I’ve experimented with various features of Quarto books. I’ve realized we no longer need older statistical packages like SAS and SPSS. My current project involves implementing statistical software using WebAssembly (WASM) technology.\nWe would like to get to know you more personally. Can you please tell me about yourself? For example, your hobbies/interests or anything else you want to share.\nInitially, I wasn’t sure if I would succeed, but I became involved in election campaigns and grew passionate about analyzing political and election data. My interest lies in using data to uncover trends and insights from various social datasets.\nNext month, we will have a data journalism meetup, and I have friends who will join because of the articles I wrote. They will showcase some of their analyses on TV, including summaries of data related to election campaigns.\nI first developed a connection with data while majoring in statistics and then pursued computer engineering in graduate school. Although this combination of backgrounds is common now, it was unusual in Korea at the time, giving me a unique career path. My passion for open-source software and faith in the community have driven me to where I am today.\nI enjoy analyzing data, and whenever I come across interesting datasets, I analyze them and document my experiences on my blog. This hobby, along with the copyright-free nature of data, led me to develop an interest in predicting election winners using data from annual elections in South Korea. Since 2016, I have experienced three general elections, presidential elections, and local elections. Although there won’t be an election next year, I am very much looking forward to the next one." }, { - "objectID": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html#how-do-i-join", - "href": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html#how-do-i-join", - "title": "Kolkata R User Group: A Rich History with Statistics", + "objectID": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html#how-do-i-join", + "href": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html#how-do-i-join", + "title": "Full-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks", "section": "How do I Join?", "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html", - "href": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html", - "title": "ConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers", + "objectID": "posts/the-2024-isc-grant-program-will-begin/index.html", + "href": "posts/the-2024-isc-grant-program-will-begin/index.html", + "title": "The 2024 ISC Grant Program will begin Accepting Applications Soon!", "section": "", - "text": "Frans van Dunné, the organizer of the San Carlos R User Group, recently discussed with the R Consortium the development of the R community in Costa Rica and the broader Latin American (LATAM) region. He also talked about the growth of events such as the ConectaR conference and the success of the Data Latam podcast, which he co-hosts to delve into data science in Latin America. Additionally, Frans highlighted the challenges of building a data-driven community in a rural area and the creative methods they’ve employed to connect people through R.\nPlease share your background and involvement with the RUGS group.\nI have a background in biology, and during my PhD in tropical ecology, I encountered some statistical questions that I needed to solve through programming. That’s when I started learning to program, initially with Perl. Eventually, I discovered that I enjoyed solving data-related problems through programming, and that led me to R. It was around 2001 when I first started programming in R.\nEventually, I married and emigrated to Costa Rica (my wife is Tica). Knowing no one in the area, I started an R User Group to connect with people and navigate the area.\nVery soon after arriving in Costa Rica, I established my town’s San Carlos R user group. Initially, we held our meetings in-person, but I soon discovered that some attendees traveled for hours by bus to reach San Carlos. Realizing the impracticality, I decided to move our meetings online, and to my surprise, it worked out well. This change occurred even before the pandemic, and we began to see people from Peru and other distant locations joining our group. San Carlos is a small rural area with a population of around 50,000, so having individuals from different parts of Latin America join us was truly amazing.\nOne of the first San Carlos R User Group meetings - February 2016, Ciudad Quesada, Costa Rica\nWe had to stop our online meetings because Meetup informed us that, according to their policy before the pandemic, we wouldn’t be able to use their platform if we didn’t hold physical meetings. The world is different now, but that was the situation back then.\nCan you share what the local R community is like in San Carlos?\nParticipants of ConectaR 2019 - January 2019, San José Costa Rica\nWe collaborated with the University of Costa Rica to organize an event that brought together industry, academia, and citizen science professionals for a conference focused on R. The event is called Conecta R. We started in 2019 and held the latest edition this year, Conecta R 2024. When we started, we wanted to understand R’s current status and usage in the LATAM region. It only confirmed that R is widely used in academia. Most statistics courses have transitioned from licensed software to R. R is also used widely in industry.\nParticipants of the Tidymodels workshop during ConectaR 2024, March 2024, San José, Costa Rica\nAt ixpantia, the company I co-founded, we work with clients in various industries, such as consumer packaged goods, retail, oil and gas, and energy production. Additionally, a significant number of clients utilize our financial services.\nWould you like to tell us about your recent events?\nWe’ve resumed our monthly online meetings for the San Carlos R user group. The meetings now take place on the first Saturday of the month in the morning, and anyone is welcome to join through Meetup.com. Our last meeting was held recently, and it was great to see familiar faces returning.\nAdditionally, we have a podcast called Data Latam, which covers topics related to data science, not just R. We aim to release a new episode every month. We run this podcast in parallel with meetings, serving a similar purpose. It’s about providing examples and even role models of professionals working with data to show that you don’t need to be an IT professional or a programmer to work with data.\nPlease share more about the Data Latam podcast. How did you come up with the idea of starting it? Would you like to highlight a few of your favorite podcasts from this series?\nThe story behind the Data Latam podcast is funny. The co-host, Diego May, and I met through an R Package I wrote to access data from an open-data platform he had developed. We shared an interest in using data and data science to help the development of LATAM and agreed to start a podcast to get to know each other better. Within two months, we had the first opportunity to start a project, and that is when we founded ixpantia, which brings best practices in data science, data engineering, and data strategy to LATAM.\nWe have done 110 podcasts to date! It seems like a lot, but we learn so much from every conversation that it hardly feels like an effort. Some of my personal favorites that are related to R include Episode 109 with Noam Ross, where we talked about rOpenSci, episode 98 with Sherly Tarazona about her work and R-Ladies Lima, episode 85 with Tareef Kawaf from Posit and episode 75 with Jorge Ahumada about the work they do at Wildlife Insights. I could go on, but pointing to the complete list at www.datalatam.com makes more sense. I’m sure there is something for everyone interested in data there.\nDo you recommend any techniques for planning for or during the event? (Github, Zoom, other.) Can these techniques be used to make your group more inclusive to people who cannot attend physical events in the future?\nOnline events are great. I live in a rural area, and attending a physical event, even here in Costa Rica, requires a long three-hour drive to the capital. We have done that and will do it again, but having the option to go online is much more practical and has a broader reach.\nWhen we started our first online meetings, we used Google Hangouts, which would fry my laptop after one hour. These tools have improved so much over the last few years, largely pushed by the boom in remote work during the pandemic. We still like Zoom and its functionality for setting up and executing events, including registration.\nParticipants of the Datathon 2019 in San Carlos, August 2019, Santa Clara, Costa Rica\nWe have organized two datathons (similar to a hackathon but focused on data) that were incredibly enjoyable and well-attended. The key to their success was our partnerships. One datathon was organized in collaboration with the Costa Rican government, and the other involved two local universities: The University of Costa Rica (UCR) and the Costa Rica Institute of Technology (TEC). I still meet people who attended these events and have fond memories of them." + "text": "The R Consortium is excited to announce the second cycle of the 2024 Infrastructure Steering Committee (ISC) Grants Program. The Call for Proposals will open soon. This initiative aims to support projects that strengthen the R ecosystem’s technical and social infrastructure. \nHere is a list of projects that received grants from the R Consortium in the First Cycle in 2024. \nFrom the Call for Proposals page:\nThe ISC is interested in projects that:\n\nAre likely to have a broad impact on the R community.\nHave a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it up into smaller chunks (a good example of this done is with the DBI/DBItest project submission, where multiple proposals came in over time to address the various needs).\nHave a low-to-medium risk with a low-to-medium reward. The ISC tends not fund high-risk, high-reward projects.\n\nWhether you’re working on groundbreaking tools or organizing community-driven events, this is your chance to secure funding and make a significant impact on the R community!\nKey Dates:\n\nSeptember 1, 2024: Grant Application Period Opens\nOctober 1, 2024: Grant Application Period Closes\nNovember 1, 2024: Notification of Accepted Grantees\nDecember 1:  Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\nSubmit your proposal by October 1, 2024, and contribute to the ongoing growth of the R ecosystem. Visit the R Consortium website for detailed guidelines and submission instructions. Don’t miss this opportunity to bring your innovative ideas to life!" }, { - "objectID": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html#how-do-i-join", - "href": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html#how-do-i-join", - "title": "ConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers", + "objectID": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html", + "href": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html", + "title": "Keith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R", + "section": "", + "text": "Keith Karani Wachira, the Dekut R Communityorganizer based in Nyeri, Kenya, was recently interviewed by the R Consortium and shared his journey in the R community, which began in 2019 during his university years. Sparked by a tech meetup, Keith’s interest grew through the pandemic sessions. Now in academia, he uses R to address business automation challenges, attracting industry professionals to his practical sessions. Excited by trends like AI integration and tools like Quarto, Keith foresees increased automation and efficiency. Outside work, he enjoys baseball, graphic design, web development, and teaching R, finding great reward in his students’ success.\nPlease share about your background and your involvement in the R Community. What is your level of experience with the R language?\nI began my journey with R in early 2019 while studying at university. In May 2019, I learned about a tech community through a friend who posted in one of our school’s WhatsApp groups, inviting us to join a meetup. Curious, I decided to attend.\nI remember the meetup was on a Saturday, and it turned out to be the launch of a new club. My friend invited me and was part of the Microsoft Learn Students’ Ambassadors. His classmates used R for their engineering projects, which sparked my interest.\nDuring the first lesson, I found it challenging as there were about 30 students, most of whom were first-year students pursuing various degrees, including Business Information Technology, which I was majoring in, along with a minor in Communication. My first programming language that year was C, which I found interesting.\nOver time, I found the R language interesting, especially its syntax. What fascinated me the most was how data could be used to create visualizations. This curiosity led me to explore data from my local sewerage and water company, using R to create informative visualizations and derive insights that can be used in decision making.\nI continued attending the sessions in 2020 during the pandemic. Although we no longer had in-person classes, we adapted using Microsoft Teams for our meetings. Eric organized the meetups and arranged tech talks with speakers from Posit (formerly RStudio) and NairobiR. I remember attending these sessions and understanding how powerful R is.\nThroughout 2020, I attended regularly but still lacked confidence in the language. However, in 2022, I made significant progress. Under Eric’s leadership, we expanded the community to involve more people, especially students from the department of Actuarial Science, Telecommunication Engineering and electrical engineering. We set up a structured learning environment based on materials from Hadley Wickham’s books and resources from the R website and blogs.\nEric’s leadership greatly influenced me. He taught us how to write blogs using Markdown and publish on RPubs. This is a bit about my background. Today, we continue to teach R, following a structured approach to help others intermediate in using the language.\nWhat industry are you currently in? How do you use R in your work?\nI’m currently in academia, primarily focusing on various technical challenges. We hold sessions where we demonstrate the use of R in robotics for members in Electrical Engineering and Telecommunication Engineering. For those in Actuarial Science, we show how to create time series models using R.\nComing from a background in business and information technology, I focus on solving business challenges, particularly automating business processes and addressing issues in banking, logistics, retail using opensource datasets. Our efforts are not limited to academia; we concentrate on applying R across different disciplines within academia to tackle these challenges.\nWhy do industry professionals come to your user group? What is the benefit of attending?\nAn interesting scenario arose when I became interested in EMS (Engineering and Management Systems). We started organizing hybrid sessions after the COVID period and it caught interest of students from another university in Kenya ,Egerton University. Through, statistical analysis bureau of Egerton University they joined our sessions to learn how to leverage tidy models packages to create machine learning models and also collaborate with the community members.\nThey were very interested, and as future economists, we demonstrated how to build and appreciate these models. In previous meetups, we also introduced participants to Shiny apps, teaching them how to host their models and create interfaces to display their work.\nAnother valuable skill we taught was generating reports using R Markdown. This allows users to write code, format text, add videos, images, and emojis, and present their work in a professional and engaging manner. Attendees found this particularly useful as it enhanced their ability to write, structure, and report code effectively.\nParticipants learned to leverage the R ecosystem for coding, structuring their work, and reporting their findings by attending our sessions.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nA trend I’ve noticed is the widespread effort to include everyone in learning programming languages like R. This is evident in the emergence of specialized groups such as R for Medicine and R for Pharma. Two of our alumni even demonstrated how R can be used in robotics through a talk at Posit Conference 2022, demonstrating its applicability in specific industries. This specialization fascinates me, and I am eager to see how R will be used across various fields.\nAnother trend is using tools like Quarto, which facilitates the implementation of such specializations. Additionally, I am excited about the incorporation of AI in building R applications, such as using Gemini for Shiny apps. Although materials on this are currently limited, I see this as a growing trend.\nThe integration of AI will likely lead to the automation of many manual processes, further enhancing R’s utility and efficiency in various industries.\nWe would like to get to know you more personally. Can you please tell me about yourself? For example, your hobbies/interests or anything else you want to share.\nWhen not in front of my laptop, I enjoy playing baseball and softball, especially as a catcher. Catching allows me to see the entire game command the play, and I enjoy throwing the ball from home to second base and picking off a runner. It’s a challenging position that helps me focus and improve my aim.\nOn the side, I also do some graphic design using Canva which I use to create posters and newsletters for our community meetups. Additionally, I have web development skills using MERN stack.\nAnother passion of mine is teaching R to others. I love seeing people learn and apply the concepts and then go on to teach others. One of my students from his first year has now taken over as a lead in our community, which is incredibly encouraging. He even competed in hackathons and finished fourth, showing how much he has grown.\nTeaching and seeing others succeed is something I find very rewarding and motivating." + }, + { + "objectID": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html#how-do-i-join", + "href": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html#how-do-i-join", + "title": "Keith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R", "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nhttps://r-consortium.org/all-projects/rugsprogram.html" + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more\n\n\n\ngd2md-html: xyzzy Mon Jul 29 2024" }, { - "objectID": "posts/unlocking-the-power-of-r-for-insurance-and-actuarial/index.html", - "href": "posts/unlocking-the-power-of-r-for-insurance-and-actuarial/index.html", - "title": "Unlocking the Power of R for Insurance and Actuarial Science: Webinar Series Recap", + "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html", + "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html", + "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", "section": "", - "text": "The R Consortium recently hosted a webinar series tailored specifically for insurance and actuarial science professionals. This series, called the R/Insurance webinar series, led by experts Georgios Bakoloukas and Benedikt Schamberger, was crafted to guide attendees from transitioning from Excel to R to implementing R in production environments, fostering a performance culture with R, and mastering high-performance programming techniques. \nWhether new to R or looking to deepen your expertise, these webinars offer valuable insights into leveraging R’s capabilities in your field. All sessions are now accessible on YouTube, providing a fantastic resource for ongoing learning and development. \nFor further details and to watch the webinars, visit the R Consortium’s website." + "text": "R/Pharma 2024 is coming up Oct 29-Nov 1, 2024. This is a free event, fully virtual. R users in Pharma around the world are encouraged to attend, ask questions, and contribute their opinions!" }, { - "objectID": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html", - "href": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html", - "title": "The Impact of R on Academic Excellence in Manchester, UK", - "section": "", - "text": "The R Consortium recently spoke with the organizing team of the R User Group at the University of Manchester (R.U.M.). R.U.M. aims to bring together R users of all levels to share R best practices, expertise and knowledge. The group is open to all staff and postgraduate researchers at the University of Manchester, UK.\nDuring the discussion, the team shared details about their recent events and their plans for this year. They also discussed the latest trends in the R programming language and how they are utilizing it in their work.\nMartín Herrerías Azcué\nResearch Software Engineer\nUniversity of Manchester\nAnthony Evans\nResearch Software Engineer\nUniversity of Manchester\nLana Bojanić\nResearcher PhD Candidate\nUniversity of Manchester\nRowan Green\nPhD Student in Evolutionary Microbiology \nThe University of Manchester\nPlease share about your background and involvement with the RUGS group.\nMartin: My name is Martin, and I joined the University of Manchester a year ago. They assigned me to manage the R user group, which was previously under Camila’s leadership. Although I am officially in charge, this is a collaborative effort between all of us who are present in this meeting, along with some others who couldn’t join. I work in Research IT and mainly use R for projects assigned to me by other people.\nAnthony: My name is Anthony and I work at Research IT with Martin at the University of Manchester. I first came into contact with R when I was a student. Later, I became a helper at many of the university’s R training courses based on the Carpentries training courses. Camila, who was Martin’s predecessor, was also a trainer at R and she formed the R Users Manchester group. I volunteered to help her with the group a year ago, and it just turned a year old. After that, I continued to be a part of the group.\nLana: Hi there, my name is Lana. I am a PhD student and research assistant at the Division of Psychology and Mental Health at the University of Manchester. I have been using R for the past six years, ever since my Master’s degree. I have been a part of the group since its inception and have been running R introduction sessions for beginners within my division for a couple of years now. When I learned the group was being formed, I contacted Camila a year ago. This makes us founding members of the group.\nRowan: Hello, my name is Rowan Green. I am currently a PhD student in the Department of Earth and Environmental Sciences. For my research work, I use R extensively for simulation modeling bacteria, analyzing lab data, and creating visualizations. The best thing about using R is that it produces much prettier visualizations than other options available to us as biologists. We have a lot of master’s and undergraduate students coming through the lab. I often give them pre-written scripts they can tweak to create their plots. It’s exciting to see them working hard to produce their plots.\nCamilla mentioned starting a group to share knowledge about R on a university-wide level. I found this a great opportunity to participate and learn from others’ presentations during the meetings. It has been an enriching experience so far.\nCan you share what the R community is like in Manchester?\nAnthony: In industries such as banking and finance, R is frequently used to create graphs to showcase econometric data in an easy-to-understand manner. The graphical capabilities of this programming language make it a popular choice in these fields. The university we’re in has access to the Financial Times, which is known for producing visually stunning graphs. Interestingly, they also use an R package called FT plot tools, which is a specialized package solely for their use. So, it’s safe to say that R has a significant presence in the banking and finance sectors.\nAre your meetups virtual or in-person? What topics have you covered recently? What are your plans for the group in the future?\nMartin: Our events are a mix of in-person and online meetings. There have been talks about developing packages, data visualization, automating reports, and working with tables. We usually cover topics we are confident about or know people from the university are working on. However, we are also trying to get external speakers to come and talk. It’s challenging, but we are doing our best to make it happen. We are currently accepting proposals from potential speakers.\nOur book club has mostly or completely taken place online.\nLana:  Bookclub was mostly online. During the summer book club, we were reading R for Data Science. We covered a chapter or two chapters each time. We had the book’s second edition, and people from all over the university joined the club.\nWe were discussing the possibility of changing the format of Tidy Tuesdays. We received feedback that people don’t have enough time to come up with something extra creative every month. Additionally, there has been a need for more practice. Therefore, we plan to redesign Tidy Tuesdays to be more practice-oriented than creativity-oriented. We will be implementing these changes this year.\nAnthony: We’ve recently had several discussions on useful packages, particularly in R. Some packages that were developed and published were custom-made. We also had presentations on the cosinor and cosinor2 packages, which are used for fitting curves, and an R update package for validating clinical prediction models.\nThere are two other R groups in Manchester. Our aim for this year is to establish communication with them and collaborate in a coordinated manner. (Editor’s Note: We recently talked with the Manchester R User Group.) Currently, our group solely focuses on the internal R community at the University of Manchester.\nAny techniques you recommend using for planning for or during the event?\nRowan: I’m not sure if everyone would agree with me, but I think we did well in the format of our meetings. We started with brief, brief talks – within an hour – followed by questions and discussions, which worked well.\nHowever, the harder part has been promoting and informing people about the meetings. Sometimes, word of mouth has been more effective than emails and posters. I noticed that they were interested in attending when I encouraged my lab group, who all use R. But without any scheduled reminders and someone to encourage them, it may be difficult to get people to come.\nLana: It’s important to identify everyone’s strengths or specialties within the organizing group, as they will probably be useful in the first few events. After that, you can expand your network within the community, which is easy to do since people are easily reachable. This will allow you to find interesting topic ideas and strengths to draw from.\nWhat trends do you currently see in R language?\nMartin: I’ve noticed a growing interest in Shiny lately, as I manage a pilot server for the university and have seen an increase in users over time. There have also been several inquiries about using R within our high-performance computer cluster, which may be something we can offer to the university. This interest is not surprising, given the current hype around machine learning.\nA trending area that applies to multiple platforms, not just R, is towards reproducible research and compatibility between different programming languages. This means that R can be integrated with Python and other languages to create a documented and integrated pipeline. I’ve been experimenting with SnakeMake, which works well with R, but it would be great to see more integration from the R side, perhaps through the common workflow language or another similar tool.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nRowen: Recently, I wrote a preprint of a paper where we simulated the growth and mutation of bacteria using differential equations and R programming language. To perform the simulation, we utilized high-performance computing, which enabled us to simulate various ways the bacteria could grow by adjusting the rates of reactions occurring within the cells. This simulation required high-performance computing to be feasible for running multiple simulations.\nAfter running simulations, we came up with some ideas to test in the lab. Our focus was on measuring mutation rates, and we used statistical analysis to estimate them through R. We have been striving to ensure reproducibility, and as a result, we have annotated all the data tables and R scripts with the paper.\nIt has been an interesting journey for me. I had to tidy up my messy scripts and think about how someone else would perceive them. I had to ensure they made sense. However, the project was fascinating as I generated hypotheses using R, tested them, and analyzed and visualized them with the same tool. R is a complete tool that can handle all aspects of the process, making it a brilliant choice." + "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free", + "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free", + "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", + "section": "Register now for free!", + "text": "Register now for free!\nFor the first time, R/Pharma will be including a dedicated Asia-Pacific (APAC) track which better aligns with Asian time zones and includes 2 pre-conference workshops, 3 keynotes that will be recorded from the global track and then streamed with live discussion sessions thereafter, and 2 live panels, one focusing on Japan, and one on China. In addition, there are 20 contributed talks.\n\n\nThe R Consortium talked with Daniel Sabanés Bové, R/Pharma organizer, co-chair of openstatsware.org, co-founder of RCONIS, a biostatistics consulting and software engineering firm, (co-)author of multiple R packages published on CRAN and Bioconductor, and author of the book “Likelihood and Bayesian Inference: With Applications in Biology and Medicine.” Daniel is giving a 3-hour workshop on October 27 with Joe Zhu (Roche) on “Good Software Engineering Practice for R Packages,” and introducing openstatsware in a talk on 31 October.\nWe talked to Daniel to find out more about the new APAC track.\n\n\nWhy is R/Pharma adding an APAC track now?\nLast year, I was on an extended business trip for Roche for 6 weeks in Shanghai. I was fortunate to attend the first China Pharma R User Group (RUG) Meeting in March 2023, so I have seen how active the community is. I also found out how tough it can be to be based in Asia - you just don’t get enough sleep working with colleagues in Europe and North America!\nSo when the R/Pharma program committee reported that they have been approached by colleagues in Asia about organizing events in their time zone or region, I used the opportunity of my upcoming move to Taipei mid 2024 to propose organizing a dedicated track in the Asia-Pacific timezones.\nThe R/Pharma APAC track is designed specifically to help avoid time zone burnout, as well as to foster the APAC regional community.\n\n\nHow does adoption of R in Pharma in APAC differ from other parts of the world?\nThis is not based on robust data, but from a personal perspective I have noticed one key feature is that biotech and Pharma companies in Asia are concentrated in a few hubs, there is Shanghai, Tokyo, and not too many more. Having said that, I have noticed the rise of Contract Research Organizations (CROs) e.g. in India that are starting to use R - the CROs are catching up. Compare that to Europe and the United States, with a wide range of Pharma companies and organizations spread around many different locations. This also influences the adoption of R and open source technologies in general.\n\n\nWhat are some of the key topics being covered in the APAC track?\nI was pleasantly surprised at the amount and variety of proposals submitted. We have organized the APAC track’s topics into 6 types of sessions:\n\nChange management (moving from proprietary software to R)\nSessional clinical reporting (producing tables and reports)\nShiny\nBest practices\nAI/ML\nHigh dimensional data\n\nWe have quite an exciting APAC Track program that includes:\n\n2 pre conference workshops\n3 keynote streams, which are recorded keynotes that are slightly delayed to stream during convenient APAC times, plus we have added some discussion after\n2 live panel discussion (China, Japan)\n20 contributed talks in total\n\n\n\nFull Agenda\nA full list of workshops, keynotes, talks and panels is available here.\nIf you use the filter button you can get just the APAC Track information." }, { - "objectID": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html#how-do-i-join", - "href": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html#how-do-i-join", - "title": "The Impact of R on Academic Excellence in Manchester, UK", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute." + "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free-1", + "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free-1", + "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", + "section": "Register now for free!", + "text": "Register now for free!\nIf you, or your organization, would like to support R/Pharma you can do so following this link. Be sure to follow the R/Pharma blog, LinkedIn and Twitter/X." }, { - "objectID": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html", - "href": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html", - "title": "Collaborative Growth: The Botswana R User Group and Regional Partnerships", + "objectID": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html", + "href": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html", + "title": "Ann Arbor R User Group: Harnessing the Power of R and GitHub", "section": "", - "text": "In 2022, Edson Kambeu, founder and organizer of the Botswana R User Group, shared his plans with the R Consortium how the “New R Community in Botswana Wants to Implement Data Into Local Businesses. In this new interview, Edson updated the R Consortium about the group’s growth and recent activities. The Botswana R User Group has attracted a global audience through its online events and actively collaborates with R User Groups in the region.\nThe Botswana R User Group is seeking speakers for their upcoming online events. If you are an R expert interested in sharing your experience with R users in Botswana, please contact Edson at botswanarusers@gmail.com\nPlease share about your background and involvement with the RUGS group.\nMy educational background is in finance. I pursued finance and investments for my master’s degree but also studied economics during my undergraduate years. Mathematics has been my strongest subject since primary school, and I’m passionate about it. This passion led me to develop an interest in Statistics and statistical software.\nIn the past, I mainly used SPSS, Stata, and EViews for my statistical analysis projects. Then, someone introduced me to data science. During my research on data science, I discovered that two popular programming languages are used for it. I installed Python for the first time, but I could not use it as I didn’t have a computer science background. So, I switched to R and started watching a few YouTube videos. From there, I continued to learn and improve my skills in R.\nR was my first language of choice for Data Science. Currently, I use both R and Python for my work.\nI am pursuing a Master’s in Computer Science with Data Science from the University of Sunderland. Our different modules use R and Python, and knowing both languages is helping me in my studies.\nAs I was learning R around 2019 and beginning to follow several R Users on Twitter, I discovered that small R communities gathered together to learn and share knowledge about it. R Ladies Johannesburg in South Africa inspired me the most, as they held events more frequently during that time. I then became interested in starting an R User community in Botswana.\nIn February 2020, I reached out to Heather Turner, who was scheduled to visit Botswana and other Southern African countries to conduct Introduction to R workshops. During our conversation, Heather provided me with all the information needed to start a community. As a result, in March 2020, Botswana R Users was established during Heather Turner’s Introduction to R workshop.\nHow has your group been doing since we last talked?\nOur meetup group had about 100 members when we last talked to you. We now have almost 400 members. However, I have observed that people from different countries are joining us. We are now a global meetup group rather than a Botswana User group. This is because we mostly hold online meetups, which allow people from other countries to join.\nParticipants attending an online meetup hosted by Botswana R users in collaboration with Estwatini R Users and Bulawayo R\nWe are, however, still committed to growing the local community. We want to see more local participation in our meetup group. Last year, we collaborated with R Ladies Gaborone to organize an introduction to R workshop to increase our local membership. We are pleased to announce that this year, we plan to hold another workshop as a pre-conference event in the upcoming Botswana Deep Learning Indaba conference in July 2024. This workshop will help us to increase our local membership further and create more awareness about our group.\nParticipant at the Introduction to R Workshop held in collaboration between Botswana R users and R Ladies Gaborone\nWe value collaborations with our partner R User meetup groups in Southern Africa. In recent years, we have had regular meetups involving collaborative efforts with the Bulawayo R User Group from Zimbabwe, the Eswatini R User Group from Swaziland, and the Namibia R User Group from Namibia. We have established a routine of holding joint meetups almost every two months, depending on the availability of speakers. The idea is to grow our communities by increasing the frequency of activities.\nVebash Naidoo of RLadies Jozi presenting in an online meetup for Botswana R Users\nYou have a Meetup titled “GIS and Creating Dashboards in R. A case study of conflicts events in Kenya,” can you share more on the topic covered? Why this topic?\nI had an opportunity to attend a series of workshops and webinars organized by the United Nations for their Datathon. I realized the importance of GIS in advancing sustainable development. In January 2024, I invited Godwin Murithi, a GIS specialist, to present a topic on GIS. The topic was “GIS and Creating Dashboards in R. A case study of conflict events in Kenya.” We wanted to expose our members to the rising field of GIS and show them how the R language and various packages can help solve GIS problems. It was a fascinating topic for our participants, and they loved it.\nHow has the use of R evolved in the industry since we last talked?\nWe are observing an increasing acceptance of the R programming language, particularly in universities. Some universities have adopted R as their primary language for statistics and quantitative programs. This trend indicates academic institutions’ growing preference for open source programming languages.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nOrganizing is one of the most challenging tasks. To get speakers, I have primarily used Twitter (now called X) and LinkedIn to communicate with people who might want to speak at our meetup groups. Lately, there has been a problem with sending direct messages on Twitter. The reason is that Twitter has changed its messaging system. Now, to send a direct message, you need to be verified. I have been affected by the fact that my usual way of talking to people has been disrupted. Therefore, I have resorted to using LinkedIn to search for people interested in R and reach out to them. Sometimes, they are too busy or cancel, which can be challenging. However, I have been successful in finding potential speakers through these platforms.\nOccasionally, we use different video conferencing tools like Zoom and Google Meet. We usually rely on these two platforms. However, sometimes a speaker may prefer using Google Meet over Zoom, so we try to be flexible and accommodate their preferences.\nWe also use GitHub. We have our account, and if the speaker has their material on GitHub, they can share the link with us. Alternatively, they can provide us with the material directly, and we will upload it onto our own GitHub account for the community to access. Ultimately, it all depends on the speaker’s preference.\nPlease share about a project you are working on or have worked on using the R language. What is the goal/reason, result, or anything interesting, especially related to the industry you work in?\nOne of my recent school projects was to create a dashboard about UK imports and exports, which I completed towards the end of last year. I developed this project using Shiny and R packages such as Shiny Dashboard, ggplot2, and dplyr.\nI’m currently working on another project that is still in its early stages. The goal of this project is to identify areas in Botswana that require greater financial inclusion. I am currently gathering data and plan to utilize R and Python to apply geospatial techniques.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nI have observed that people find Quarto and GIS techniques interesting. The community is gaining increasing interest in these areas, and I foresee the increasing use of R in GIS applications." + "text": "The R Consortium talked to Barry Decicco, founder, and organizer of the Ann Arbor R User Group, based in Ann Arbor, Michigan. Barry shared his experience working with R as a statistician and highlighted the current trends in the R language in his industry. He also emphasized the significance of organizing regular events and effective communication for managing an R User Group (RUG).\nPlease share about your background and involvement with the RUGS group.\nThroughout my professional career, I have gained extensive experience in various industries as a statistician. Statisticians are often thought of as either staying in one industry for their entire career or frequently transitioning between them. I have followed the latter path, having held positions at Ford Motor Company, their spinoff Visteon, the University of Michigan School of Nursing, the University of Michigan Health System, Nissan Motor Company, Volkswagen Credit (as a contractor), Michigan State University, and currently Quality Insights.\nI have been using the R programming language consistently for several years now. I have extensively worked with R during my tenure at Michigan State University as a member of the Center for Statistical Training and Research (CSTAT). CSTAT serves as the university’s statistical laboratory. Our team heavily relied on R as our preferred software for statistical analysis.\nOur reporting process involved using R Markdown reports. Steven Pierce, the assistant director, developed a highly complex and upgradeable system using R Markdown to process data. This system allowed us to initiate a report and then trigger the R Markdown file to process the data and generate the final datasets for each report. Another R Markdown file was then called to render the report. This streamlined process enabled us to produce about 40 PDF reports within 45 minutes. The process remained relatively straightforward when we needed to make modifications, such as changing the reporting period from fiscal years to calendar years or adding or subtracting individuals, units, or departments.\nI have recently started a new job primarily working with the SAS programming language. Initially, I will focus on gaining proficiency in this area. After that, I will transition to performing more in-depth analysis and ad hoc reporting, requiring me to use additional tools and resources. I have also moved to a new system where we use Hive or Hadoop through Databricks. As part of my role, I am responsible for taking over the current reporting system and identifying future reporting needs. This will require me to use R extensively.\nBefore the COVID pandemic, the R users group met in Ann Arbor. However, the pandemic dealt a major blow to the group, and we are still recovering from its impact. In our efforts to revive the group, we continued with the same theme as before: a mix of programming and statistics. However, we have been focusing more on programming and simpler analysis to make it easier to get the group restarted. We have also introduced some new presenters covering topics such as machine learning pipelines in their presentations.\nCan you share what the R community is like in Ann Arbor?\nR has become a popular programming language in academia and will likely remain relevant in this field. However, general coding and applications are more prevalent in the industrial sector. Python is gaining popularity because it attracts a broader range of programmers, including those who are not data or analytics specialists. Therefore, R will continue to be a significant but specialized tool.\nCurrently, I have noticed a significant decrease in the usage of SAS. This trend is driven by the dislike of license fees among individual and corporate users. The matter is further complicated by corporate accounting practices, where different funding sources may have varying spending restrictions. As a result, organizations may end up incurring higher salary expenses because of the complexity of corporate accounting processes.\nIf a company spends a fixed amount, say $10,000, on SAS licenses yearly, it might not like it. But then, it may hire additional staff to do the same work SAS did earlier. The salary of these people, and other associated costs, may come from a different funding source. As a result, the company may spend a significant amount of money, ranging from $120,000 to $150,000 annually, to replace a smaller amount of $10,000 to $20,000 annually. However, whether this arrangement is acceptable would depend on the funding source.\nDo you have an upcoming meeting planned? What are your plans for the RUG for this year?\nOur next presenter, Brittany Buggs, Staff Data Analyst at Rocket Mortgage, will demonstrate the usage of the GT package for generating tables. Additionally, we are striving to establish closer integration with the Ann Arbor chapter of the American Statistical Association to foster mutual support and collaboration between the groups. We have been conducting hybrid meetings catering to in-person and virtual attendees. Ann Arbor Spark, a local startup business development organization, has generously provided us with a physical meeting space. Our meetings follow a hybrid format, recognizing the convenience and accessibility it offers to many individuals.\nThis year, I aim to have more presenters as I have been doing all the presentations by myself. I plan to raise awareness about R, R Markdown, and Quarto and show people how these tools can be useful. I will promote these tools at the University of Michigan and other companies.\nWhat trends do you currently see in the R language?\nWhen it comes to data analysis, R has a clear advantage. The tidyverse syntax is easy to understand, even for those unfamiliar with data tables or Pandas-like programming paradigms.\nWhen working with data tables, both base R and Pandas use programming languages that differ significantly from English, which can make understanding them difficult. On the other hand, R Markdown has a notable advantage in that it makes it easy and quick to generate HTML documents. For instance, my former supervisor at C-STAT spent much time creating visually appealing PDF documents because his reports were highly customized. However, if your main goal is to produce polished reports relatively quickly, R Markdown is the better option.\nI understand that my main focus is the transition to Quarto. As someone who used to work with R Markdown, I have been learning more about Quarto and adjusting to its features. However, I am concerned about how new users may react to Quarto. I plan to give presentations throughout the year to gauge their responses and better understand any potential issues that may arise.\nMoreover, I’ve noticed that many people are unaware of R Markdown’s capabilities. To address this, I conducted an introductory session on R Markdown for a group at the University of Michigan. During my thirty-minute presentation, the participants were surprised by the diverse functionalities of R Markdown, as they were used to working with JavaScript and basic R. Although I had inferior knowledge compared to some of the individuals in the group, my ability to perform certain tasks using R Markdown impressed them.\nOne of the benefits of R Markdown is its ability to run multiple languages, with each language being executed chunk by chunk. I hope Quarto will also support this feature.\nIn the past, I have presented on calling R from SAS and SAS from R. During these presentations, I demonstrated how to run a SAS job within an R chunk. However, this approach has a limitation. For it to work, SAS must be accessible from the computer running the R code. This means the SAS installation must be on the computer or a network drive that the computer recognizes as a local drive. On a certain occasion, while using Enterprise Guide on a Linux machine, I faced a problem. I couldn’t locate the executable file (EXE) for SAS from my computer, which obstructed me from executing a SAS job.\nIt is now possible for individuals to use R Markdown with their preferred programming languages. For instance, R Markdown can be used with Pandas for most cases, which can help individuals produce visually appealing reports quickly. With this approach, all the work can be done within Pandas, and users need only basic knowledge of R. Therefore, Quarto can be seen as a language for report writing only. I will keep an eye on this situation and evaluate its effectiveness.\nI want to highlight the smooth combination of Git and GitHub with R. I use GitHub frequently in my work, though I am not very skilled because RStudio IDE fulfills most of my requirements. I rarely face conflicts due to my carelessness; I must interact with Git and GitHub manually.\nI highly recommend the book “Happy Git with R” as an essential resource for beginners. This comprehensive guide provides a step-by-step approach to setting up and using Git and GitHub effectively in R.\nWhen using Git in conjunction with R, you can access a detailed transaction history that can be reviewed anytime. I have found this feature incredibly useful and have been able to recover important work using this method. As a data management instructor at MSU, I have also taught my students how to execute this process manually. However, having R Studio automatically handle this task is much more convenient.\nIn fact, I used SPSS to conduct a project and leveraged GitHub as an experiment. I utilized the data management capabilities of RStudio and found the results satisfactory.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nI suggest that RUG organizers should arrange regular monthly meetings. It would be advantageous to fix these meetings on the same day and time every month, as it will help attendees get accustomed to the routine and know when to expect them.\nIn my years of working with different groups, I have noticed that if we don’t consciously communicate regularly, our communication will become less effective over time. This can lead to a lack of new ideas and engagement, and we may unintentionally exclude potential participants.\nFor almost 20 years, I have been part of a group that communicated through a university mailing list. However, we faced difficulties as the list was not easily discoverable through search engines like Google. This made it challenging for new individuals to find or contact us. We have taken steps to tackle this problem by introducing Meetup as a new tool that can be used alongside or instead of our traditional mailing list. The main benefit of Meetup is that it is easily searchable on Google, which makes it simple for anyone to locate and get in touch with our group.\nI want to emphasize the importance of effective communication. Neglecting communication efforts can cause a decline in communication quality. I have personally witnessed this happening in different groups, and I have seen others experiencing similar challenges." }, { - "objectID": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html#how-do-i-join", - "href": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html#how-do-i-join", - "title": "Collaborative Growth: The Botswana R User Group and Regional Partnerships", + "objectID": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html#how-do-i-join", + "href": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html#how-do-i-join", + "title": "Ann Arbor R User Group: Harnessing the Power of R and GitHub", "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html", - "href": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html", - "title": "R4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions", + "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html", + "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html", + "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", "section": "", - "text": "Marcela Victoria Soto, co-organizer of the R4HR -Club de R para RRHH, Buenos Aires, Argentina, recently updated the R Consortium about the group’s recent activities. Last year, Sergio García Mora, the group’s founder, discussed the adoption and expansion of R in human resources in Argentina. Marcela emphasized the importance of data analysis for informed and agile decision-making for companies in Argentina. She also shared details of some of her budgeting, accounting, and annual income tax projects.\nR4HR is holding an online event called “Data Visualization in HR” on June 1, 2024, for Spanish-speaking R users. The meetup will be conducted via Google Meet.\nPlease share your background and involvement with the RUGS group.\nI earned a bachelor’s degree in labor relations and received training as a labor relations teacher at the University of Buenos Aires (UBA). Additionally, I completed a postgraduate course in Human Resources Management from the Pontifical Catholic University of Argentina (UCA) and a Diploma in Computational Social Sciences from the National University of General San Martín (UNSAM). I also attended the Argentina Program at the University of Salta, completing all three program modules.\nWhat industry are you currently in? How do you use R in your work?\nI currently work in the textile industry as the Head of Human Resources. At Yagmour, I use R to present reports on employee turnover, salary reports, accounting entries, etc. Additionally, I use R to consolidate the annual Human Resources budget according to the company’s accounts.\nCan you share what the R community is like in Buenos Aires?\nThe R4HR community is a collaborative space comprising individuals interested in data and human resources. We hold various meetups within the community where projects, R packages, etc., are shared. It is a Spanish-speaking community. The R Club is a meeting space for professionals in the field, where we can share tools, new ways of addressing issues, and novel approaches to similar problems. People who attend and are familiar with R sometimes need to be made aware of everything this programming language offers for simple and complex issues—the benefit of attending lies in sharing and creating spaces for knowledge exchange.\nYou have a Meetup on “Data Visualization in HR” on June 1st, 2024. Can you share more about the topic covered? Why this topic?\nIn June, we will hold a meetup to address Data Visualization in HR using the ggplot2 package, adding interactivity and context with plotly. This topic is not just interesting but also highly practical. Visualization is a great way to interpret data and graphically identify behavior patterns, which can also prompt questions about the presented information. The plotly package can add insights that are not apparent in the graphs. Additionally, plotly allows for creating interactive visualizations, enabling users to explore and manipulate the charts directly within the visualization. It can include zooming, data selection, and more, providing a richer and more dynamic user experience.\nThis meetup’s target audience is individuals interested in understanding the benefits of working with R‌ and people in the human resources field who are interested in the topic.\nFor this event, we conducted the invitation through Meetup and provided a Google Meet link. After the event, we will upload it to YouTube and communicate to the community through social media.\nWould you like to tell us about an interesting recent Meetup from the group?\nI recently presented at a group event titled Annual Income Tax with R to showcase the various problems one can address using R beyond data visualization or analysis. In Argentina, to carry out this development, one must consider the guidelines provided by the Federal Administration of Public Revenues (AFIP), which, at the national level, determines the parameters to be used for presentations; payroll software interprets these parameters. Those who do not have a payroll system can use the development done in R to carry out this presentation.\nIn Argentina, the frequent changes and calculation methods have made everything related to this tax quite complex. They impose this tax on salaries that are considered high-value. It is a tax withheld by the company, and due to inflation and various modifications, the analysis and handling of this tax end up being one of the most complex issues for employees in the country. I made this process easier in this meetup by using R.\n.png\nWhat trends do you currently see in R language and your industry? Are there any trends you see developing in the near future?\nTrends in R are about its growing popularity and its transformative impact. It allows more people to join and enhances its application to various problems. There is also ongoing work on clustering applied to Human Resources to understand how each group functions, their relationships, common characteristics, etc. In Argentina, due to the current economic situation, data analysis not only at the salary level but also at the soft skills level is an urgent necessity for companies aiming to use data for agile decision-making. Business data is vital for analyzing the rest of the decisions that need to be made by Human Resources and the entire company. To use data for agile decision-making, companies must consider salary levels, understand which soft skills are needed and what the context requires, and make decisions accordingly.\nA trend that will continue to develop in the future relates to Artificial Intelligence and how it complements everyday tasks or serves as a support tool.\nPlease share about a project you are working on or have worked on using the R language. What is the goal/reason, result, or anything interesting related to your industry?\nI have worked on several projects in R, starting with the basics related to data visualization of absenteeism, turnover, and salary analysis.\nSomething different that I worked on with R was creating the annual Income Tax presentation. The objective was to consolidate the yearly information of each employee covered by the regulations according to the parameters provided by the Federal Administration of Public Revenues. It required interpreting each requirement at the programming level. This file had to be submitted in TXT format, which meant working with rare extensions in Human Resources areas.\nAnother different project in R was creating accounting entries. It allows for systematizing a large amount of information and grouping it according to the accounts.\nI have also used R to prepare information presented to the Ministry of Labor, which required extensive cross-referencing. For example, it involved cross-referencing gender with absences, working hours, days, leaves, and paid leaves, among other variables. The complexity of this was the relationship between the data, where any incorrect data would ultimately lead to inconsistencies in the information.\nLastly, before applying R, the Budgeting process in our company involved transferring information across different Excel sheets, using pivot tables, and copying and pasting it into a summarized form. It took a significant amount of time, and whenever a variable needed to be changed, the entire process had to be redone, which implied errors due to the large amount of information transfer. Today, people work on this process dynamically in Excel and then process it in a script that consolidates all the information in minutes, sometimes less. It allows for the creation of multiple scenarios dynamically in a time of significant volatility and limited time. This process using R has achieved a substantial reduction in time, in addition to ensuring data consistency." + "text": "Join the R Consortium for an enlightening webinar on March 20th, 2024, at 4:00 PM ET, featuring Mine Cetinkaya-Rundel, Professor of the Practice of Statistical Science at Duke University. Discover the innovative Quarto tool to streamline the creation of reproducible, publication-ready manuscripts." }, { - "objectID": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html#how-do-i-join", - "href": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html#how-do-i-join", - "title": "R4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#key-highlights", + "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#key-highlights", + "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", + "section": "Key Highlights:", + "text": "Key Highlights:\n\nQuarto Manuscripts Introduction: Learn how to easily integrate reproducibility into your research with Quarto’s user-friendly features, creating comprehensive bundled outputs ready for journal submission.\nInteractive Demo: Witness a live demonstration of Quarto in action, showcasing how to enhance your current manuscript preparation process and address common challenges.\nExpert Guidance: Gain insights from Mine Cetinkaya-Rundel’s extensive experience in statistical science and reproducible research, offering valuable tips for improving your workflow." }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "", - "text": "Dive into the world of validation at the first R Validation Hub community meeting of the year! What defines a validated R package? Is it ensuring reproducibility across systems? Prioritizing bug-free and well-maintained packages? We want to hear YOUR take!" + "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#event-details", + "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#event-details", + "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", + "section": "Event Details:", + "text": "Event Details:\nWhen: March 20th, 2024, at 4:00 PM ET\nDon’t miss this opportunity to refine your manuscript preparation process with the latest advancements in reproducibility technology.\n\nRegister now!" }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-community-call-microsoft-teams-meeting", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-community-call-microsoft-teams-meeting", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "Join the community call! (Microsoft Teams meeting) ", - "text": "Join the community call! (Microsoft Teams meeting)" + "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html", + "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html", + "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "section": "", + "text": "The R Consortium is excited to announce the opening of our call for proposals for the 2024 Infrastructure Steering Committee (ISC) Grant Program on March 1st, 2024. This initiative is a cornerstone of our commitment to bolstering and enhancing the R Ecosystem. We fund projects contributing to the R community’s technical and social infrastructures.\nSubmit your proposal here!" }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#meeting-details", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#meeting-details", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "Meeting Details", - "text": "Meeting Details\n\nWhen: February 20, 12:00 EST\nWhere: Virtual meeting" + "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#enhancing-the-r-ecosystem-technical-and-social-infrastructures", + "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#enhancing-the-r-ecosystem-technical-and-social-infrastructures", + "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "section": "Enhancing the R Ecosystem: Technical and Social Infrastructures", + "text": "Enhancing the R Ecosystem: Technical and Social Infrastructures\nOur past funding endeavors have spanned a variety of projects, illustrating our dedication to comprehensive ecosystem support:\n\nTechnical Infrastructure: Examples include R-hub, a centralized tool for R package checking, enhancements in popular packages like mapview and sf, and ongoing infrastructural development for R on Windows and macOS.\nSocial Infrastructure: Initiatives such as SatRDays, which facilitates local R conferences, and projects for data-driven tracking of R Consortium activities." }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#why-attend", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#why-attend", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "Why Attend?", - "text": "Why Attend?\nThis is your chance to share your perspective, learn from diverse viewpoints, and help shape the future of validation in the R ecosystem. Whether you’re a developer, user, or enthusiast, your insights are valuable." + "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#focused-funding-areas", + "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#focused-funding-areas", + "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "section": "Focused Funding Areas", + "text": "Focused Funding Areas\nThe ISC is particularly interested in projects that align with technical or software development that aids social infrastructure. It’s important to note that conferences, training sessions, and user groups are supported through the RUGS program, not the ISC grants." }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#lets-discuss", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#lets-discuss", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "Let’s Discuss", - "text": "Let’s Discuss\nWhat does validation mean in the R world to you? Join us to debate, learn, and network. Mark your calendars and prepare to contribute to shaping the standards of R package validation." + "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#ideal-isc-projects", + "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#ideal-isc-projects", + "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "section": "Ideal ISC Projects", + "text": "Ideal ISC Projects\nWe look for proposals that:\n\nHave a broad impact on the R community.\nPossess a clear, focused scope. Larger projects should be broken down into manageable stages.\nRepresent low-to-medium risk and reward. High-risk, high-reward projects are generally not within our funding scope.\n\nProjects unlikely to receive funding are those that:\n\nOnly impact a small segment of the R community.\nSeek sponsorship for conferences, workshops, or meetups.\nAre highly exploratory." }, { - "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-call-here", - "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-call-here", - "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", - "section": "Join the call here!", - "text": "Join the call here!" + "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#important-dates", + "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#important-dates", + "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "section": "Important Dates", + "text": "Important Dates\n\nFirst Grant Cycle: Opens March 1, 2024, and closes April 1, 2024.\nSecond Grant Cycle: Opens September 1, 2024, and closes October 1, 2024.\n\nYou can learn more about submitting a proposal here.\nWe eagerly await your proposals and are excited to see how your ideas will propel the R community forward. Let’s build R together!" }, { - "objectID": "posts/r-addicts-paris-promoting-diversity-in-r/index.html", - "href": "posts/r-addicts-paris-promoting-diversity-in-r/index.html", - "title": "R Addicts Paris: Promoting Diversity in R", + "objectID": "posts/thank-you-joseph-rickert-a-legacy-of-leadership/index.html", + "href": "posts/thank-you-joseph-rickert-a-legacy-of-leadership/index.html", + "title": "Thank You, Joseph Rickert: A Legacy of Leadership and Innovation in the R Community", "section": "", - "text": "Vincent Guyader, organizer of the R Addicts Paris and president of ThinkR, recently updated the R Consortium on the group’s activities. Last year, Vincent discussed the application of R in developing solutions for industrial problems. He emphasized the importance of helping people become fluent in R and leveraging the language to add value to their work. ThinkR is dedicated to enhancing R proficiency in various industries. The R Addicts Paris, one of France’s oldest and largest R user groups with 1,800 members, continues to foster a strong R community under Vincent’s leadership.\nPlease share your background and involvement with the RUGS group.\nMy name is Vincent, and I have been using R since my student days. During my studies, I took on freelance R projects for various companies. Currently, I head a company called ThinkR, where we have a team of over 10 experts specializing in everything related to R. Our services include training, consulting, developing Shiny applications, creating R packages, and more. We also collaborate with Posit and handle hardware installations for clients, primarily in France but also in Switzerland, Belgium, and other parts of Europe.\nSince 2018, I have been managing the R user group in Paris, known as the R Addicts Paris. It’s one of the oldest and possibly the largest R user groups, with 1,800 members. I aimed to organize meetups every three months, but the next one has been delayed due to internal organizational issues. I genuinely enjoy helping people become fluent in R and use the language to add value to their work.\nWhat challenges do you face in organizing the R Addict Paris group and how do you overcome those challenges?\nOne of the main challenges is that our users are not professional programmers or developers; they are specialists in fields like biology and finance. They have to shift their mindset to use programming languages. My daily job involves helping these individuals embrace software development. Coming from a genetics and biochemistry background, I understand how challenging this can be for non-developers. However, I love doing this, and I have a dedicated, competent team to assist.\nBased on your work with ThinkR, which industries in France do you see using R?\nWe have clients in various fields across France, including finance, retail, and research. The health sector is particularly prominent. For instance, a company that used SAS a few years ago now uses R & Python. About half of our clients currently use Python. While we provide Python installation on hardware, we don’t offer Python training yet.\nWe are committed to being the sole organization in France that can certify R users and developers. The French government has authorized us to issue an official certification akin to a diploma. Our goal is to elevate R proficiency across various fields in France. Our clients include businesses and individuals, with many investing their resources to learn proper software and programming skills.\nDo you host online or in-person events?\nI chose not to host online events. It’s a very opinionated choice because most meetups switched to online formats during the pandemic. At ThinkR, we are a fully remote company, and I spend my day on Zoom. While remote training is effective, I’ve found that in-person events work better for our user group.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people who are unable to attend physical events in the future?\nOne of the main challenges we face as a group is finding female speakers. I try to avoid having only male speakers, but I only get female speakers every fifth or sixth event, which is not enough. I encourage other R user group organizers to recognize our power to give a voice to different kinds of people. I push myself to include more female speakers. Sometimes, I encounter highly qualified women who hesitate to speak, while less experienced men are more willing. It’s challenging, but I strive to maintain a balanced representation.\nI consciously avoid engaging with speakers who lack substance, ensuring I have time to encourage qualified women to share their knowledge. Despite my efforts, female representation remains below 20%. A few years ago, my colleague Diane and I tried to connect with the R-Ladies Paris group. Many men are actively engaged there, and I wonder why that is.\nThere are many skilled women in the R community, which includes biologists and geneticists. There’s no excuse for the lack of female representation. We must remember our influence and endorse individuals who truly represent our values.\nWhat are some trending topics in R in your R User Group?\nI’ve noticed a decline in interest in statistics over the past two to five years. During meetups, we rarely discuss statistics. The machine learning and AI fields aren’t well-represented in R, possibly because most people in these fields use Python. It could also be due to regional differences or my network.\nYou had a Meetup “Raddicts x RTE – {webr} – Shinyproxy and return of the Reconteres 2024” on 19th June, can you share more on the topic covered? Why this topic?\nFor this event, we had two male speakers. Colin Fay discussed {webr}, a new JavaScript capability for launching user insights in the browser. This is powerful for deploying Shiny applications. Valentin Cadoret talked about new Shinyproxy functionalities, and tools that enhance the deployment of Shiny applications. So we focused heavily on Shiny once again." + "text": "As we announce the end of Joseph (Joe) Rickert’s tenure as the Executive Director of the R Consortium, we reflect on his remarkable contributions that have significantly contributed to the R community. Joe’s leadership has been instrumental in fostering growth, innovation, and collaboration within the R ecosystem.\nFounding the R Consortium\nJoe has been with the R Consortium since its inception in 2014. He was initially appointed to be Microsoft’s representative to the Infrastructure Steering Committee (ISC) and was soon tasked with creating the R User Groups (RUGS) grants program. Joe also pioneered the formation of ISC working groups to foster industry-wide collaborative projects. In 2016, Joe was appointed to be RStudio’s representative to the Board of Directors. In 2018, he took on the role of Secretary, and by 2019, he was elected Chair of the Board. In 2023, Joe took on the role of Executive Director. Under his guidance, the R Consortium has grown into an inclusive organization supporting the R programming language and its community. Our new executive director, Terry Christiani, was affirmed by the board of directors in our August 2024 board meeting after a selection committee interviewed candidates and made recommendations.\nAdvancing User Groups\nOne of Joe’s notable achievements is his unwavering support for R user groups worldwide. He recognized the importance of grassroots movements in spreading the use of R and provided essential resources and funding to these groups. He was instrumental in funding the R-Ladies as a top-level ISC project that operates worldwide to provide safe places for women to come together and learn from each other in an otherwise male-dominated space. Joe was also directly involved with the Bay Area useR Group (BARUG), organizing events, speaking, or contributing to discussions around the R programming language, especially in the context of data science and statistical computing. This support has enabled countless R enthusiasts to connect, share knowledge, and collaborate on projects, thereby strengthening the global R community.\nIndustry Collaboration and Working Groups\nJoe actively reached out to industry leaders to create unique working groups aimed at solving industry-wide problems. These collaborations have led to the development of working groups focused on R programming solutions that benefit not only the community but also industries that rely on data science and statistical computing.\nA Legacy of Innovation\nThroughout his tenure, Joe has been a driving force behind numerous initiatives that have propelled the R community forward. His efforts have ensured that the R Consortium remains a dynamic and inclusive organization, fostering a spirit of collaboration and innovation. His leadership has left an indelible mark on the R community, and his legacy will continue to inspire future generations of R users and developers.\nAs we welcome new leadership, we extend our heartfelt gratitude to Joe Rickert for his dedication, vision, and tireless efforts in advancing the R community. Thank you, Joe, for your invaluable contributions and for paving the way for a brighter future for the R ecosystem." }, { - "objectID": "posts/r-addicts-paris-promoting-diversity-in-r/index.html#how-do-i-join", - "href": "posts/r-addicts-paris-promoting-diversity-in-r/index.html#how-do-i-join", - "title": "R Addicts Paris: Promoting Diversity in R", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/announcing-health-technology-assessment-HTA-working-group/index.html", + "href": "posts/announcing-health-technology-assessment-HTA-working-group/index.html", + "title": "Announcing the Health Technology Assessment (HTA) Working Group", + "section": "", + "text": "The R Consortium is pleased to announce a new Working Group (WG) focused on Health Technology Assessment (HTA). The HTA WG has a mission of promoting the use of R in all aspects of HTA analytics, including both clinical assessment and economic evaluation. It aims to build on the success of other R Consortium working groups in bringing together and promoting dialogue between the broadest range of stakeholders from the HTA ecosystem (industry, HTA bodies, academics and others) to identify needs and address challenges through practical tools and pilot exercises. Health Technology Assessment (HTA) helps decision-makers determine which medical technologies and treatments are effective and worth paying for. It can help ensure that the right treatments reach the right patients at the right time by assessing clinical evidence and economic evaluations to inform policy-making about reimbursement and market access.\nRecent policy changes, such as the EU HTA Regulation, require pharmaceutical companies to face stricter standards and shorter deadlines for submitting evidence. At the same time, HTA authorities must review an increasing number of complex analyses under the pressure for timely evidence-based decisions. Lastly, there is pressure on academia to provide easy-to-use HTA software and tools.\nInitially, the WG will focus on the following objectives.\n\nFoster Collaboration and Knowledge Sharing:\n\nUnderstanding the needs of all stakeholders for HTA analytics, and where the use of R may best fit.\nPromote the common goal of delivering HTA analytics work that meets those needs and efficiently utilizes R.\nBecome a central hub for connecting existing and new R initiatives in the HTA space, ensuring efficient and unified efforts.\n\nDevelop and Document Best Practices:\n\nDevelop and disseminate best practices for using R in HTA analytics work for clinical and economic evaluation.\nPromote transparency and reproducibility in HTA analytics work.\n\nExplore Pilot Studies with HTA authorities\n\nExplore pilot studies to test and refine open source R-based tools and frameworks for clinical and economic evaluation.\nPursue collaborative efforts with HTA authorities to validate these tools, demonstrating their value in real-world HTA scenarios.\n\n\nIf you think any of this is exciting and would like to become involved, please leave your name and email in issue number 1 at the HTA GitHub repository." }, { - "objectID": "posts/aligning-belief-and-profession-using-r-in-protecting-the-penobscot-nation-traditional-lifeways-r-consortium/index.html", - "href": "posts/aligning-belief-and-profession-using-r-in-protecting-the-penobscot-nation-traditional-lifeways-r-consortium/index.html", - "title": "Aligning Beliefs and Profession: Using R in Protecting the Penobscot Nation’s Traditional Lifeways", + "objectID": "posts/one-more-step-forward-the-r-consortium-submission-working-group-presentation-to-swissmedic-on-regulator-submission-using-r-and-shiny/index.html", + "href": "posts/one-more-step-forward-the-r-consortium-submission-working-group-presentation-to-swissmedic-on-regulator-submission-using-r-and-shiny/index.html", + "title": "One More Step Forward: The R Consortium Submission Working Group’s Presentation to Swissmedic on Regulatory Submission using R and Shiny", "section": "", - "text": "Jan Paul, Water Quality Lab Coordinator at Penobscot Nation, sampling in field\n\n\nIn a recent interview by the R Consortium, Angie Reed, Water Resources Planner for the Penobscot Indian Nation, shared her experience learning and using R in river conservation and helping preserve a whole way of life. Educated in New Hampshire and Colorado, Angie began her career with the Houlton Band of Maliseet Indians, later joining the Penobscot Indian Nation. Her discovery of R transformed her approach to environmental statistics, leading to the development of an interactive R Shiny application for community engagement.\npαnawάhpskewi (Penobscot people) derive their name from the pαnawάhpskewtəkʷ (Penobscot River), and their view of the Penobscot River as a relative guides all of the Water Resources Program’s efforts. This perspective is also reflected in the Penobscot Water Song, which thanks the water and expresses love and respect. Angie has been honored to:\n\nwork for the Water Resources Program,\ncontribute to the Tribal Exchange Network Group,\nengage young students in environmental stewardship and R coding, blending traditional views with modern technology for effective environmental protection and community involvement, and\nwork with Posit to develop the animated video about Penobscot Nation and show it at the opening of posit:conf 2024\n\nPlease tell us about your background and how you came to use R as part of your work on the Penobscot Indian Nation.\nI grew up in New Hampshire and completed my Bachelor of Science at the University of New Hampshire, followed by a Master of Science at Colorado State University. After spending some time out west, I returned to the Northeast for work. I began by joining the Houlton Band of Maliseet Indians in Houlton, Maine, right after finishing my graduate studies in 1998. Then, in 2004, I started working with the Penobscot Indian Nation. Currently, I work for both tribes, full-time with Penobscot and part-time with Maliseet.\nMy first encounter with R was during an environmental statistics class taught by a former USGS employee, Dennis Helsel during a class he taught for his business Practical Stats. He introduced us to a package in R called R Commander. Initially, I only used it for statistics, but soon, I realized there was much more to R. I began teaching myself how to use ggplot for graphing. I spent months searching and learning, often frustrated, but it paid off as I started creating more sophisticated graphs for our reports.\nWe often collaborate with staff from the Environmental Protection Agency (EPA) in Region One (New England, including Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont and 10 Tribal Nations). One of their staff, Valerie Bataille, introduced us to R Carpentries classes. She organized a free class for tribal staff in our region. Taking that class was enlightening; I realized there was so much more I could have learned earlier, making my journey easier. This experience was foundational for me, marking the transition from seeing R as an environmental statistics tool to recognizing its broader applications. It’s a bit cliché, but this journey typifies how many people discover and learn new skills in this field.\nThe Penobscot Nation views the Penobscot River as a relative or family. How does that make water management for the Penobscot River different from other water resource management?\nIf you watch The River is Our Relative, the video delves deeper into seeing the river from a relative, beautiful, and challenging perspective. This view fundamentally shifts how I perceive my work, imbuing it with a deeper meaning that transcends typical Western scientific approaches to river conservation. It’s a constant reminder that my job aligns with everything I believe in, reinforcing that there’s a profound reason behind my feelings.\nWorking with the Penobscot Nation and other tribal nations to protect their waters and ways of life is an honor and has revealed the challenges of conveying the differences in perspective to others. Often, attempts to bridge the gap get lost in translation. Many see their work as just a job, but for the Penobscot people, it’s an integral part of their identity. It’s not merely about accomplishing tasks; it’s about their entire way of life. The river provides sustenance, acts as a transportation route, and is a living relative to whom they have a responsibility.\nHow does using open source software allow better sharing of results with Penobscot Nation citizens?\nMy co-worker, Jan Paul, and I had the pleasure of attending and presentingat posit::conf 2023 and working with Posit staff to create an animated video that describes what we do and how opensource and Posit tools help us do it. It was so heart-warming to watch the video shown to all attendees at the start of conf, and was a great introduction to my shameless ask for help during my presentation and through a table where I offered a volunteer sign-up sheet/form, I was humbled by the number of generous offers and am already receiving some assistance on a project I’ve been eager to accomplish. Jasmine Kindness, One World Analytics, is helping me recreate a Tableau viz I made years ago as an interactive, map-based R Shiny tool.\n\nI find that people connect more with maps, especially when it comes to visualizing data that is geographically referenced. For instance, if there’s an issue in the water, people can see exactly where it is on the map. This is particularly relevant as people in this area are very familiar with the Penobscot River watershed. My aim is to create tools that are not only interactive but also intuitive, allowing users to zoom into familiar areas and understand what’s happening there.\nThis experience has really highlighted the value of the open source community. It’s not just about the tools; it’s also about the people and the generosity within this community. The Posit conference was a great reminder of this, andthe experience of working with someone so helpful and skilled has truly reinforced how amazing and generous the open source community is.\nHow has your use of R helped to achieve more stringent protections for the Penobscot River?\nBefore we started using open source tools, my team and I had been diligently working to centralize our data management system, which significantly improved our efficiency. A major shift occurred when we began using R and RStudio (currently Posit) to extract data from this system to create summaries. This has been particularly useful in a biennial process where the State of Maine requests data and proposals for upgrading water quality classifications.\nIn Maine, water bodies are classified into four major categories: AA, A, B, and C. If new data suggests that a water body, currently classified as a lower grade, could qualify for a higher classification, we can submit a proposal for this upgrade. In the past we have facilitated upgrades for hundreds of miles of streams, however it took much longer to compile the data. For the first time in 2018 we used R and RStudio to prepare a proposal to the Maine Department of Environmental Protection (DEP) to upgrade the last segment of the Penobscot River from C to B. Using open source tools, we were able to quickly summarize data and compile data into a format that could be used for this proposal, a task that previously took a significantly longer time. DEP accepted our proposal because our data clearly supported the upgrade. In 2019, the proposal was passed and we anticipate this process continuing to be easier in the future.\nYou are part of a larger network of tribal environmental professionals, working together to learn R and share data and insights. Can you share details about how that works?\n\n\n\nJan Paul, Water Quality Lab Coordinator at Penobscot Nation, sampling in field\n\n\nI’m involved in the Tribal Exchange Network Group (TXG), which is a national group of tribal environmental professionals like myself and is funded by a cooperative agreement with the Office of Information Management (OIM) at the Environmental Protection Agency (EPA). We work in various fields, such as air, water, and fisheries, focusing on environmental protection. Our goal is to ensure that tribes are well-represented in EPA’s Exchange Network, and we also assist tribes individually with managing their data.\nSince attending a Carpentries class, I’ve been helping TXG organize and host many of them. We’ve held one every year since 2019, and we’re now moving towards more advanced topics. In addition to trainings, TXG provides a variety of activities and support, including small group discussions, 1-on-1 assistance and conferences. Although COVID-19 disrupted our schedule we are planning our next conferencefor this year.\nOur smaller, more conversational monthly data drop-in sessions always include the opportunity to have a breakout room to work on R. People can come with their R-related questions, or the host might prepare a demo.\nOur 1-on-1 tribal assistance hours allows Tribes tosign up for help with issues related to their specific data. I work with individuals on R code for various tasks, such as managing temperature sensor data or generating annual assessment reports in R Markdown format. This personalized assistance has significantly improved skill building and confidence among participants and are particularly effective as they use real data and often result in a tangible product, like a table or graph, which is exciting for participants. We’ve also seen great benefits, especially in terms of staff turnover. When staff members leave, the program still has well-documented code, making it easier for their successors to pick up where they left off. These one-on-one sessions.\nAdditionally, I’ve been involved in forming a Pacific Northwest Tribal coding group, which still doesn’t have an official name as it is only a few months old. It began from discussions with staff from the Northwest Indian Fisheries Commission (NWIFC) and staff from member Tribes. And I am thrilled to say we’ve already attracted many new members from staff of the Columbia River Inter-Tribal Fish Commission (CRITFC). This group is a direct offshoot of the TXG efforts with Marissa Pauling of NWIFC facilitating, and we’re excited about the learning opportunities it presents.\nOur work, including the tribal assistance hours, is funded through a grant that reimburses the Penobscot Nation for the time I spend on these activities. As we move forward with the coding group, planning to invite speakers and organize events, it’s clear there’s much to share with this audience, possibly in future blogs like this one. This work is all part of our broader effort to support tribes in their environmental data management endeavors. If anyone would like to offer their time toward these kinds of assistance, they can use the TXG google form to sign up.\nHow do you engage with young people?\nI am deeply committed to engaging the younger generation, especially the students at Penobscot Nation’s Indian Island school (pre-K through 8th grade). In our Water Resources Program at Penobscot Nation, we actively involve these students in our river conservation efforts. We see our role as not just their employees but as protectors of the river for their future.\n\n\n\nSampling for Bacteria\n\n\nOur approach includes hands-on activities like taking students to the river for bacteria monitoring. They participate in collecting samples and processing them in our lab, gaining practical experience in environmental monitoring. This hands-on learning is now being enhanced with the development of the R Shiny app I’m working on with Jasmine, to make data interpretation more interactive and engaging for the students.\nRecognizing their budding interest in technology, I’m also exploring the possibility of starting a mini R coding group at the school. With students already exposed to basic coding through MIT’s Scratch, advancing to R seems a promising and exciting step.\nBeyond the Penobscot Nation school, we’re extending our reach to local high schools like Orono Middle School. We recently involved eighth graders, including two Penobscot Nation citizens, in our bacteria monitoring project. This collaboration has motivated me to consider establishing an R coding group in these high schools, allowing our students continuous access to these learning opportunities.\n\n\n\nProcessing bacteria sample\n\n\nMy vision is to create a learning environment in local high schools where students can delve deeper into data analysis and coding. This initiative aims to extend our impact, ensuring students have continuous access to educational opportunities that merge environmental knowledge with tech skills and an appreciation of Penobscot people, culture and the work being done in our program.\nOver the years, witnessing the growth of students who participated in our programs has been immensely gratifying. . A particularly inspiring example is a young Penobscot woman, Shantel Neptune, who did an internship with us through the Wabanaki Youth in Science (WaYS) Program a few years back , then a data internship through TXG and is now a full-time employee in the Water Resources Program. Shantel is also now helping to teach another young Penobscot woman, Maddie Huerth, about data collection, management, analysis and visualization while she is our temporary employee. We’re planning sessions this winter to further enhance their R coding skills, a critical aspect of their professional development.\nIt’s essential to me that these women, along with others, receive comprehensive training. Our program’s success hinges on it being led by individuals who are not only skilled but who also embody Penobscot Nation’s values and traditions. Empowering young Penobscot citizens to lead these initiatives is not just a goal but a necessity. Their growth and development are vital to the continuity and integrity of our work, and I am committed to nurturing their skills and confidence. This endeavor is more than just education; it’s about preserving identity and ensuring our environmental efforts resonate with the Penobscot spirit and needs." + "text": "This post was authored by Gregory Chen, Biostatistics and Research Decision Sciences (BARDS), MSD, Switzerland, and Ning Leng, Product Development Data Sciences (PDD), F. Hoffmann-La Roche, USA\n\nOn January 30, 2024, the R Consortium Submission Working Group made a presentation to Swissmedic in Bern, Switzerland, with 10 attendees in person and 50 online. It started with a motivation as to why to consider using open source and specifically R for regulatory submissions. The group then proceeded to show cases of the pilot 1 and 2 submission to FDA.\nThe conclusion was an insightful discussion for about 20 minutes with the participants on the lessons learned, key factors to sort in line for broader adoption of R and Shiny for regulatory submissions, and what would be most added value for a regulatory shiny app, namely\n\nHow to deploy the submitted R package and Shiny App to guarantee the clinical outcomes can be smoothly reproduced on the regulatory side\nWhat would be the ultimate purpose of a regulatory shiny app, and what are value-added features? Should the app only focus on offering interactivities to facilitate the review of tables, figures, and listings in CSR, or should it also include designed features to enable exploratory, descriptive analysis (e.g., for subgroups) to certain degrees, which may greatly shorten back-and-forth inquiry between regulator and drug developer?\nValidation and version traceability of dependent open source R packages used in the submission package\nHow to leverage existing and emerging cross-industrial initiatives (e.g. R consortium) in the open source space to support and ease the potential technical issue during the adoption of R for submission\n\nAccompanying this post, the full presentation slide deck is made publicly available here, inviting further exploration and discussion.\nThe R Consortium’s presentation at Swissmedic represents a hopeful step toward more interactive, efficient, and transparent regulatory submissions. As the conversation between the R Consortium and regulatory bodies continues, our future collection of pilot projects hopefully will offer richer examples and templates to our growing R community within the pharmaceutical sector, spanning both regulatory and drug developer sides.\nTo find out more about the R Consortium Submission Working Group, please see: https://rconsortium.github.io/submissions-wg/" }, { - "objectID": "posts/the-crucial-role-of-release-control-in-r-for-healthcare-organizations/index.html", - "href": "posts/the-crucial-role-of-release-control-in-r-for-healthcare-organizations/index.html", - "title": "The Crucial Role of Release Control in R for Healthcare Organizations", + "objectID": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html", + "href": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html", + "title": "Cakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group", "section": "", - "text": "Guest blog contributed by Ning Leng, People and Product Leader, Roche-Genentech; Eric Nantz, Director, Eli Lilly and Company; Ben Straub, Principal Programmer, GSK; Sam Parmar, Statistical Data Scientist, Pfizer\nSupporting the science of drug development requires computational tools with careful implementations of core statistical functions and data structures. The R programming language, a general purpose language developed by statisticians that grows dynamically through the contributions of a worldwide community of developers, is a common choice for serious statistical work. However, managing new versions of the core R language and the hundreds of specialized libraries (called packages in R) necessary to support multiple development groups in a way that ensures the consistency, reproducibility, and reliability of results poses many practical challenges\nThe FDA, for example, requires that the software and tools supporting a clinical trial submission are capable of producing reproducible results for an extended period of time. This means submitting code based on a version of R that is sufficiently tested and stable yet new enough to support the critical R packages over the required FDA time horizon.\nSo, how is the R environment release managed across different healthcare organizations? We interviewed individuals from different pharma companies to learn their internal approaches to keep their R environment up-to-date and secure.\n\nRoche’s Scientific Computing Environment is container based, with clinical reporting done from managed qualified images being released twice per year – roughly timed to capture the last update to an R major version (April release) and a 6 month later update (September release). For each image, R packages undergo a mostly automated risk assessment to document package quality. Automated indicators of package quality include test coverage, thoroughness of documentation, test coverage of exported objects (using covtracer), and may be supplemented with package adoption measured using download counts, author reputation or other peripheral knowledge of the package’s history. Prior to internal publication, a representative sample of reverse dependencies are re-evaluated to safeguard against breaking changes. If the package meets our quality criteria it is published to a continuously updated repository of validated packages corresponding to the image’s R minor version (e.g. x.x). This allows flexibility for teams to roll forward to newer releases of packages within a managed release by moving their renv snapshot to a later date, easing the transition between bi-annual image releases. A generalized version of Roche’s automated process has been open sourced as ’theValidator’, and more details on the Roche process was shared within the R Validation case studies series.\nEli Lilly currently updates its qualified R environment only after a new major release of R is available and the corresponding release of Bioconductor (utilizing that version of R) is also available. In a new release, all packages currently installed from the CRAN and Bioconductor repositories are refreshed to their latest versions at the time of the release. Once the new R version is deployed, all packages are frozen for that particular release to ensure stability and reproducibility. Lilly maintains multiple R versions for backward compatibility. Only packages available on CRAN or Bioconductor are permitted for installation in the central package library. Lilly uses a hybrid approach of automation and risk-based assessment when a new package is requested for installation. In the event that a new version of a package is necessary for a project (such as a new Shiny application), the users are encouraged to leverage the renv package created by Posit to create a project-based environment which will not impact the central package library. As technology evolves and the R language becomes more prominent in clinical data analysis, Lilly continues to assess the current and future possibilities of a robust clinical computing environment primed for innovation while adhering to the foundational principles of reproducibility and transparency.\nGSK releases “frozen R environments” for clinical reporting work on a 6-12 month cycle. The choice of R version is the latest stable release with at least one patch release of R, e.g. 4.3.1 rather than 4.3.0. As R itself is stable with decades of use, we prefer to focus on package assessment for building of our “frozen R environments.” Packages for this environment can be from external sources (CRAN, Bioconductor) or internally built at GSK, regardless of origin we assess the same way. We pay close attention to author qualification and institutional backing, types and breadth of testing, documentation and examples, and the practice of software development life cycle practices. Once a package is approved in this process it will be included in the frozen environment. Packages change over time, if substantial changes are implemented in the packages, then we re-assess with a focus on those changes for allowing up-versioning of the package in the frozen environment. These frozen environments ensure that clinical reporting can be easily reproduced if needed as all packages versions and the version of R used during the analysis are contained in the frozen environment.\nPfizer releases one new R version every year. We typically target R-x.y.1 releases to pick up patches – so we might consider this a “stable” release. The process of testing, documenting, and deploying R into validated containers is performed every 6 months, with a new release of R once per year, e.g. R-4.3.1, and an update to package set and package versions 6 months later (for the same R version). We take a snapshot date of CRAN to form the basis of our package set for the container build. We try to balance competing priorities of getting latest versions of packages and newest package releases, while maintaining a snapshot and version-controlled release to ensure reproducibility and stability.\n\nHere is what we have: four companies and four somewhat complex bespoke solutions. It seems likely that if we interviewed a hundred representatives from a hundred different companies we would get at least a hundred different solutions. It is also not difficult to imagine that multiple protocols for managing R and package versions imposed a fairly complex project management solution on the FDA as it simultaneously deals with submissions from multiple sponsors.\nIn the R Consortium’s R Submissions Work Group meeting we have been discussing whether there might be a simple solution for at least dealing with the R versioning problem that might serve as a de facto standard for the industry. One suggestion that has gained some traction is that sponsors use the previous minor and latest patched R version for a submission. For example, if R version 4.4.0 is currently available then it is suggested that a sponsor uses the latest patch version (4.3.z). If R version 4.5.0 becomes available, then it is suggested that a sponsor uses the latest patch version (4.4.z). This ensures that the minor version is stable and most likely available to all stakeholders. Of course, if a version change eliminates a security problem, that might be preferred. (Note that R versions are organized R x.y.z where, x is the major version, y is the minor version, and z is the patch version.)\nWe would love to hear what you think. Please, go to Issue number 117 on the GitHub repository of our working group and leave a comment." + "text": "Rasmus Bååth, the organizer of the CopenhagenR UseR Group, recently spoke to the R Consortium about his experience in organizing the group. After joining the Copenhagen R User Group in 2013, he took the lead in reviving the group in 2023 after a period of inactivity. Under his guidance, the group now focuses on industry-related topics, personal projects, and emerging tools like Quarto. Rasmus is dedicated to fostering a vibrant local R community through in-person meetups that encourage learning and collaboration.\nThe CopenhagenR UseR Group is hosting an exciting “Two Tools for Report Generation in R” event on October 3, 2024. The event will feature two presentations on using Sweave and Quarto for report generation, followed by discussions and networking at PROSA, København, Denmark.\nPlease share your background and involvement with the RUGS group.\nI currently work as a Data Science Manager at Normative.io. I’ve used R on and off for about 15 or 16 years. It all started when I was doing my bachelor’s in academia and needed to plot a histogram. At that time, plotting a histogram in Excel wasn’t easy, so my supervisor suggested trying out R. I gave it a shot and got hooked. After that, I pursued a PhD in cognitive science, where I used R extensively for statistical analysis.\nI used R for a lot of graphing during my academic years. After academia, I became a data scientist in the industry, and R was my preferred tool. I work with R and Python, depending on the job’s requirements. In 2013, there were no R meetups in the south of Sweden where I live. I found out about an R meetup in Copenhagen and decided to attend. There, I met Kenneth Rose, the organizer, who was full of energy and charisma. It was a fun group, so I started attending regularly despite the commute from Sweden to Copenhagen. Kenneth was very active and enthusiastic in running the meetup group.\nAfter a couple of years, the group’s activity declined. A new organizer revived the group, but COVID hit, ending the meetups. The group had been around for ten years by 2023, and I felt it was a shame to let it die. I decided to restart it, and now we have a small but active group. We enjoy discussing industry-related topics and personal projects.\nCan you share what the local R community is like?\nIt is the Copenhagen meetup group located in Denmark. However, I can speak for Denmark and Sweden since I live in Sweden. R is widely used in academia and is considered the language of choice for statistics. Python is more prevalent in the industry due to the large number of programmers who are familiar with the language. In Denmark, the pharmaceutical industry is significant. R is still widely used there due to its close ties to academia and the specific requirements for reporting, statistics, and visualization, in which R excels.\nDo you guys host online or in-person events?\nDuring the COVID-19 pandemic, we tried some online events, but creating a sense of community online with so much content is challenging. I believe online events are great, and people should consider them. However, we also recognize the need for in-person events. For those unable to attend, there is plenty of valuable content online. We don’t have the setup to record events, but we would consider doing so if feasible.\nYou have a Meetup titled “Two tools for report generation in R.” Can you share more on the topic covered? Why this topic?\nOur next meetup will focus on automatic reporting in R. We’ll have two speakers: Dmytro Perepolkin and an anonymous speaker. The anonymous speaker will present on Sweave, an older tool used to generate reports in R, while Dmytro will present on Quarto, a more recent and popular tool for combining R code and text. This meetup will depart from the usual topics, focusing on automatic reporting rather than visualization.\nI’m looking forward to our upcoming event. It will be a history lesson and a great opportunity to learn about a useful minimalistic tool (Sweave). I’m also excited about Quarto and the potential for new developments. We could have a Quarto meetup every year to stay updated with the latest advancements. The meetup will feature different presentations, including introductions to new tools and discussions about projects and code. It will be a great way to learn and connect with others in the field.\nWhat are some of the popular R-related topics in the group?\nThe topics we typically cover are where R is at its strongest. We often discuss personal projects, and although I wonder if they receive a great response, I love them. Additionally, we frequently explore new tools and libraries, particularly those related to dashboarding, Shiny, and visualization. Presentations are highly technical, and I’ve noticed that our audience may not be accustomed to text-heavy or math-intensive presentations. Therefore, topics such as statistics and statistics packages might not receive as much attention despite my interest in them. Surprisingly, machine learning is not a common focus at our meetups, as most speakers are more inclined towards visualization, reporting, and statistics rather than machine learning.\nDo you recommend any techniques for planning for or during the event? (GitHub, Zoom, other.) Can these techniques be used to make your group more inclusive to people who cannot attend physical events in the future?\nThere are three key components needed to get started with organizing an event. First, you need people who are interested in attending your event. It can be challenging if you’re in a small town or a location where it’s difficult to attract attendees. Second, you need to secure speakers who are willing to participate. Lastly, finding a suitable venue is crucial. Having a reliable and cost-free location for your event is essential. We were fortunate to secure a free venue through a union for IT workers in Copenhagen, which aligns with our goal of offering free courses without being tied to a specific company.\nFinding speakers can be challenging, but constantly contacting and asking for volunteers is the best approach. To make it easier for potential speakers, consider organizing events where multiple speakers can do shorter presentations, which may be less intimidating than a full-hour presentation. However, attracting speakers and attendees remains the most difficult aspect of organizing events. Nevertheless, securing a dependable venue is a great starting point.\nAnd then there are some small things. Make sure to make nice announcements. They need a nice picture. They need friendly text so that people feel welcome. That’s the minimal thing. And the other thing is, if it’s allowed in the meetup space, bring some cakes or cookies and have some snacks. If people know there will be a little bit of snacks, they’re more likely to show up. So it’s a small thing, but I think that helps. This meetup is in Copenhagen, and I’m from Sweden. However, Denmark and Copenhagen have a special relationship with beer. I distinctly remember my first Copenhagen meetup when Kenneth Rose was the organizer. Back then, he brought a big case of beer cans to each meetup, and everyone was having a nice time. I don’t say you need a beer at your meetup, but bringing drinks and snacks is always nice." }, { - "objectID": "posts/earl-early-bird-tickets-are-now-available/index.html", - "href": "posts/earl-early-bird-tickets-are-now-available/index.html", - "title": "EARL Early Bird Tickets Are Now Available!", - "section": "", - "text": "Contributed by Abbie Brookes, Senior Data Analyst at Datacove\n\nDatacove is pleased to announce the availability of tickets for the upcoming EARL (Enterprise Applications of the R Language) conference.\nThe EARL conference is a cross-sector event that will be held at the Grand Hotel in Brighton. This venue promises to provide attendees with a blend of Victorian elegance and modern conference facilities over three days, from the 3rd to the 5th of September 2024. The conference schedule includes high-quality workshops on the first day (3rd September) and two days of presentations and talks (4th – 5th September). An evening networking event is planned for the 4th of September at the British Airways i360 venue, offering attendees the opportunity to connect with peers and speakers in a relaxed setting.\nWe are offering tickets at a reduced early bird rate. Additionally, we provide discounts for government employees, NHS staff, charity workers, academics, and those making bulk purchases. For more detailed information on ticket pricing and discounts, contact Abbie Brookes at abbie.brookes@datacove.co.uk.\nThe EARL conference draws attendees from across the globe and from a variety of sectors. Previous participants have included notable organizations such as The Dogs Trust, BBC, Microsoft, Swiss RE, Posit, Sainsburys, and Bupa.\nThis year’s keynote speakers include:\n\nProfessor Andy Field, known for his contributions to statistics education\n\nChristel Swift, a senior data scientist at the BBC\n\nHadley Wickham, a key figure in the R community and author of the Tidyverse\nIn addition to the main conference, a selection of pre-conference workshops will be available, offering in-depth training opportunities. For more information on the conference venue, schedule, and registration, please visitour website. We invite you to join us for what promises to be an informative and engaging event for the R and Python communities" + "objectID": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html#how-do-i-join", + "href": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html#how-do-i-join", + "title": "Cakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn More!" }, { - "objectID": "posts/elevate-your-r-community-with-the-2024-rugs-grant-program/index.html", - "href": "posts/elevate-your-r-community-with-the-2024-rugs-grant-program/index.html", - "title": "Elevate Your R Community with the 2024 RUGS Grant Program", + "objectID": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html", + "href": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html", + "title": "Unlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research", "section": "", - "text": "The R Consortium is rolling out its 2024 R User Groups (RUGS) Grant Program, and it’s an opportunity you don’t want to miss. The program, which aims to foster vibrant R communities worldwide, is in full swing, and we are eagerly awaiting your application!\n\nApply here!\n\n\nWhy Apply and… For What?\nUser Group Grants: Boost engagement and initiate user-focused activities.\nConference Grants: Support for R-related events, either hosting or attending.\nSpecial Projects Grants: Kickstart innovative projects with the potential to impact the R community.\nWith 74 active groups and a thriving community of over 67,000 members, the RUGS network is a hub of innovation and knowledge sharing. Your participation could be the next milestone in this growth journey.\nExamples of some recent R Consortium sponsored RUGS activities:\n\nThe Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics\nR-Ladies Goiânia: Promoting Diversity and Inclusion in Local R Community\n\n\n\nKey Information\nApplication Deadline: September 30th, 2024. Don’t delay!\nEligibility: Open to initiatives aimed at community building, not software development (for that, see ISC Grant Program).\nBe part of shaping the future of R. Visit here for more details and to apply. Your contribution matters to the global R narrative. Apply now, and let’s grow together!\n\nFor details and to apply, visit here." + "text": "The R Consortium recently interviewed Kristina Riemer, director of the CCT Data Science Team at the University of Arizona, and Eric Scott, Scientific Programmer and Educator in the CCT Data Science Team, the developers behind the volcalc package, to discuss the motivation and development of this innovative tool designed to automate the calculation of chemical compound volatilities. volcalc streamlines the process by allowing users to input a compound and quickly receive its volatility information, eliminating the need for time-consuming manual calculations. Initially created to assist Dr. Laura Meredith in managing a large database of volatile compounds, volcalc has since grown into a more versatile tool under Eric’s leadership, now supporting a wider range of researchers.\nKristina and Eric share insights into the challenges they faced, including managing dependencies, integrating with CRAN and Bioconductor, and refining complex molecular identification methods. They also discuss future enhancements, such as incorporating temperature-specific volatility calculations and expanding the package’s functionality to estimate other compound characteristics. This project was funded by the R Consortium.\nCould you share what motivated the development of the volcalc package and how it aligns with the broader goals of the R ecosystem, particularly in scientific computing?\nKristina: I was heavily involved in the initial development of volcalc, and later on, Eric took over the project. We developed volcalc because we began collaborating with Dr. Laura Meredith, who was compiling a database of volatile chemical compounds. At the time, she had around 300 compounds, and her students manually gathered details for each one by examining their representations and calculating various associated values. This process was tedious and prone to errors, so we thought there must be a more efficient and automated way to handle it.\nThat’s when we came up with the idea of creating a pipeline where someone could input a compound and quickly receive its volatility information, eliminating the need for all the manual labor. The purpose of volcalc was to transform the process from taking months to gather details for 300 compounds to obtaining information for thousands in a much shorter time.\nEric: volcalc was initially developed specifically for a project where the researchers were mainly interested in chemical compounds from the KEGG database (Kyoto Encyclopedia of Genes and Genomes). When I joined the team and learned about the project, I was thrilled because, as a chemical ecologist, I saw its potential. However, I also recognized a limitation: the tool only worked with the KEGG database. This was a drawback because many researchers, including food scientists and others who work with similar compounds, might not find their compounds in that specific database.\nThis realization inspired me to apply for the R Consortium grant. We saw a significant opportunity to expand volcalc, making it more flexible and applicable to a wider range of researchers. We also wanted to improve its integration within the R ecosystem by adding features like returning the file path of a molecule representation after downloading it, so it could be easily piped into subsequent steps. These enhancements aimed to make the tool more versatile and user-friendly for a broader audience.\nWhat were the most significant challenges you faced during the development of the initial version of volcalc, and how did you overcome them?\nKristina: One of the most challenging aspects of developing volcalc, which continues to be an issue, is managing dependencies. Specifically, we rely heavily on a command-line program to handle much of the processing. Early on, we struggled with how to enable users to run volcalc without needing to install this program on their own computers, as many of our users aren’t familiar with that kind of setup. I spent a lot of time trying to create a reproducible environment using Binder, but I was never able to get it fully working. Even today, there are still issues related to managing these dependencies, which Eric can elaborate on further.\nIt was incredibly important to have Eric on this project because I don’t have a strong background in chemistry. His ability to come in and figure out some of the intricate details that would have taken me much longer to grasp was a huge advantage. The more we can collaborate with domain experts, the better our results will be.\nEric: One thing that has helped with the dependency challenges is that we’ve started building volcalc on R-Universe, which means binaries are available there. While it’s not on CRAN yet, having these binaries on R-Universe makes installation a bit easier. However, we’ve faced some challenges with dependencies, particularly because two of them are from Bioconductor. We didn’t originally aim to develop this package for Bioconductor, which uses S4 objects and has different standards than CRAN. Our goal was to get it on CRAN, but our first submission was rejected because the license field for the Bioconductor package wasn’t formatted to CRAN’s liking. These differences between Bioconductor and CRAN have created barriers, even though the authors of the Bioconductor package have been very responsive. Their package works fine on Bioconductor, but it doesn’t meet CRAN’s criteria, which has been a frustrating challenge.\nAnother major challenge in developing volcalc relates to the method we use for estimating volatility. This method involves counting the numbers of different functional groups on molecules—such as hydroxyl groups or sulfur atoms—and assigning coefficients to them. To do this programmatically, we use something called SMARTS, which is essentially like regular expressions but for molecular structures. Regular expressions for text are already challenging, but SMARTS is even more complex because it deals with three-dimensional molecules.\nBefore I joined the group, the first version of volcalc had most of these functional groups figured out, but not all. I spent a significant amount of time trying to develop SMARTS strings to match additional molecules. Moving forward, I hope that if we implement new versions, we can get help from the community to refine these SMARTS strings, as there are likely people out there who are more skilled at it than I am.\nThe original project proposal mentions expanding volcalc to work with any chemical compound with a known structure. What are the key technical challenges you anticipate in achieving this goal?\nEric: This task turned out to be less difficult than I initially expected, but let me explain. In the original version of volcalc, before we received the R Consortium funding, the main function started with a KEGG ID—an identifier specific to the KEGG database. The function would download a MOL file, which is a text representation of a molecule corresponding to that ID. It would then identify and count the functional groups in the molecule, and finally, calculate the volatility based on those counts.\nThe major change we needed to implement to make volcalc more versatile was to decouple these steps. In the current version of volcalc, the functionality to download a MOL file from KEGG is still available, but it’s now separate from the main function that calculates volatility. This means that the inputs for calculating volatility can now be any MOL file, not just ones from KEGG. The file can come from any database, be exported from other software, or even be downloaded manually. Additionally, the tool now supports SMILES, which is another, simpler text-based representation of molecules.\nThere are various ways to represent chemicals in text, including another format called InChI. The Bioconductor packages we use, ChemmineR and ChemmineOB, have the ability to translate from InChI and other types of chemical representations. However, that feature isn’t available on Windows. So, I decided to keep volcalc focused on SMILES and MOL files. I believe that chemists and other researchers should be able to obtain data in one of these two formats, or use another tool to translate their data into these formats. I didn’t want to overload volcalc with the responsibility of being a chemical representation translator, as that didn’t seem like its primary purpose.\nCan you walk us through the process of implementing the SIMPOL algorithm within the volcalcc package?\nKristina: The algorithm itself is fairly simple; it’s just basic math. You need to input some constants, the mass of the compound, and the counts of the functional groups we discussed earlier. Writing the code for this was straightforward and not particularly challenging.\nEric: Each functional group has a coefficient associated with it, which is multiplied by the number of times that group appears in the molecule. These values are then summed up, and the mass of the molecule is factored in as well. The challenging part wasn’t the algorithm itself, which is straightforward—just multiplying by coefficients and adding them up. The real difficulty was interpreting what the authors of the algorithm meant by each of the functional groups. Some were oddly specific, like how the hydroxyl group that is part of a nitrophenol group isn’t supposed to count toward the total number of hydroxyl groups. I spent a lot of time poring over the paper, particularly one table, to fully understand how they defined each group. That interpretation was the hardest part.\nWhat future functionalities or expansions do you see as crucial for volcalc, especially in the context of evolving research needs in chemoinformatics?\nEric: Right now, we’re working on allowing users to specify different temperatures. The paper that describes the SIMPOL.1 method includes equations for how the coefficients of each functional group change with temperature. These changes aren’t always linear, and the contributions of functional groups can shift in importance as the temperature varies. This is an important feature to include because the version of volcalc we currently have uses coefficients calculated at 20°C, based on a table from the original paper. To accommodate other temperatures, we need to integrate another table that provides equations for calculating these coefficients based on temperature, and that’s what we’re working on.\nAnother key feature we want to leave room for in the future is the ability to add other methods for estimating volatility. SIMPOL.1 is just one type of group contribution method, but there are other approaches described in various papers that use different functional groups, equations, and coefficients. The basic idea remains the same: count the functional groups in a molecule, apply an equation, and estimate volatility. We’re trying to structure the code in a way that makes it easy to incorporate additional methods later, even if we don’t add them right away. I think these are the most important features we’re focusing on right now.\nKristina: We’re focused on the features I mentioned in the near future, but looking further ahead, I could see volcalc expanding to estimate other characteristics of compounds beyond just volatility. While I’m not a chemistry expert or a chemical ecologist, I imagine that those interested in volatility might also be interested in other compound characteristics that currently lack automated tools for estimation. So, it’s possible the package could evolve to include those features.\nThat said, one of the things I appreciate about the R package ecosystem is that it allows for specialized tools. Since anyone can build what they need, we don’t end up with massive, overly complex packages that try to do everything and become difficult to maintain. It might be better to keep volcalc focused and leave room for separate packages to handle additional functionality. This way, the tools remain manageable and easier to maintain in the long run.\nHow has it been working with the R Consortium? Would you recommend applying for an ISC grant to other R developers?\nKristina: The application process was straightforward, and I found the grant format to be very practical. It was focused on milestones and product development, which is refreshing compared to many academic research grants that tend to avoid specific deliverables. I highly recommend considering this grant. I believe people often overlook smaller funding sources, but even small amounts can make a big impact on the work you’re doing.\nEric: The first time I applied for an R Consortium grant was as a grad student, and I strongly encourage trainees to apply as well. It was a great experience for me because I could do it independently—my advisor wasn’t involved as one of the authors, and it wasn’t a complex process like applying for an NSF grant. It was straightforward and really rewarding. The only tricky part was figuring out the payment process, but that’s something people can work out.\nI’ve noticed there seem to be fewer projects in recent years, and I don’t think it’s due to a lack of funding. It seems like fewer people are applying, which is why I especially encourage others to give it a shot. From what I’ve seen, there’s a very good chance of getting funded if you apply right now.\nPeople should be creative and think broadly about how their project can benefit the broader R community. This doesn’t mean you need to develop the next big thing like R-Universe or CRAN. It can be something smaller, like a package that other R users will find helpful. For example, with our project, volcalc, our main goal was to encourage chemists—who usually use point-and-click software—to start using R. That was enough of a contribution to the R community to get funded. So, I really encourage people to think creatively about what “benefiting the R community” can mean." }, { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "", - "text": "Guest Post contributed by Andrea Luciani, Bank of Italy, Directorate General for Economics, Statistics and Research, maintainer of the bimets package (Time Series and Econometric Modeling) in CRAN\nThe US Federal Reserve’s econometric model for the US economy (i.e., FRB/US) is publicly available at federalreserve.gov. The website states, “FRB/US is a large-scale estimated general equilibrium model of the US economy that was developed at the Federal Reserve Board, where it has been in use since 1996 for forecasting, analysis of policy options, and research projects.”\nFRB/US is a quarterly model with hundreds of equations and variables. The model definition and time series data are available for download on the Federal Reserve website, as is the source code, which allows users to perform several econometric exercises. However, the Federal Reserve publicly distributes source codes only for EViews™ and python.\nIn this post, we show how to load the FRB/US model, and perform in R the same econometric exercises provided by the Federal Reserve." + "objectID": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html#about-isc-funded-projects", + "href": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html#about-isc-funded-projects", + "title": "Unlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research", + "section": "About ISC Funded Projects", + "text": "About ISC Funded Projects\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nLearn More!" }, { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#the-frbus-model", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#the-frbus-model", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "The FRB/US model", - "text": "The FRB/US model\nThe Federal Reserve website also states, “Compared with DSGE models, however, FRB/US applies optimization theory more flexibly, which permits its equations to better capture patterns in historical data and facilitates modeling the economy in greater detail… A distinctive feature of FRB/US is its ability to switch between alternative assumptions about how economic agents form expectations. Under the VAR-based option, expectations are derived from the average historical dynamics of the economy as manifested in the predictions of estimated VAR models. Under model-consistent (MC), agents are assumed to form accurate expectations of future outcomes as generated by simulations of FRB/US itself.”\nFRB/US is a quarterly model, and counts 284 equations and 365 variables (Feb. 2024 version). The XML model definition is available for download on the Federal Reserve website, and contains, for each endogenous variable, the following information: the variable name, the variable definition with a short description, the economic sector the variable belongs to, the related equation in both EViews™ and python format, coefficients and exogenous variables involved in the equation.\n64 endogenous variables are marked as stochastic and, during the stochastic simulation exercise, will be transformed by applying sequences of shocks as drawn randomly from their historical residuals.\n14 endogenous variables belong to the MCE group (i.e., Model-Consistent Expectations) and have an alternative equation that contains forward-looking references.\nFinally, at the end of the XML model definition, users can find additional information on economic sectors and exogenous variables involved in the model definition." + "objectID": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html", + "href": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html", + "title": "The Evolution of Melbourne’s Business Analytics and R Business User Group", + "section": "", + "text": "Maria Prokofieva, organizer of the Business Analytics and R Business User Group, spoke to the R Consortium last year about the Adoption of R by the Actuaries Community in Melbourne. Recently, Maria updated the R Consortium on the group’s focus, which has shifted towards business consultancy. The group provides a platform for graduate students to gain valuable industry experience and mentorship through various projects. The group is committed to ethical data governance and inclusive community building and prioritizes these values in all its initiatives.\nPlease share about your background and your involvement in the R Community.\nMy name is Maria Prokofieva. I work as a Leading ML Engineer at Mitchell Institute at Victoria University. I lead a stack of projects that use data to inform strategy and policy development. I am also an academic at the university, conducting research and teaching courses on ML/AI and data analysis. Through my work, I have the privilege of collaborating with various organizations, governments, and scholars to assist them in utilizing data to make decisions that impact the lives of many. I love open source, and what we see today is amazing – the world is changing. I have been a member of R and Python communities for many years, and seeing us grow is great.\nHow has your R User Group been doing since the last time we spoke?\nThe group has been performing well. As we grow, we focus on projects and become extremely busy with them. We already have a small community of people involved in different projects who also work together and communicate regularly. Once a month, we organize meetups where we present master classes—we moved to an in-person space but occasionally do online events. Our group has two main directions: business consultancy and business knowledge exchange.\nWe have been quite successful in building connections with bigger and smaller businesses interested in doing more data analysis. Some smaller businesses have staff who can perform their duties, and this is where community members have been fantastic.\nThe backbone of my community comprises my current and former Master’s students, who completed a course on business analytics. They are passionate about using R in everyday tasks and already possess some knowledge and experience, which they are happy to share. They are also interested in building connections and networking for their future jobs. This platform provides a mutually beneficial relationship for new students who get valuable industry experience through unpaid volunteering. These students receive mentorship from business leaders and senior software developers who share their programming knowledge and their knowledge of business negotiations and working with clients through the entire project life cycle.\nWe have been successful in working with cloud services such as AWS. We are actively exploring ways to automate data science on AWS and have several upcoming workshops where we will dive deeper into this topic. One workshop will focus on AWS Bedrock, where we will introduce non-technical business community members to employing large language models to perform their tasks. Our workshops focus on addressing specific problem-solving tasks rather than just the environment. We look into the business problems and how they can be solved.\nIt’s better to identify a problem and brainstorm solutions than to focus on tools. It’s fascinating to see how the community comes up with unique solutions to the problem. This approach is exactly what we need today, where no single preferred tool exists. Even if we use R Studio, we can easily integrate Python and other environments to accomplish the task. The focus should always be on the task guiding the process rather than the tools themselves.\nAny recent project you have worked on using R?\nOur recent project is based on utilising AWS Bedrock and GPT-4 to implement a Retrieval-Augmented Generation (RAG) system for a business. This system streamlines customer email communication using internal documents and company FAQs to auto-generate tailored responses. With some components there, we successfully integrated data analysis in R with Python implementation. We also have a few projects using open source models and integrating transformer models from Hugging Face. R is a star for any data-wrangling tasks and data visualizations!\nWhat are your plans for the upcoming months?\nOne area of interest that we plan to focus on is the use of responsible AI and responsible practices. This is crucial not only for AI but also for any data management that we undertake. Responsible modeling and responsible data science are important concepts that need more attention. We have seen instances where people intentionally or accidentally manipulate statistics, and this needs to change. We must focus on being data governors and ensure our analysis is responsible. This includes managing the data and the application size, as well as ensuring continuity of work. Many packages are available, but maintaining and updating them is challenging. Our future work is to contribute to the community by ensuring the continuity of our packages so developers can rely on them.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nMany people talk about large language models, but the focus is often on their applicability and use cases. While many amazing models are available, businesses need to see how they can be practically applied to their needs. It’s not just about text generation – image generation and other areas are also important. When we share the use cases with the businesses, the possibilities they haven’t considered often amaze them. Therefore, there is a growing demand for case studies demonstrating these models’ practical applications rather than just tutorials.\nWe focus on the practical applications of tools. Our approach is to identify a problem and explore various solutions. I’m not interested in specific software packages but in finding efficient solutions to problems. If there’s a new tool that can help me solve a problem more effectively, I’m open to learning about it and sharing my experience with others.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nThe most important technique is interaction, networking, and keeping the connection alive among the group members. This is especially crucial when you have a larger proportion of new users in the group. It’s important to ensure that once they learn the skills, they understand that we are all busy and have business obligations to attend to. Therefore, it’s necessary to make sure that we keep the group relevant to all members, without getting carried away by our busy lives.\nThis is more about sitting together and engaging in problem-solving exercises, such as preparing for AWS certification. The group can help with other tasks, too, creating additional value beyond just learning. This is where the benefits of membership come in. Members are also motivated to give back to the community, as they can use their skills in real life, not just for learning purposes.\nFor instance, we have an AWS data practitioner interested in learning R. However, this is an opportunity for that person to share their expertise and contribute to the group. Similarly, we have a cybersecurity professional who is also interested in learning R. But this is an opportunity for them to present a use case on how machine learning can automate some of their tasks. They are also willing to share their knowledge, which may not have been considered. Therefore, it’s important to create a diverse experience for all members and engage with them in all possible ways. While it can be difficult to involve every group member, it’s crucial to understand their general interests and what’s important for them and focus on their professional development.\nTake a moment to analyze where your members come from and their future plans and steps. Discuss their next career moves. It will be beneficial to provide networking opportunities where members can get referrals for job searches and advice for their next career move. These opportunities are quite important. Therefore, promotions should always be the end goal. You cannot become complacent or content with where you are because life is about growth and evolution." }, { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#moving-towards-r", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#moving-towards-r", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "Moving towards R", - "text": "Moving towards R\nFRB/US model definition is available to R users in the FRB__MODEL dataset of the bimets package (bimets ver. 4.0.2, a software framework for time series analysis and econometric modeling):\n\n#load bimets\nlibrary(bimets)\n\n\n#load FRB/US MDL definition\ndata(FRB__MODEL)\n\n#print first 4 equations in model definition\ncat(substring(FRB__MODEL,1,1615))\n\nMODEL\n\n$DOWNLOADED FROM federalreserve.gov AND CONVERTED TO BIMETS MDL IN Feb, 2024\n\n$FRB/US is a large-scale estimated general equilibrium model of the U.S. economy \n$that was developed at the Federal Reserve Board, where it has been in use since 1996 \n$for forecasting, analysis of policy options, and research projects. \n\n$--------------------------------------------------------------------------\n\n$ ENDOGENOUS SECTION\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for both thresholds\n$DMPTMAX equals one when either the unemployment threshold or\n$the inflation threshold is breached.\nIDENTITY> dmptmax\nIF> dmptlur>=dmptpi\nEQ> dmptmax=\ndmptlur\nIDENTITY> dmptmax\nIF> dmptlur<dmptpi\nEQ> dmptmax=\ndmptpi\n\n$-----------------------------------------------\n$Federal funds rate, first diff\nIDENTITY> delrff\nEQ> delrff=\nTSDELTA(rff)\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for unemployment threshold\n$DMPTLUR equals zero when the unemployment rate is above its\n$threshold (LURTRSH) one when it is below. A logistic function\n$smoothes the transition, improving solution convergence properties.\nIDENTITY> dmptlur\nEQ> dmptlur=\n1/(1+EXP(25*(lur-lurtrsh)))\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for inflation threshold\n$DMPTPI equals zero when expected inflation is below its threshold\n$and one when it is above. A logistic function smoothes the\n$transition, improving solution convergence properties.\nIDENTITY> dmptpi\nEQ> dmptpi=\n1/(1+EXP(-25*(zpic58-pitrsh)))" + "objectID": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html#how-do-i-join", + "href": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html#how-do-i-join", + "title": "The Evolution of Melbourne’s Business Analytics and R Business User Group", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#dynamic-simulation-in-a-monetary-policy-shock", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#dynamic-simulation-in-a-monetary-policy-shock", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "Dynamic simulation in a monetary policy shock", - "text": "Dynamic simulation in a monetary policy shock\nThe first econometric exercise proposed by the Federal Reserve is a dynamic simulation of the FRB/US model under a monetary policy shock. The simulation is operated from 2040-Q1 to 2045-Q4, after the rffintay time series, defined as “Value of eff. federal funds rate given by the inertial Taylor rule”, is shocked by 100 base points in 2040-Q1.\n\n# Load data\ndata(LONGBASE)\n\n# Load model\ndata(FRB__MODEL)\nmodel <- LOAD_MODEL(modelText = FRB__MODEL)\n\nAnalyzing behaviorals...\nAnalyzing identities...\nOptimizing...\nLoaded model \"FRB__MODEL\":\n 0 behaviorals\n 284 identities\n 0 coefficients\n...LOAD MODEL OK\n\n# Load data into model\nmodel <- LOAD_MODEL_DATA(model, LONGBASE, quietly=TRUE)\n\n# Specify dates\nstart <- c(2040,1)\nend <- normalizeYP(start+c(0,23),4)\n\n# Standard configuration, use surplus ratio targeting\nmodel$modelData$dfpdbt[[start,end]] <- 0\nmodel$modelData$dfpsrp[[start,end]] <- 1\n\n# Solve to baseline with adds\nmodel <- SIMULATE(model,\n simType='RESCHECK',\n TSRANGE=c(start,end),\n ZeroErrorAC = TRUE,\n quietly=TRUE)\n\n# 100 bp monetary policy shock\ntrac <- model$ConstantAdjustmentRESCHECK\ntrac$rffintay[[start]] <- trac$rffintay[[start]]+1\n\n# Solve\nmodel <- SIMULATE(model,\n simAlgo = 'NEWTON',\n TSRANGE = c(start,end),\n ConstantAdjustment = trac,\n BackFill = 12,\n quietly=TRUE)\n\nR code produces the following charts:\n\nOn the other hand, the python code provided by the US Federal Reserve produces very similar results:" - }, - { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#stochastic-simulation", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#stochastic-simulation", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "Stochastic simulation", - "text": "Stochastic simulation\nAnother econometric exercise proposed by the Federal Reserve is a stochastic simulation of the FRB/US model. The stochsim procedure in the pyfrbus python package (available on the Federal Reserve web site) performs a stochastic simulation by applying sequences of shocks to 64 endogneous variables of the model, as drawn randomly from historical residuals. In a similar way in R, the STOCHSIMULATE procedure allows users to shock the same endogenous variables with randomly sampled historical residuals.\nR code, omitted for brevity, produces the following charts:\n\nOn the other hand, the python code provided by the US Federal Reserve produces very similar results, despite the random numbers generator being different between R and python:" + "objectID": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html", + "href": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html", + "title": "Improving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade", + "section": "", + "text": "The R Consortium recently connected with Kylie Bemis, assistant teaching professor at the Khoury College of Computer Sciences at Northeastern University. She has a keen interest in statistical computing frameworks and techniques for analyzing intricate data, particularly focusing on datasets with complex correlation patterns or those that amalgamate data from various origins.\nKylie created matter, an R package that offers adaptable data structures suitable for in-memory computing on both dense and sparse arrays, incorporating multiple features tailored for processing nonuniform signals, including mass spectra and various other types of spectral data. Recently, Kylie upgraded matter to version 2.4. Since our May 2023 discussion, Kylie has enhanced its signal processing capabilities, focusing on analytical tools like principal component analysis and dimension reduction algorithms, which are crucial for imaging and spectral data. A grant from the R Consortium supports this project.\nWe talked with you about matter in May 2023. You were providing support for matter and looking to improve the handling of larger data sets and sparse non-uniform signals. matter has been updated to version 2.4. What’s new?\nLast time we spoke, I had already rewritten most of the matter infrastructure in C++ for better maintainability. Since then, my focus has been on enhancing our signal processing capabilities. This summer, I’ve been adding essential signal processing functions and basic analytical tools, which are particularly useful in fields dealing with spectra or various types of signals.\nI’ve incorporated fundamental techniques like principal component analysis, non-negative matrix factorization, and partial least squares. I’ve also added several dimension reduction algorithms and a range of signal processing tools for both 1D and 2D signals. This includes smoothing algorithms for images and 1D signals and warping tools applicable to both.\nThese enhancements are crucial for working with imaging and spectral data and include features like distance calculation and nearest neighbor search.\nMy aim has been to augment matter with robust signal processing tools, particularly for sparse and non-uniform signals. This is inspired by my experience in augmented reality (AR) and my desire to integrate tools similar to MATLAB’s Signal Processing Toolbox or SciPy in Python. As someone primarily analyzing mass spectrometry imaging data, I found these tools initially in my Cardinal package. I wanted to transfer them to a more appropriate platform, not specific to mass imaging, and reduce Cardinal’s reliance on compiled native code for easier version updates.\nAdditionally, I’ve been building a more robust testing infrastructure for these tools and documenting them thoroughly, including citations for the algorithms I used for key picking and smoothing techniques. This documentation details the implementation of various algorithms, such as guided filtering and nonlinear diffusion smoothing, citing the sources of these algorithms.\nBy providing support for non-uniform signal data, matter provides a back end to mass spectrometry imaging data. But working with large files is applicable in a lot of domains. What are some examples?\nI deal with large files and data sets across various fields. Matter can be particularly impactful in areas dealing with signal, spectral, or imaging data. One field that comes to mind is remote sensing, where the imaging tools I’ve incorporated would be highly beneficial. That’s one key application area.\nAnother field is biomedical imaging, especially MRI data. For instance, a data format we often use for mass spectrometry imaging was originally developed for MRI – it’s called Analyze, and there’s a more recent variant known as NIfTI. This format is also supported in Cardinal for mass spec imaging data, but it’s primarily used in MRI and fMRI data analysis. While matter doesn’t directly offer plug-and-play functionality for MRI data, with some modifications, it could certainly be adapted for importing and processing MRI data stored in these formats.\nWe don’t have a specific function to read NIfTI files directly, but the structure of these files is quite similar to the mass imaging files we commonly work with. They consist of a binary file organized in a particular format, with a header that functions like a C or C++ struct, indicating where different image slices are stored. Understanding and interpreting this header, which is well-documented elsewhere, is key.\nSo, with some effort to read and attach the header file correctly, it’s entirely feasible to build a function for reading and importing MRI data. We’ve already done something similar with the Analyze format. Someone could definitely examine our approach and develop a method to handle MRI data effectively.\nPreviously, you indicated you wanted to improve R data frames and string support. You have a prototype data frame in the package already? What’s the schedule for improvements?\nI’m currently evaluating how far we’ll expand certain features in our project. One of these features is supporting strings, which is already implemented. Regarding data frames, I believe there might be better solutions out there, but it’s quite simple to integrate our data with them. For instance, taking a vector or an array, whether a matter matrix or a matter vector, and inserting it into a data frame column works well, particularly with Bioconductor data frames.\nI’m not entirely convinced that developing standalone, specialized data frame support in matter is necessary. It seems that other platforms, especially those like Bioconductor, are already making significant advancements in this area. For now, it seems sufficient that users can easily incorporate a matter vector or array into a data frame column. I’m hesitant to duplicate efforts or create overlapping functionalities with what’s already being done in this field.\nWhat’s the best way for someone to try matter? How should someone get started?\nLike any Bioconductor package, we offer a vignette on the Bioconductor website. This vignette provides a basic guide on how to start using our package, including creating matrices and arrays. It shows how these can serve as building blocks to construct larger matrices, arrays, and vectors. This is a straightforward way for users to begin.\nRegarding the applicability of our package, it really depends on the specific data needs of the user. For instance, our package provides out-of-memory matrices and arrays. If that’s the primary requirement, then our package is certainly suitable. However, there are other packages, both in Bioconductor, like HDF5 array support, and on CRAN, such as big memory and FF, that also offer similar functionalities.\nThe real advantage of our package becomes apparent when dealing with specific data types. If you’re working with data formats like MRI, where you have a binary file and a clear understanding of its format, our package can be very helpful. It simplifies attaching different parts of the file to an R data structure.\nMoreover, if your work involves signal data, particularly non-uniform signals like those in mass spectrometry or imaging data, our package becomes even more beneficial. Over the summer, I’ve added extensive support for preprocessing, dimension reduction, and other processes that are crucial for handling these types of data. So, in these scenarios, our package can be a valuable tool.\nAnything else you would like to share about matter 2.0?\nI’ve spent much of the summer working on improvements to the matter package, and it’s now in a good place, particularly regarding signal processing capabilities. These enhancements are largely aligned with the needs of mass spectrometry, an area I closely focus on. As new requirements emerge in mass spectrometry, I’ll look to add relevant features to matter, particularly in signal and image processing.\nHowever, my current priority is updating the Cardinal package to support all these recent changes in matter. Ensuring that Cardinal is fully compatible with the new functionalities in matter is my next major goal, and I’m eager to get started on this as soon as possible." }, { - "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#section", - "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#section", - "title": "The U.S. Federal Reserve quarterly model in R", - "section": "________________", - "text": "________________\nAdditional exercises, e.g., rational expectations, endogenous targeting, etc., and computational details are available in the package vignette The U.S. Federal Reserve quarterly model in R with bimets" + "objectID": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html#how-do-i-join", + "href": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html#how-do-i-join", + "title": "Improving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/empowering-r-enthusiasts-satrdays-london-2024-unveiled/index.html", - "href": "posts/empowering-r-enthusiasts-satrdays-london-2024-unveiled/index.html", - "title": "Empowering R Enthusiasts: SatRDays London 2024 Unveiled", + "objectID": "posts/enhancing-clinical-trial-data-sharing-with-r-consortiums-r-submissions-working-group/index.html", + "href": "posts/enhancing-clinical-trial-data-sharing-with-r-consortiums-r-submissions-working-group/index.html", + "title": "Enhancing Clinical Trial Data Sharing with R Consortium’s R Submissions Working Group", "section": "", - "text": "SatRDays London 2024 is set to ignite the data science community with a vibrant lineup of speakers and a rich array of topics ranging from survival analysis to geospatial data. This inclusive event, designed for R enthusiasts at all levels, emphasizes networking and collaboration amidst the backdrop of King’s College London’s iconic Bush House. Keynote speakers like Andrie de Vries, Nicola Rennie, and Matt Thomas bring unparalleled expertise, offering attendees a unique opportunity to deepen their knowledge and connect with peers. As a hub of innovation and learning, SatRDays London promises to be a cornerstone event for anyone passionate about R and its applications in the real world.\n\nRegister Now!\nHow does this year’s satRDays in London compare to last year’s event? What’s new and different?\nAfter a successful SatRdays London in 2023, we are keeping the format the same, but with a whole new lineup of speakers! This year we’re excited to welcome:\n\nAndrie de Vrie – Posit\nHannah Frick – Posit\nCharlie Gao – Hibiki AI Limited\nMichael Hogers – NPL Markets Ltd\nMatthew Lam & Matthew Law – Mott MacDonald\nMyles Mitchell – Jumping Rivers\nNicola Rennie – Lancaster University\nMatt Thomas – British Red Cross\n\nTalk topics for the day include survival analysis, geospatial data, styling PDFs with Quarto and using R to teach R, as well as a range of other exciting themes! The talks can reach a varied audience from aspiring data scientists right to the experienced audiences.\nTake a look at the full list on the conference website for more information.\nWho should attend? And what types of networking and collaboration opportunities should attendees expect?\nAnyone and everyone with an interest in R! The SatRdays conferences are designed to be low cost, to allow as many to attend as possible, and they’re on a SatRday, so you don’t have to worry about getting time off work if your job isn’t necessarily R focussed.\nNetworking is the main focus of the event. We have multiple coffee breaks to give attendees the opportunity to interact with fellow R enthusiasts. If you’re brand new to this kind of event, and are not sure where to start, don’t worry! Find one of the attendees from JR, and we’ll be happy to help you make introductions!\nCan you share some insights into the keynote speakers, their areas of expertise, and how they will contribute to the overall experience at SatRDays?\nAt this year’s event, we have talks from three invited speakers – Andrie de Vries of Posit, Nicola Rennie from the University of Lancaster and Matt Thomas of the British Red Cross.\nAndrie is Director of Product Strategy at Posit (formerly RStudio) where he works on the Posit commercial products. He started using R in 2009 for market research statistics, and later joined Revolution Analytics and then Microsoft, where he helped customers implement advanced analytics and machine learning workflows.\nNicola is a lecturer in health data science based at the Centre for Health Informatics, Computing, and Statistics at Lancaster University. She is particularly interested in creating interactive, reproducible teaching materials and communicating data through effective visualisation. Nicola also collaborates with the NHS on analytical and software engineering projects, maintains several R packages, and organises R-Ladies Lancaster.\nMatt is Head of Strategic Insight & Foresight at the British Red Cross. His team conducts research and analysis to understand where, how and who might be vulnerable to various emergencies and crises within the UK.\nCould you elaborate on the types of sessions and workshops available and how they cater to different interests and skill levels within the R community?\nThe day will consist of eight 25-ish minute talks, plus Q&A, from a variety of speakers across various sectors.\nThe talks are on a wide range of topics. For example, last year we had speakers talking about everything from using R for mapping air quality, to EDI and sustainability in the R project, and why R is good for data journalism. If you want to take a look at what you can expect, we have a playlist of last year’s talk recordings available on our YouTube channel.\nWith the event being hosted at King’s College London, how does the venue enhance the experience for attendees, both in terms of facilities and location?\nWe’re very excited to be partnering with CUSP London again this year, who provide the amazing Bush House venue at King’s College London. The venue is a beautiful listed building, right in the heart of London, only a few minutes walk from Covent Garden.\nBeing in the center of London means easy access to multiple public transport links, both for national and international attendees!\nThe venue facilities and supporting technology provides a great space for sharing insights and networking.\n\n\nDon’t miss out, register today!" + "text": "The R Consortium’s working group R Submissions Working Group is spearheading an innovative approach to clinical trial data sharing, according to a feature in Nature. This initiative, led by Eric Nantz, a statistician at Eli Lilly in Indianapolis, Indiana, involves a pilot project with the US Food and Drug Administration (FDA). Sharing clinical trial data traditionally requires each scientist to install custom computational dashboards, a cumbersome and error-prone process.\nNantz elaborates on the benefits of using webR and WebAssembly in this context: “Using WebAssembly, [it] will minimize, from the reviewer’s perspective, many of the steps that they had to take to get the application running on their machines.” This technology not only simplifies the data sharing process but also has the potential to accelerate drug approval timelines and enhance collaborative research across various fields.\nFor more details, read the full article on Nature’s website:Read the full article here (Paid subscription required).\nTo further explore Eric Nantz’s insights on using R and Shiny in regulatory submissions, you can also check out the R/Adoption Series: R and Shiny in Regulatory Submissions with Eric Nantz." }, { - "objectID": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html", - "href": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html", - "title": "Empowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative", + "objectID": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html", + "href": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html", + "title": "Navigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors", "section": "", - "text": "The Dengue Data Hub, an ambitious initiative funded by the R Consortium ISC, transforms how researchers access and utilize dengue-related data. At its core, the Dengue Data Hub aims to provide a centralized repository for dengue incidence, mortality, and risk-related data, streamlining the research process and empowering scientific inquiry into this global health issue. The platform offers easy access through the denguedatahub R package, a Shiny app, and an informative website, making data analysis more efficient and accessible.\nPlease note: denguedatahub version 2.1.1 was published on CRAN on Sep 22, 2024.\nDr. Thiyanga Talagala, a Senior Lecturer at the University of Sri Jayewardenepura in Sri Lanka, spearheads this initiative. With a PhD from Monash University, where she honed her skills in R programming and data science, Dr. Talagala is deeply passionate about leveraging her expertise to address Sri Lanka’s public health challenges, particularly dengue. Together with her sister, Dr. Priyanga Talagala, she co-founded the R-Ladies Colombo group and has been instrumental in bringing innovative solutions to the scientific community. Dr. Talagala’s commitment to enhancing dengue research through accessible data resources is central to her ongoing work, making the Dengue Data Hub a vital tool for researchers worldwide.\nTell us about your background and how it connects to the Dengue Data Hub project\nCurrently, I am working as a Senior Lecturer, Department of Statistics, Faculty of Applied Sciences, University of Sri Jayewardenepura, Sri Lanka. I earned my PhD from Monash University, Australia. During my time at Monash University in Australia, I was part of the NUMBAT research group, where I developed a deep interest in the R programming language and discovered its incredible potential for data analysis and research. I also had the opportunity to meet and collaborate with leading experts in the field, which further fueled my passion for R and data science. I also got to know about the R Ladies community, and I attended events organized by R-Ladies Melbourne.\nOnce I returned to Sri Lanka after completing my PhD, I felt a strong desire to contribute to my country using the knowledge I had gained. I, along with my Sister, Dr Priyanga Dilini Talagala (we both did our PhDs together at Monash University), established the R Ladies Colombo meetup group.\nDengue is a major public health issue in Sri Lanka. As a data scientist, I can contribute to its mitigation by establishing a centralized repository for dengue data for data analysis and modeling, which empowers dengue research. This project was funded by R Consortium ISC 2022 - 1 Grant and I have been working on it since 2022.\nWhat is the Dengue Data Hub?\nThe Dengue Data Hub is a centralized repository that provides access to a variety of data sets related to dengue incidence and other relevant factors. This includes data on dengue deaths, reported cases, indigenous cases, local cases, dengue serotypes, breeding sites, and country-wise levels of risk. I have data related to annual dengue incidence for 195 countries around the world.\nWhy is this project important for the research community?\nDengue researchers often spend their valuable time searching for datasets, web scraping and cleaning data. The publication of data in a centralized repository helps to prevent duplicate efforts. The dengue data hub enables the community to focus on analysis and modeling rather than data collection and cleaning. Additionally, it enhances research sustainability by allowing researchers to utilize data for their studies while preserving it for future researchers.\nHow do researchers use the Dengue Data Hub?\nThere are three straightforward ways for anyone to participate. Use the denguedatahub R software package, use the Dengue Data Hub Shiny app (for non-programmers), or use our website which provides tutorials and examples.\nThe denguedatahub R package allows researchers to download dengue-related data easily. For Sri Lanka, it includes web scraping functions that directly retrieve weekly epidemiological reports published by the Epidemiology Unit, Ministry of Health, Sri Lanka. This functionality also cleans the data into a tidy format. Additionally, the package offers various data manipulation functions tailored for dengue data visualization and modeling. You can find the package on GitHub at https://github.com/thiyangt/denguedatahub.\nThe Shiny app provides an interface for non-programmers to access dengue data. It is available at: https://denguedatahub.shinyapps.io/denguedatahub/\nThis website is the home for the projects. It provides tutorials and examples. The site was developed using Quarto.\nWhat impact do you hope the Dengue Data Hub will have?\nMy hope is that the Dengue Data Hub will become a go-to resource for dengue researchers globally. I believe the hub will accelerate dengue research and discoveries which will help in developing effective strategies to combat dengue. The dengue data hub also serves as a\nteaching tool for data science and statistics, as it includes comprehensive data sets.\nDo you have any final thoughts or messages you’d like to share with the research community?\nI invite dengue researchers worldwide to collaborate on this project. I do not have access to clinical trial data, so contributions in that area would be especially valuable. We are looking to expand the datasets available, as comprehensive data sharing is essential for advancing our collective understanding of dengue epidemiology. Additionally, we welcome contributions of data, analytical tools, and insights that can help strengthen the hub’s capacity to serve as a central resource for researchers globally.\nYou can learn more about how to collaborate here. We can build a stronger network to enhance dengue research and response efforts worldwide." + "text": "The R Consortium recently spoke with Mario Annau, co-organizer of the Vienna R User Group. During the conversation, he discussed the use of R in the finance and pharmaceutical industries in Vienna. He also shared insights into the latest and upcoming trends in using R in these sectors and tips for organizing successful hybrid meetups with minimal overhead.\nIn September 2022, Mario Annau talked to the R Consortium about the role of the local financial industry in the Robust Vienna R Community. Recently, the R Consortium reached out to Mario for a detailed discussion about the use of R in the finance and pharmaceutical industries in Vienna. Mario shared his insights regarding the latest and upcoming trends in using R in these sectors and tips for organizing successful hybrid meetups with minimal overhead.\nPlease share about your background and involvement with the RUGS group.\nI became interested in R during my university studies in computer science. I earned a bachelor’s degree in software engineering and a master’s in intelligent systems or computational intelligence. During my master’s studies, I began using R. I also found out that Kurt Hornik, was at a different university in Vienna and was also using R. Together with other R core developers, he created R with its package repository and many features. Although I am not a trained statistician, I became more involved in statistics and machine learning, which are closely related. I did my master’s thesis with Kurt Hornik.\nDuring my second thesis, I became increasingly involved with R, which led me to explore text mining and sentiment analysis with this language. This interest ultimately kick-started my career. I am proud to say that I am one of the few people who have truly benefited from using R in my professional life. Back then, using open source software in companies was uncommon, and many people preferred Matlab and other professional tools. People would often ask me who supported R and why it was free. However, I found that having this skill set was very beneficial.\nThe experience of using open source languages and technologies has been really helpful for me. Over the years, I have switched jobs and worked for different employers, but the knowledge I gained has always been useful in other settings and companies. Unlike bigger corporations, I never had to worry about buying licenses or running into budget issues. For example, Matlab is expensive, so it’s always a concern for some companies. But since I’ve had experience with open source technologies, I never had to deal with those issues.\nI learned about open source technologies during my university studies and discovered that they are free to use even in my professional career. This has been very helpful to me, and I am amazed at how far I have been able to go with it. Although R is not as widely used in the professional field as other languages, it has served me very well, and I am happy to be able to use it in my career. The Vienna R User Group allows me to bring it to the local R community.\nCan you share what the R community is like in Vienna?\nIt’s evident that the industry has started accepting open source, including R. I work primarily in the financial sector and pharma, which are industries where R is widely used. R is also a strong contender, alongside Python, in these fields.\nThe acceptance of using R in production environments is increasing, but some companies still view it as just a tool for creating graphs and nothing else. Despite this perception, I still use R a lot in production, and it works well. However, some wrong assumptions about using R in production are still present, which makes it challenging to deploy. Since R is a dynamic language and not compiled, some issues need to be addressed. Python also faces similar issues but is seen as easier to use. Although it is possible to use R in production, it depends on the department, as IT departments tend to be less accepting of R compared to the statistics or math departments.\nThere are always discussions regarding the best programming language to use in various industries. However, with the emergence of cloud technology and containerization, it is possible to package everything up into a nice container, making it work well. R is an industry-standard, and many risk departments in the financial industry use it to develop core models. Although people may complain and want to learn other languages like Python, R is still widely used.\nWhat industry are you currently in? How do you use R in your work?\nWe apply our expertise to various industries, including finance and pharmaceuticals. As external consultants, we assist clients in setting up proper procedures and creating useful dashboards and applications. We often work with existing R codes or other resources to improve their functionality and create helpful add-ons. Our focus is on maximizing existing knowledge and leveraging the existing code base. Our services often involve package creation, documentation, containerization, and dashboard framework development. We tailor our approach to suit the unique needs of each project.\nNowadays, we are developing more and more frameworks to set up departments in the industry with the right infrastructure. This includes developing R packages and connecting everything with the rest of the organization. Initially, we started by creating small models and calculations, but it gradually became more significant, and now we are mostly helping entire departments set themselves up in the right way and make the most of R and their people.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nThe trend of containerization has been around for some time now, where you package your app or REST API dashboard in a Docker container and deploy it in an environment such as the cloud. This trend is prevalent in both R and Python. As for upcoming trends, I am excited about the web assembly initiative, which makes it possible to run a Shiny app within a browser without a server. This initiative has great potential and can bring R to people who are unaware of its existence. It is exciting to see R bring data and statistics to life in various applications. I hope that this initiative can go further and reach more people.\nRegarding the deployment of our Shiny projects, it is always surprising to see how complicated it can be depending on the environment. This tool aims to make the deployment process easier and accessible to a broader audience. Currently, the loading times are still too long, but these issues can be optimized with some improvements.\nI have noticed another trend in certain industries, which is the increasing demand for regulatory compliance. For example, the FDA regulates the pharmaceutical industry, while finance has its own regulatory authorities. This trend encompasses ensuring that packages and codes are properly regulated and reviewed. I am seeing this trend in both the finance and pharmaceutical industries.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nWe have a GitHub page and a Meetup page, which is our setup. We tried to ensure that everything we present is also available, such as code and slides on GitHub, so that it’s easy for everyone to access. However, finding speakers and rooms is always a challenge. The good news is that finding rooms is getting easier than finding speakers. Some companies are always willing to host an hour-long meetup and have some online meetings. We are a group of smart people who like to talk about interesting things.\nThe most challenging aspect is locating speakers, particularly female speakers. I am pleased that initiatives like R Ladies provide a dedicated space for women in this field. Generally, finding speakers is a difficult task for us, and we rely heavily on referrals from friends and acquaintances. However, as a community, we always work to overcome this obstacle.\nIt’s important to always have a stream of topics and speakers available for events, but this can be difficult, especially when finding female speakers. Creating a welcoming and safe community where everyone feels comfortable sharing their knowledge is essential. Organizing these events is worth the effort, as you get to meet many like-minded people in your industry, and it can help you professionally. You’ll learn a lot and get to know people in your field, which is always an advantage. So, if you’re thinking of organizing meetups, just do it, and you’ll see how far it can take you.\nBefore COVID, our meetings were always in person. We tried recording them, but it didn’t work out. During COVID, we had to switch to online meetings only, and afterward, we started having hybrid meetings. I don’t find online meetups very satisfying because you miss out on the networking and socializing aspects. Going out to a bar or a pub and talking with people is an important part of the experience for me. That’s why I still prefer in-person meetups. However, thanks to COVID, things have changed, and I think we can now find more ways to combine the benefits of in-person and online meetings.\nYou are creating a lot of content that some people miss due to various reasons. There may be people who wanted to attend but couldn’t due to certain difficulties. To address this issue, we have now set up hybrid meetings, which require more equipment, like microphones and cameras. Most of the time, I have to carry this equipment. However, it makes sense to have this kind of content and share it with your community. Sometimes, speakers may not be happy about it, but it’s rare. Most of the time, it makes sense to do it hybrid.\nAs for the hybrid, I can say that recording can be difficult, and it rarely works out perfectly the first time around. However, I would recommend setting up a system that reduces your overhead for platforms like YouTube Live. Strive for minimal overhead to make your life easier. Don’t make the mistake we did once when Hadley Wickham was in town and we had to do a lot of editing and cutting because the recording wasn’t perfect. Instead, aim for a setup that works seamlessly and consider doing live streams instead.\nThe most practical way to share content with YouTube is to stream it live. This automatically uploads the content online, eliminating the need for further actions. As a result, when users visit the platform, the content is readily available for viewing.\nI have realized that delaying uploading our content to perform tasks such as editing and rearrangement is a time-consuming process that‌ does not offer significant benefits. Therefore, we are working towards improving our setup by acquiring high-quality microphones and mobile cameras to make the process more efficient and provide our viewers with a seamless experience.\nI am often amazed by the gratitude expressed by individuals around the world who get the opportunity to participate. Without the necessary infrastructure, achieving this would be impossible. However, some members of my community believe that it requires an excessive amount of work.\nIn light of the current global situation, people are less likely to travel or move to different cities for work or other purposes. Therefore, hybrid events are the most suitable way to improve accessibility and encourage community participation. Event organizers should consider using hybrid formats to provide a more inclusive and efficient experience for all participants." }, { - "objectID": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html#about-isc-funded-projects", - "href": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html#about-isc-funded-projects", - "title": "Empowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative", - "section": "About ISC Funded Projects", - "text": "About ISC Funded Projects\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nhttps://r-consortium.org/all-projects/callforproposals.html" + "objectID": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html#how-do-i-join", + "href": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html#how-do-i-join", + "title": "Navigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html", - "href": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html", - "title": "Bridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students", + "objectID": "posts/R-Medicine-is-coming-June-10-14-2024-See-Top-Five-R-Medicine-Talks-from-Previous-Years/index.html", + "href": "posts/R-Medicine-is-coming-June-10-14-2024-See-Top-Five-R-Medicine-Talks-from-Previous-Years/index.html", + "title": "R/Medicine is coming June 10-14, 2024 – See Top Five R Medicine Talks from Previous Years", "section": "", - "text": "Umar Isah Adam, the founder and organizer of the R User Group Kano, Nigeria, spoke with the R Consortium during the pandemic about his efforts to engage the next generation of students in the R community. Recently, the R Consortium followed up with Umar to discuss the group’s progress over the past few years. He discussed the increasing acceptance and interest in R within academia. The user group is working with various colleges in Kano state to introduce R to students and teach them the fundamentals. Umar also shared his experience using R for managerial tasks related to student data. He hopes to persuade college management to use R for data handling instead of the current manual processes.\nPlease share your background and involvement with the RUGS group.\nMy name is Umar Isah Adam, and I’m from Kano State, Nigeria. I studied mathematics at the Federal University Dutse, Jigawa State. During my studies, I became interested in statistics and technology. One of my lecturers mentioned R as a statistical analysis tool, which piqued my interest. I learned it by researching online and watching videos. Later, a friend introduced me to R User Groups. I found that I was interested in R and noticed there wasn’t a group in Kano State, so I applied to start a chapter there, and it was approved.\nCan you share what the R community is like in Kano, Nigeria?\nThe use of R is relatively new in Kano State. Most academics in the area use SPSS in their work. It makes it challenging for R to gain traction in this environment. Despite the challenges, we have been making progress with the support of our user group. Currently, I work as an assistant lecturer at a college in Kano State. I recently organized a well-attended seminar for lecturers and students at the Kano State College of Education and Preliminary Studies. I also posted a video of the workshop on YouTube and have received requests for more information.\nThere’s room for improvement. We’ve received requests from academic institutions to host events or provide information about the power of R. However, we cannot do so now due to the nature of my work and inadequate funding. However, we plan to start a 10-week training session soon. It will likely be free, as we are collaborating with the Kano State College of Education and Preliminary Studies to organize it. R isn’t very popular here, and more than 70% of academicians need help understanding what it is and how to use it effectively. However, those introduced to it have shown a high interest in learning and utilizing it.\nWe aim to introduce R to the academic community, and after this, we plan to move on to another college and launch a new program. In summary, R is not widely known in our society, but we are progressing. There has been an increase in the acceptance of R and a growing interest from different people in academia, particularly in R. Many are interested. Still, there needs to be more awareness about it. Most people need to learn what R is and how to use it. Therefore, most of our upcoming programs will focus on introducing the R language.\nAdditionally, there is an issue with student access. Most of our students don’t have personal computers and can only access them on campus, usually at the ICT department. This lack of access also affects student engagement. However, among academics and lecturers in our colleges, there is growing interest in R.\nDo you host in-person or online events? How do you make your events inclusive?\nIt’s important to remember that online events became essential during the pandemic. However, due to internet connectivity issues, we avoid online meetings or events most of the time. As a result, our sessions are usually held offline. We have been hosting events within colleges and other institutions to make them easily accessible to students and academics. It is also more cost-effective and popular than hosting in private locations. Advertising these events has proven effective, as interested individuals are usually willing to attend when they see the advertisement.\nWe attempted to transfer between colleges, such as those owned by the state government. The majority of the data and processes are research-based. Therefore, we strive to incorporate more R programming aligned with academic requirements. We aim to limit topics to the use of R in academia to ensure that attendees feel more connected and can see the practical applications of using R. For instance, compared to using SPSS, where one often needs to use code or convert data into another format, with R, one can easily import data into the working environment and manipulate it as needed.\nPlease share about a project you are currently working on or have worked on using the R language. What is the goal/reason, result, or anything interesting, especially related to your industry?\nI usually demonstrate to people around me, including the school management, how easy it is to use R. For example, we need help with the examination office potentially losing some of their data. However, they have a backup on an external drive. I am importing the data from the old template to the new one in Excel format. I am also working on calculating the student results and offloading them into the new portal we have developed. Doing this job manually might take a month, but if I successfully create this program, it will complete the job in two to three days. It will demonstrate to the school management the importance and impact of using R.\nI am proposing to the college management to introduce a certified course of study on “Introduction to R” within the ICT department. Showcasing how this programming language can impact the working environment will help them understand the need for this course. Many students rely on fundamental analyses using questionnaires, frequency, and percentage without exploring visualization techniques. As a supervisor, I encourage using R for data analysis in student projects, as it provides a more comprehensive approach. However, many students need access to computers. Therefore, by offering this course, we can equip them with valuable skills and knowledge to benefit their future careers." + "text": "What to get a feel for the kind of content will be available at R/Medicine 2024? We’re spotlighting the most engaging and educational sessions from past R Medicine Virtual Conferences. Whether you’re a healthcare professional, a data scientist, or simply curious about the intersection of healthcare and technology, these selected talks offer a wealth of knowledge and innovation using the R programming language. Dive into these sessions to enhance your understanding and skills in medical data science.\n\n🔗 Register for the R Medicine 2024 Virtual Conference here!\n\n\n1. GitHub Copilot in Rstudio, It’s Finally Here! – R Medicine Virtual Conference 2023\nThis session introduces GitHub Copilot for RStudio, a highly anticipated tool that enhances coding efficiency and innovation in medical research. Watch as experts demonstrate its capabilities and potential impact on healthcare data analysis.\n\n\n\n\n2. Analyzing Geospatial Data in R (Sherrie Xie) – R/Medicine 2022 Virtual Conference\nFeaturing Sherrie Xie, this presentation explores the applications of geospatial data analysis within the healthcare sector using R. Gain insights into the importance of spatial data in understanding health trends and outcomes.\n\n\n\n\n3. R/Medicine 101: Intro to R for Clinical Data (Stephan Kadauke, Joe Rudolf, Patrick Mathias) – R/Medicine 2022\nThis introductory session is perfect for those new to using R in a clinical setting. The speakers guide you through the basics and demonstrate how R can revolutionize medical research and patient care.\n\n\n\n\n4. Introduction to R for Medical DataTidy Spreadsheets in Medical Research – R/Medicine 2021\nUMich Prof and {medicaldata} author Peter Higgins will cover best practices for using medical data in spreadsheets like Excel and Google Sheets.\n\n\n\n\n5. Multistate Data Using the {survival} Package – R/Medicine 2021\nExplore the use of the {survival} package in R for analyzing multistate data. Discover the methods and models that are shaping the future of survival analysis in medical research.\n\n\nEngage and Learn More!\nEach of these sessions provides unique insights and practical tools for harnessing the power of R in medical research and healthcare analytics. Whether you are watching these for the first time or revisiting them, each video promises a deep dive into the capabilities of R that are driving advancements in the field.\n📢 Mark Your Calendars! The R Medicine Conference for this year is scheduled for June 10-14. Register now to secure your spot and connect with a community of like-minded professionals!\n\n\n🔗 Register for the R Medicine 2024 Virtual Conference here!\nRemember to subscribe to the R Medicine channel for more updates and upcoming conference information. Enhance your skills in medical data science today!" }, { - "objectID": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html#how-do-i-join", - "href": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html#how-do-i-join", - "title": "Bridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/the-r-consortium-2023-a-year-of-growth-and-innovation/index.html", + "href": "posts/the-r-consortium-2023-a-year-of-growth-and-innovation/index.html", + "title": "The R Consortium 2023: A Year of Growth and Innovation", + "section": "", + "text": "Excerpted from the Annual Report\n\nAccess the annual report here!\nLetter from the Chair — Mehar Pratap Singh, Chairman\nWelcome to the 2023 Annual Report of the R Consortium. This document reflects a year of significant growth, innovation, and community engagement within and beyond the R ecosystem. As we present the accomplishments and milestones of the past year, we also set our sights forward, laying out the path for an even more collaborative and impactful future.  \nThe R Consortium serves as a central hub for the R community, bringing together industry leaders, academic institutions, and individual contributors to foster the development and proliferation of the R language. Our mission is to support the R community through funding, infrastructure improvement, community initiatives, and global outreach.  \nIn 2023, the R Consortium played a pivotal role in shaping the development of the R ecosystem. Through monetary grants, nearly $200,000 dollars to develop R packages and other technical infrastructure, through fostering industry wide collaborative working groups, and by supporting R-Ladies, R user groups, and several important industry conferences, including Latin-R, New York R, and Bioconductor conferences. This report highlights some of these achievements, showcasing the collective effort of our members and the broader community.  \nRecognizing the dynamic nature of data science technologies and the evolving needs of industry, we also recognize the responsibility of the R Consortium to help set a vision for the evolution of the R ecosystem. As you read through this report, we hope you’ll appreciate the strides we’ve made together and feel inspired by the potential of what we can achieve in the future. The R Consortium is more than just an organization: it’s a vibrant community of innovators, problem-solvers, and thought leaders. Together, we are shaping a future where the power of R is accessible to all and continues to drive progress across industries worldwide.   \nThank you for your continued support and dedication to the R Consortium and the wider R community. \n\n\nAccess the annual report here!" }, { - "objectID": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html", - "href": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html", - "title": "Gergely Daróczi’s Journey: Empowering R Users in Hungary", + "objectID": "posts/r-ladies-cotonou-a-community/index.html", + "href": "posts/r-ladies-cotonou-a-community/index.html", + "title": "R-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women", "section": "", - "text": "Gergely Daróczi, the founder and organizer of the Budapest Users of R Network, updated the R Consortium about the group’s recent activities. Last year, Gergely discussed the group’s inception, and the challenges faced by the group during the pandemic. The group has now resumed in-person meetings, followed by networking sessions. The recent events organized by the group have focused on bioinformatics, large language models, and mathematical modeling.\nPlease share about your background and involvement with the RUGS group.\nI have a background in social sciences, and it was during one of my university classes 20 years ago that I was introduced to the R language. We had to use R to run simulations related to the chaotic behavior of the Hungarian potato market. I found R more enjoyable and versatile than other GUI tools like IBM’s SPSS and started using it for other projects as well. Later, I even developed some additional packages for R.\nI have been working with R for almost 20 years now. Despite my academic background in social sciences, I have worked in various industries, such as ad tech, fintech, and health tech, for the past 10 years.\nIn 2013, I attended my first useR! conference in Albacete, Spain, and it was a great experience to meet fellow R users from around the world. At the conference, I met Szilard Pafka, a Hungarian living in LA and organizer of the Los Angeles R User group. He suggested that I start an R User group in Hungary. After returning home, I decided to give it a shot, and we held our first meeting at the end of the summer of 2013. In a university room, it felt like there were only a dozen R users from academia. However, a lot has changed since then, as we now have almost 2,000 members in the local R User group, which exceeded my original expectations for such a small country like Hungary. It has been an interesting and great experience.\nIn Hungary, the community’s growth began slowly, with only 20 to 30 members in the first few years. However, it gradually increased over time. The community also hosted some famous personalities such as Romain Francois, Matt Dowle, and Hadley Wickham, which further accelerated its growth. Additionally, the community organized the first satRday and second ERUM conference, which provided a platform for networking and knowledge sharing, further strengthening the community.\nHow has the group been doing since our last conversation?\nAfter COVID, restarting the meetups was very challenging. We didn’t organize any virtual events because the main benefit of meetups was meeting in person, having face-to-face conversations, and getting to know each other. Therefore, we waited until the quarantine was over and it was safe to meet in person. We started slowly, organizing only two events per year with around 30 to 70 attendees, which was much lower than before COVID-19. However, it has been great to reconnect with old friends and make new ones.\nRecently, we have been focusing on bioinformatics and I was introduced to a local company that offered help with reaching out to speakers. Speakers drive these community meetings by bringing in a topic for discussion and talk, which we continue to discuss later on. Our past few events have focused on life sciences and have followed a lightning talk format, where we had around five 15-minute talks at each event. The topics were diverse, covering life sciences, some with LLMs involved, others focused on highly advanced math for modeling. We also had shiny applications that showed the biodiversity of forests in Hungary and some open-source tools besides R.\nAny techniques you recommend using for planning for or during the event?\nI can only offer subjective experiences on the matter, but I have witnessed the success of both virtual and in-person communities. However, our focus is on providing an exceptional in-person experience. To achieve this, we search for a central venue that is easily accessible for most of our members. This can be challenging, even in Hungary, a small country, as it can be difficult for members from other cities to travel to the capital for meetups. Nevertheless, we do our best to find a central venue, such as a university or an industry partner who can offer a space for talks and a networking opportunity afterward.\nIt is important to have a room with plenty of chairs and a larger area for people to gather after the talks. We can provide soft drinks, beer, or wine along with some pizzas and have a chat for an hour or two after the talk. The venue is a crucial factor. It’s also important to have speakers who are interested in the community so that they will come to learn as well. It’s great to have speakers with interesting topics, but the most important thing for me is networking. After the talks, coming together and getting to know others, learning about their struggles, and maybe sharing some tips in person with each other, becoming friends, or learning about opportunities in other industries. Networking and facilitating connections are crucial tasks for R user group organizers.\nWhat trends do you currently see in R language?\nFive years ago, machine learning models were a hot topic, and everyone discussed different implementations of GBM. However, things have changed, and nowadays, large language models (LLM) rule over all the topics. LLMs are often implemented in languages other than R, making it difficult to train them from R. Despite this, there are still many use cases for LLMs, even in life sciences and health tech. However, caution must be taken when using AI and LLMs in these fields. Recently, at two bioinformatics events, some nice use cases of LLMs were shared with the audience. This has attracted new members interested in learning how to use AI or LLMs, which can be as simple as doing some API integrations in R, such as calling the chatGPT API to generate text or images.\nI’m excited that COVID restrictions are easing up and meetups are returning to normal. I can’t wait for the first in-person useR! conference in Salzburg in a few months. I highly recommend that anyone who can travel to Salzburg in July join us. The city has excellent train connections to European cities, so I hope many people from Europe can make it. I’m looking forward to attending an in-person useR! conference again.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nCurrently, I’m focusing on the ETL pipeline of the Spare Cores project, collecting information on cloud compute resources, which will soon have the R bindings as well. In the past, I’ve been working on R packages related to reporting (e.g. “pander”) and using R in production (e.g. “logger,” “dbr” or “boto3”). Recently, I enjoyed integrating APIs and frameworks from other programming languages, such as Python (kudos to the reticulate team!), in R." + "text": "Nadejda Sero, the founder of the R Ladies Cotonou chapter, shared with the R Consortium her experiences learning R, the challenges of running an R community in a developing country, and her plans for 2024. She also emphasized the importance of considering the realities of the local R community when organizing an R User Group (RUG).\nPlease share about your background and involvement with the RUGS group.\nMy name is Nadejda Sero, and I am a plant population and theoretical ecologist. I have a Bachelor of Science in Forestry and Natural Resources Management and a Master of Science in Biostatistics from the University of Abomey-Calavi (Benin, West Africa). I discovered R during my Master’s studies in 2015. From the first coding class, I found R exciting and fun. However, as assignments became more challenging, I grew somewhat frustrated due to my lack of prior experience with a programming language.\nSo, I jumped on Twitter (current X). I tweeted, “The most exciting thing I ever did is learning how to code in R!” The tweet caught the attention of members of the R Ladies global team. They asked if I was interested in spreading #rstats love with the women’s community in Benin. I was thrilled by the opportunity and thus began my journey with R-Ladies Global.\nThe early days were challenging due to the novelty of the experience. I did not know much about community building and social events organization. I started learning about the R-Ladies community and available resources. The most significant work was adjusting the resources/tools used by other chapters to fit my realities in Benin. My country, a small French-speaking developing African country, had poor internet access and few organizations focused on gender minorities. (We are doing slightly better now.) On top of that, I often needed to translate some materials into French for the chapter.\nAs I struggled to make headway, the R-Ladies team launched a mentoring program for organizers. I was fortunate enough to participate in the pilot mentorship. The program helped me understand how to identify, adjust, and use the most effective tools for R-Ladies Cotonou. I also gained confidence as an organizer and with community work. With my fantastic mentor’s help, I revived the local chapter of R-Ladies in Cotonou, Benin. I later joined her in the R-Ladies Global team to manage the mentoring program. You can read more about my mentoring experience on the R-Ladies Global blog.\nHappy members of R-Ladies Cotonou sharing some pastries after the presentation. At our first official meetup, the attendees discovered and learned everything about R-Ladies Global and R-Ladies Cotonou.\nI am grateful for the opportunity to have been a part of the R-Ladies community these last six years. I also discovered other fantastic groups like AfricaR. I am particularly proud of the journey with R-Ladies Cotonou. I am also thankful to the people who support us and contribute to keeping R-Ladies Cotonou alive.\nCan you share what the R community is like in Benin?\nR has been commonly used in academia and more moderately in the professional world over the past 2-3 years. For example, I worked with people from different areas of science. I worked in a laboratory where people came to us needing data analysts or biostatisticians. We always used R for such tasks, and many registered in R training sessions. The participants of these sessions also came from the professional world and public health. I have been out of the country for a while now, but the R community is booming. More people are interested in learning and using R in different settings and fields. I recently heard that people are fascinated with R for machine learning and artificial intelligence. It is exciting to see that people are integrating R into various fields. There are also a few more training opportunities for R enthusiasts.\nCan you tell us about your plans for the R Ladies Cotonou for the new year?\nMore meetups from our Beninese community, other R-Ladies chapters, and allies.\nWe are planning a series of meetups that feature students from the training “Science des Données au Féminin en Afrique,” a data science with R program for francophone women organized by the Benin chapter of OWSD (Organization for Women in Science for the Developing World). We have three initial speakers for the series: the student who won the excellence prize and the two grantees from R-Ladies Cotonou. The program is an online training requiring good internet, which is unfortunately expensive and unreliable. If you want good internet, you must pay the price.\nR-Ladies Cotonou supported two students (from Benin and Burkina Faso) by creating a small “internet access” grant using the R Consortium grant received in 2020.\nThe meetup speaker is taking us through a review of the most practical methods of importing and exporting datasets in R. The attendees are listening and taking notes.\nThis next series of meetups will focus on R tutorials with a bonus. The speakers will additionally share their stories embracing R through the training. The first speaker, Jospine Doris Abadassi, will discuss dashboard creation with Shiny and its potential applications to public health. I hope more folks from the training join the series to share their favorite R tools.\nI believe these meetups will assist in expanding not only the R-Ladies but the entire R community. I particularly enjoy it when local people share what they have learned. It further motivates the participants to be bold with R.\nAbout “Science des Données au Féminin en Afrique“, it is the first time I know that a data science training is free for specifically African women from French-speaking areas. Initiated by Dr. Bernice Bancole and Prof. Thierry Warin, the program trains 100 African francophone women in data science using R, emphasizing projects focused on societal problem resolution. The training concluded its first batch and is now recruiting for the second round. So, the community has expanded, and a few more people are using R. I appreciate that the training focuses on helping people develop projects that address societal issues. I believe that it enriches the community.\nAs I said in my last interview with the R consortium, “In some parts of the world, before expecting to find R users or a vivid R community, you first need to create favorable conditions for their birth – teach people what R is and its usefulness in professional, academic, and even artistic life.” It is especially true in Benin, whose official language is French. English is at least a third language for the average multilingual Beninese. Many people are uncomfortable or restrained in using R since most R materials are in English. I hope this OWSD Benin training receives all the contributions to keep running long-term. You can reach the leading team at owsd.benin@gmail.com.\nOur other plan is to collaborate with other R-Ladies chapters and RUGS who speak French. If you speak French and want to teach us something, please email cotonou@rladies.org.\nOtherwise, I will be working on welcoming and assisting new organizers for our chapter. So, for anyone interested, please email cotonou@rladies.org.\nAre you guys currently hosting your events online or in-person? And what are your plans for hosting events in 2024?\nWe used to hold in-person events when we started. Then, the COVID-19 pandemic hit, and we had to decide whether to hold events online. Organizing online events became challenging due to Cotonou’s lack of reliable internet access or expensive packages. As a result, we only held one online event with poor attendance. We took a long break from our activities.\nGoing forward, our events will be hybrid, a mix of in-person and online events. In-person events will allow attendees to use the existing infrastructure of computers and internet access of our allies. It also offers an opportunity to interact with participants. Therefore, I am working with people in Cotonou to identify locations with consistent internet access where attendees can go to attend the meetups. Online events will be necessary to accommodate speakers from outside of the country. It will be open to attendees unable to make it in person.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nThe techniques and tools should depend on the realities of the community. What language is comfortable for attendees? What meeting modality, online or in person, works best for participants?\nAs mentioned earlier, I was inexperienced, and organizing a chapter was daunting. My mentoring experience shifted my perspective. I realized that I needed to adjust many available resources/tools. Organizing meetups became easier as I integrated all these factors.\nFor example, our chapter prioritizes other communication and advertisement tools like regular emails and WhatsApp. The group is mildly active on social media, where the R community is alive (X/Twitter, Mastodon). It is easier to have a WhatsApp group to share information due to its popularity within our community. We recently created an Instagram account and will get LinkedIn and Facebook pages (with more co-organizers). I would love a website to centralize everything related to R-Ladies Cotonou. Using emails is an adjustment to Meetup, which is unpopular in Benin. Getting sponsors or partners and providing a few small grants for good internet would help tremendously our future online events.\nAdjusting helps us to reach people where they are. It is imperative to consider the community, its realities, and its needs. I often asked our meetup participants their expectations, “What do you anticipate from us?” “What would you like to see in the future?” Then, I take notes. Also, we have Google Forms to collect comments, suggestions, potential speakers, contributors, and preferred meeting times. It is crucial to encourage people to participate, especially gender minorities less accustomed to such gatherings.\nI have also attempted to make the meetups more welcoming and friendly in recent years. I always had some food/snacks and drinks available (thanks to friends and allies). It helps make people feel at ease and focus better. I hope the tradition continues for in-person meetups. It is valuable to make the meetups welcoming and friendly. How people feel is essential. If they come and feel like it is a regular lecture or course, they may decide to skip it. But, if they come to the meetup and learn while having fun, or at the very least, enjoy it a little, it benefits everyone.\nThese are some of the key aspects to consider when organizing a meetup. It is critical to consider the people since you are doing it for them. Also, make sure you have support and many co-organizers if possible.\nAll materials live on our GitHub page for people who can’t attend physical events. Another solution would be recording and uploading the session on the R-Ladies Global YouTube or our channel.\nWhat industry are you currently in? How do you use R in your work?\nI am now a Ph.D. student in Ecology and Evolutionary Biology at the University of Tennessee in Knoxville.\nR has no longer been my first programming language since I started graduate school. I still use R for data tidying data analysis but less extensively. I worked a lot with R as a master’s student and Biostatistician. It was constant learning and growth as a programmer. I had a lot of fun writing my first local package. However, I now work more with mathematical software like Maple and Mathematica. I wish R were as smooth and intuitive as this software for mathematical modeling. I like translating Maple code to R code, especially when I need to make visualizations.\nI am addicted to ggplot2 for graphs. I love learning new programming languages but am really attached to R (it’s a 9-year-old relationship now). I developed many skills while programming in R. R helped me become intuitive, a fast learner, and sharp with other programming languages.\nMy most recent project that utilized R, from beginning to end, was a project in my current lab on the evolutionary strategies of plants in stochastic environments. We used R for demographic data tidying and wrangling. Data analysis was a mix of statistical and mathematical models. It was a good occasion to practice writing functions and use new packages. I enjoy writing functions for any task to automate repetitive tasks, which reduces the need for copying and pasting code. I also learned more subtleties in analyzing demographic data from my advisor and colleagues who have used R longer." }, { - "objectID": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html#how-do-i-join", - "href": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html#how-do-i-join", - "title": "Gergely Daróczi’s Journey: Empowering R Users in Hungary", + "objectID": "posts/r-ladies-cotonou-a-community/index.html#how-do-i-join", + "href": "posts/r-ladies-cotonou-a-community/index.html#how-do-i-join", + "title": "R-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women", "section": "How do I Join?", "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/r4socialscience-empowering-social-science-research/index.html", - "href": "posts/r4socialscience-empowering-social-science-research/index.html", - "title": "R4SocialScience: Empowering Social Science Research with R in India", + "objectID": "posts/the-cleveland-r-user-groups-journey-through-pandemic-adaptations-and-baseball-analytics-r-consortium/index.html", + "href": "posts/the-cleveland-r-user-groups-journey-through-pandemic-adaptations-and-baseball-analytics-r-consortium/index.html", + "title": "The Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics", "section": "", - "text": "Dr. Mohit Garg, organizer of the R4SocialScience group in Delhi, India recently talked to the R Consortium about his experience of starting an R user group. The R4SocialScience group aims to bridge the gap between social science research and data analysis, offering support and training to academics, researchers, and industry professionals. Dr. Garg shares his experiences, the growth of the R community in India, and his plans for expanding R’s reach.\nPlease share about your background and involvement with the RUGS group.\nI’m currently working as an assistant librarian at the Indian Institute of Technology, Delhi, one of the premier institutions in India.  My academic background includes a BTech in Information Technology from Guru Gobind Singh Indraprastha University followed by an MS in Librarian Information Science from the Indian Statistical Institute, an institution dedicated to statistics in India started by the late Professor P.C. Mahanobis. After that, I completed my PhD in Library and Information Science from IGNOU, New Delhi.\nMy interest in R began in 2013 when I started my MS at the Indian Statistical Institute.  Since then, I have taken various courses as part of my MS program and some online courses. I became interested in R due to its open source nature and the free availability of packages for all kinds of analysis. Then, I started promoting R in the academic community. However, in 2013, there was little interest in R because the prevalent approach in India was more focused on using commercial software for data analysis.  However, in the past few years, there has been an increasing interest in R, with many workshops and government-funded events dedicated to it.\nI have been providing R training to professors, teachers, and research scholars, and I have also worked on web-based development using Shiny packages. Furthermore, we have developed a web dashboard to visualize real-time research productivity data obtained from sources like Scopus through API. Recently, we completed a 12-week MOOC course on NPTEL SWAYAM platform with a focus solely on R. The course was quite popular, with 2584 learners from India joining, and 515 learners registering for the final examination. Although the course was free, participants had the option to pay for certification.\nCan you share what the R community is like in India?\nI have been involved in the academic profession since 2016 and have been giving lectures and providing resource points at various institutions. I believe that there is a need to build a community focused on social sciences, especially for those who may have a limited understanding of mathematics, and statistics. The idea is to create a specific community related to social science, not just in India, but also in collaboration with other institutions. The community will cater to three main groups: those who are proficient in coding and development of R packages, those who are familiar with basic R but need further guidance, and those who are completely new to R.\nThe community aims to provide support for those interested in social science and to make R more accessible by offering packages related to social science, basic R tutorials. One specific package gaining popularity in academia is “biblo shiny bibliometrics,” which facilitates scientific productivity mapping using R.\nWe want to emphasize that R is not just a programming language, but a software for data analysis, to encourage more people to explore its potential. While both R and Python are interpreted languages, we aim to dispel the fear of programming and demonstrate how these languages can be used effectively. Although Python appears to be more widely used in the industry, there is still a growing interest in R.\nWhat are your plans for the group going forward?\nI have been teaching R for more than 10 years, and I found that researchers are interested in using R. I have identified three potential co-organizers from different regions in India to make a team of four people. We have already received a grant, and we plan to conduct training sessions in different locations across India.\nI am focusing on a “train the trainer” model, where I aim to train individuals who can then carry out training sessions in their respective regions. India has over 50,000 colleges and around 1,200 universities, all involved in significant research and analysis activities. We also aim to have dedicated R trainers in all districts in India by 2026.\nOur approach involves dividing the country into five zones, followed by state-wise and district-wise planning. We are not heavily reliant on industry support, as our activities are primarily related to academia and research.\nWe plan to charge a nominal registration fee, which would cover expenses such as food and refreshment. We are hoping to minimize travel expenses, as they can be quite costly. But we will explore some way to fund the travel and accommodation expenses. We have hosted a one day workshop on “Doing Research using R” at Galgotias University.\nI am currently focusing on building a community and providing training sessions. I have noticed that online sessions may not be as effective as I had hoped, as participants seem to encounter many problems. Therefore, I am considering conducting more in-person workshops, which I believe will help popularize the training sessions. Additionally, I aim to develop specialized packages for social science and build a dedicated team. I am optimistic about these plans. During a recent workshop, I noticed that many participants preferred simple tools for data analysis. I intend to introduce such tools to make the training more accessible and user-friendly for participants. This is my vision for the community.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nWe have developed a platform utilizing the shiny and other text mining packages. This platform is still in the testing phase. The platform allows real-time data fetching from the Scopus API.\nFor example, if I search for a faculty member, it will display the publication data such as the number of publications, H-index, citations, types of publications, sources of publication, and annual publication distribution. We can also download this data.\nWe have also developed a word cloud based on the titles of the publications for each faculty member, processed using the TM package. This helps to infer the expertise of the professors. Furthermore, we have included a feature for identifying the H-classic, which is related to the H-index.  This platform is quite useful and efficient, especially for academic institutions. We now have the capability to download data from a specific date range as an Excel file. The data includes publication dates and the number of citations.\nWe’re in the process of creating a full dashboard for universities or institutions. We’ve also conducted a pilot study for other institutions. We are also considering publishing this work as a research paper to increase its visibility." + "text": "Last year, R Consortium talked to John Blischak and Tim Hoolihan of the Cleveland R User Group about their regular structured and casual virtual meetups during the pandemic. Recently, Alec Wong, another co-organizer of the Cleveland R User Group, updated the R Consortium about how the group provides a networking platform for a small but vibrant local R community. Alec shared details of a recent event from the group regarding the use of R for analyzing baseball data. He also discussed some tools for keeping the group inclusive and improving communication among group members.\n\n\n\nPlease share about your background and involvement with the RUGS group.\nI completed my Bachelor of Science degree in Fisheries and Wildlife from the University of Nebraska-Lincoln in 2013, and my Master of Science degree in Statistical Ecology from Cornell University in late 2018. During my graduate program, I gained extensive experience using R, which is the de facto language of the ecological sciences. I discovered a passion for the language, as it is extremely intuitive and pleasant to work with.\nAfter completing my program in 2018, I moved to Cleveland and immediately began attending the Cleveland R User Group in 2019, and have been a consistent member ever since. I eagerly look forward to each of our events.\nAfter completing my graduate program, I started working at Progressive Insurance. Working for a large organization like Progressive provides me with many diverse opportunities to make use of my extensive experience with R. I was happy to find a vibrant R community within the company, which allowed me to connect with other R users, share knowledge, and I enthusiastically offer one-on-one assistance to analysts from all over Progressive.\nStarting in 2022, I accepted the role of co-organizer of the Cleveland R User Group. As a co-organizer, I help with various tasks related to organizing events, such as the one we held last September. I am passionate about fostering the growth of these communities and helping to attract more individuals who enjoy using R.\nOur group events are currently being held in a hybrid format. When we manage to find space, we will meet in person, such as when we met to view the 2023 posit::conf in October–several members visited in person and watched and discussed videos from the conference. Most of our meetups continue to be virtual, including our Saturday morning coffee meetups, but we are actively searching for a more permanent physical space to accommodate our regular meetups.\nI am only one of several co-organizers of the Cleveland R user group. The other co-organizers include Tim Hoolihan from Centric Consulting, John Blischak who operates his consulting firm JDB Software Consulting, LLC, and Jim Hester, currently a Senior Software Engineer atNetflix. Their contributions are invaluable and the community benefits tremendously from their efforts.\nCan you share what the R community is like in Cleveland? \nI believe interest in R has been fairly steady over time in Cleveland since 2019. We have a handful of members who attend regularly, and typically each meeting one or two new attendees will introduce themselves.\nI would venture to say that R continues to be used frequently in academic settings in Cleveland, though I am ‌unfamiliar with the standards at local universities. At least two of our members belong to local universities and they use R in their curricula.\nAs for industry usage, many local companies, including Progressive use R. At Progressive, we have a small, but solid R community; although it is not as large as the Python community, I believe that the R community is more vibrant. This seems characteristic of R communities in varying contexts, as far as I’ve seen. Another Cleveland company, the Cleveland Guardians baseball team, makes use of R for data science. In September 2023 we were fortunate to invite one of their principal data scientists to speak to us about their methods and analyses. (More details below.)\nTypically, our attendance is local to the greater Cleveland area, but with virtual meetups, we’ve been able to host speakers and attendees from across the country; this was a silver lining of the pandemic. We also hold regular Saturday morning coffee and informal chat sessions, and it’s great to see fresh faces from outside Cleveland joining in.\nYou had a Meetup titled “How Major League Teams Use R to Analyze Baseball Data”, can you share more on the topic covered? Why this topic?\nOn September 27th, 2023, we invited Keith Woolner, principal data scientist at the Cleveland Guardians baseball team, to give a presentation to our group. This was our first in-person meetup after the pandemic, and Progressive generously sponsored our event, affording us a large presentation space, food, and A/V support. We entertained a mixed audience from the public as well as Progressive employees.\nKeith spoke to us about “How Major League Baseball Teams Use R to Analyze Baseball Data.” In an engaging session, he showcased several statistical methods used in sports analytics, the code used to produce these analyses, and visualizations of the data and statistical methods. Of particular interest to me was his analysis using a generalized additive model (GAM) to evaluate the relative performance of catchers’ ability to “frame” a catch; in other words, their ability to convince the umpire a strike occurred. The presentation held some relevance for everyone, whether they were interested in Cleveland baseball, statistics, or R, making it a terrific option for our first in-person presentation since January 2020. His presentation drove a lot of engagement both during and after the session.\n\n\n\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future? \nOne of our co-organizers, John Blischak, has created a slick website using GitHub Pages to showcase our group and used GitHub issue templates to create a process for speakers to submit talks. Additionally, the Cleveland R User group has posted recordings of our meetups to YouTube since 2017, increasing our visibility and accessibility. Many people at Progressive could not attend our September meetup and asked for the recording of our September 2023 meetup as soon as it was available.\nRecently, we have also created a Discord server, a platform similar to Slack. This was suggested by one of our members, Ken Wong, and it has been a great addition to our community. We have been growing the server organically since October of last year by marketing it to attendees who visit our events, particularly on the Saturday morning meetups. This has opened up an additional space for us to collaborate and share content asynchronously. Ken has done an excellent job of organizing the server and has added some automated processes that post from R blogs, journal articles, and tweets from high-profile R users. Overall, we are pleased with our progress and look forward to continuing to improve our initiatives.\n\nHow do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/r4socialscience-empowering-social-science-research/index.html#how-do-i-join", - "href": "posts/r4socialscience-empowering-social-science-research/index.html#how-do-i-join", - "title": "R4SocialScience: Empowering Social Science Research with R in India", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html", + "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html", + "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", + "section": "", + "text": "The R Consortium is excited to announce that, on September 20, 2024, the R Submissions Working Group successfully submitted its latest test submission package—featuring a WebAssembly component—through the FDA’s Electronic Common Technical Document (eCTD) gateway! This marks a significant milestone as the FDA Center for Drug Evaluation and Research (CDER) staff has officially received the submission package.\nStatistician Eric Nantz at pharmaceuticals company Eli Lilly in Indianapolis, Indiana, says that using WebAssembly “will minimize, from the reviewer’s perspective, many of the steps that they had to take to get the application running on their machines.”\nThe complete set of submission materials is available publicly on GitHub: R Consortium Submissions Pilot 4." }, { - "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html", - "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html", - "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", - "section": "", - "text": "The R Validation Hub next meeting is May 21st, 12:00 PM EST." + "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-pilot-4-project", + "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-pilot-4-project", + "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", + "section": "About the Pilot 4 Project", + "text": "About the Pilot 4 Project\nThe objective of the R Consortium R submission Pilot 4 Project is to explore the use of novel technologies such as Linux containers and WebAssembly to bundle a Shiny application into a self-contained package, facilitating a smoother process of both transferring and executing the application. The application was built using the source data sets and analyses contained in the R submission Pilot 1-3. To our knowledge, this is the first publicly available submission package that includes a WebAssembly component. We hope this submission package and what we have learned can serve as a good reference for future regulatory submission efforts. The WebAssembly technology compiles applications into a portable, consistent environment driven by a web browser, allowing agency reviewers to easily run and evaluate software without complex setups. The second half of the Pilot 4 Project (leveraging container technology to package a Shiny application) will be submitted as an additional package later this year. Additional agency feedback will be shared in future communications." }, { - "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here", - "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here", - "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", - "section": "Join the call here! ", - "text": "Join the call here! \nIn the dynamic field of pharmaceutical research, open source R packages offer incredible potential to innovate and enhance efficiency. The R Validation Hub is guiding the community building riskmetric and the riskassessment app. riskmetric is a framework to quantify an R package’s “risk of use” by assessing a number of meaningful metrics designed to evaluate package development best practices, code documentation, community engagement, and development sustainability. Together, the riskassessment app and the riskmetric package aim to provide some context for validation within regulated industries. \nThe benefits of utilizing open source tools in pharmaceutical projects are compelling. To address these issues and maximize their potential, join us at the R Validation Hub community meeting on May 21st at 12:00 PM EST. This gathering will focus on sharing best practices, troubleshooting common problems, and exploring innovative solutions together.\nEmbrace the opportunity to transform pharmaceutical research with us. Let’s innovate, collaborate, and overcome these hurdles together." + "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-r-submissions-working-group", + "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-r-submissions-working-group", + "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", + "section": "About the R Submissions Working Group", + "text": "About the R Submissions Working Group\nThe R Consortium R Submissions Working Group is focused on improving practices for R-based clinical trial regulatory submissions.\nHealth authority agencies from different countries require electronic submission of data, computer programs, and relevant documentation to bring an experimental clinical product to market. In the past, submissions have mainly been based on the SAS language.\nIn recent years, the use of open source languages, especially the R language, has become very popular in the pharmaceutical industry and research institutions. Although the health authorities accept submissions based on open source programming languages, sponsors may be hesitant to conduct submissions using open source languages due to a lack of working examples.\nTherefore, the R Submissions Working Group aims to provide R-based submission examples and identify potential gaps while submitting these example packages. All materials, including submission examples and communications, are publicly available on the R consortium GitHub page." }, { - "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here-1", - "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here-1", - "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", - "section": "Join the call here!", - "text": "Join the call here!" + "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#join-the-r-submissions-working-group", + "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#join-the-r-submissions-working-group", + "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", + "section": "Join the R Submissions Working Group", + "text": "Join the R Submissions Working Group\nThe R Submissions Working Group comprises members from over 10 pharmaceutical companies, as well as regulatory agencies. We are a collaborative community open to anyone interested in contributing to this important work. For more information, or to get involved, visitour website or contact us directly at director@r-consortium.org." }, { - "objectID": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html", - "href": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html", - "title": "Offa R Users Group: Empowering Data-Driven Education in Nigeria", - "section": "", - "text": "The R Consortium had a conversation with Anietie Edem Udokang, who is the founder and organizer of the Offa R Users Group (ORUG). He discussed the emerging local R community and the use of R for his research in time series analysis.\nThe Offa R Users Group has a Meetup coming up on March 26th, 2024, titled “Test for the Assumptions of Linear Regression Using R.” The group is also seeking individuals to serve as guest speakers for their online events.\nPlease share about your background and involvement with the RUGS group.\nMy name is Anietie Edem Udokang, and I am a chief lecturer at the Federal Polytechnic Offa. I hold a Master of Science degree in Statistics. It was during my postgraduate studies that my supervisor introduced me to R, which was around 2012. Since then, I’ve been using R and have discovered that it’s far superior to some of the other software programs I had previously used.\nI have found that interacting with others and utilizing specific features, such as the ability to download applications, has been incredibly beneficial to my analysis work. These special packages have helped me greatly, and I believe it is important to attach relevant packages when organizing data. This experience has made me passionate about using R for data analysis.\nEver since I began using R, I have had the privilege of engaging with a diverse group of individuals, including data scientists and software users. These interactions have led me to the realization that to continue growing and learning, it would be beneficial to establish a user group within our community. Initially, we called it the “Fedpofa R Users Group,” but later changed the name to “Offa R Users Group.” We have been organizing meetings, providing training, and engaging in other activities to keep the community vibrant.\nCan you share what the R community is like in Offa?\nR is not limited to academic use, but it is also used in industry. The reason for this is that polytechnics act as a bridge between the industry and academic institutions. If the students have a good grasp of how to use R, it means that industry will be directly or indirectly affected. Consultants often visit our ORUG and ask for some analysis, which we provide using R. Additionally, students also use R for their projects.\nI use R for many of my publications. R has gained a lot of popularity, not only within our institution but also among sister institutions in the area. Some departments have even made R the only software that students are required to use for analysis.\nWhat industry are you currently in? How do you use R in your work?\nI am in the education sector, and I use R for my work in time series analysis, which is my area of specialization. I rely on TSA, tseries and other related time series packages to carry out my work. For example, I used R for Modeling the Residuals of Financial Time Series with Missing Values for Risk Measures, which was my MSc project. I have also used R in the Application of the Seasonal Autoregressive Moving Average Model to Analyze and Forecast the Food Price Index (free registration required). Additionally, I used R in a paper titled “Volatility of Exchange Rates in Nigeria: An Investigation of Risk on Investment.” In another innovative project was Modelling Circular Time Series with Applications. These are just a few examples of the papers and research where I’ve personally used R.\nYou have a Meetup titled Test for the Assumptions of Linear Regression Using R, can you share more on the topic covered? Why this topic?\nSome authors use regression models without checking whether the assumptions hold or not. Instead of carrying out tests to confirm this, they assume that the model is valid if the assumptions are fulfilled. This topic aims to highlight the importance of carrying out such tests to ensure reliable and comprehensive results. Lack of adherence to the assumptions may lead to inaccurate conclusions. The focus will be on commonly used tests for normality, linearity, autocorrelation, heteroscedasticity/homoscedasticity, and multicollinearity, with illustrative examples using R.\nI appreciate the R Consortium for their valuable RUGs grant assistance in 2022. With this grant, I could open two other user groups: the Ilorin R Users Group and the Kwara Environmental Statistics R Group. I also want to express my gratitude to the R Consortium for sponsoring my Meetup subscription and covering other minor expenses in 2022. The subscription is still ongoing, and I hope that we can continue our partnership to promote the use of R in our community.\nI would like to request for speakers to present at our R User Group. We are currently seeking speakers for our upcoming events and would be delighted to welcome speakers from all over the world to share their R-related knowledge with us." + "objectID": "members.html#platinum-members", + "href": "members.html#platinum-members", + "title": "R Consortium", + "section": "Platinum Members", + "text": "Platinum Members" }, { - "objectID": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html#how-do-i-join", - "href": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html#how-do-i-join", - "title": "Offa R Users Group: Empowering Data-Driven Education in Nigeria", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "members.html#silver-members", + "href": "members.html#silver-members", + "title": "R Consortium", + "section": "Silver Members", + "text": "Silver Members" }, { - "objectID": "posts/pharma-rug-the-rise-of-r/index.html", - "href": "posts/pharma-rug-the-rise-of-r/index.html", - "title": "Pharma RUG: The Rise of R in China’s Pharmaceutical Industry", + "objectID": "codeofconduct.html", + "href": "codeofconduct.html", + "title": "Code of Conduct", "section": "", - "text": "PharmaRUG, China organizer Joe Zhu, spoke with the R Consortium about the growing R community and the increasing use of R in the pharmaceutical industry in China. The group has contributed to the pharmaceutical R community through several R packages. Since its establishment last year, the group has organized large-scale hybrid events. Joe also shared some tools and techniques for smoothly organizing and running hybrid events.\n\nPlease share about your background and involvement with the RUGS group.\nI have a PhD in statistics and studied in New Zealand for my undergraduate and postgraduate degrees in statistics. My PhD work focused on theoretical coalescent theory and probabilistic modeling for phylogenetics models. I also completed a postdoc at Oxford, focusing on statistical genomics for the human genome and malaria parasite genome projects. During this time, I developed open source software tools for statistical genomics, primarily using R as a front end and developing C++ software.\nFor the past four years, I’ve worked at Roche, where I started leading a major collaboration initiative in pharma three years ago. I’ve created TLG (table, listing, and figures) for regulatory submissions to the FDA. Throughout this initiative, we have open sourced around 30 software packages, including `formatters`, `rtables`, `rlistings` and `tern`. Last year, we submitted these packages to CRAN.\nAt first, we open sourced the project on GitHub and then submitted it to CRAN. I’m heavily involved in one of China’s R user groups, PharmaRUG. We use the group to share posts about developments in the area, and we organize events and conferences. In March last year, we hosted the first event with over 100 people on-site and around 100 online. The event covered topics like R package usage in the pharma industry. Later that year, we organized another event called “Open Source Clinical Reporting summeR“. \n\nLately, I have been busy organizing several events. I recently gave a talk (about R package dependencies as directed in acyclic graphs) at a conference hosted by the R community in China. Early next month, on August 1st, I will attend a pharma conference where I will conduct a workshop on good practices in software package development. The conference schedule is quite packed for me as I also have a session on how teams operate and collaborate within the Pharma industry to develop R packages. On the third day of the conference, I will organize a series of 11 data visualization talks, one of which is about Python. Most of the talks will focus on using R, except for one discussion on Python.\nCan you share what the R community is like in China? \n\nWe have opened up seats for students to join our events in the pharmaceutical industry. In the past, fewer than 20 students, mostly from academia, have joined us for these conferences. The events include big names like Roche, Johnson & Johnson, Novartis, Boehringer Ingelheim, and Sanofi and local companies such as Fosun, Hengrui, and Legend Biotech. There is a big R community in China across academia and industry. Our user group primarily focuses on the pharma industry. Our WeChat channel has nearly a thousand subscribers, and our group chat has almost 500 members. It’s a very active community. \nLater this year, we will collaborate with the “R in Pharma” for the October conference. Daniel Sabanes Bove and I have contacted Harvey and Phil, and we will organize an APAC track, including India, China, Japan, Australia, Singapore, and Korea. \nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nWe have created a GitHub account called PharmaRUG. We use this platform to share websites, posts, slides, and videos related to our events. The Pharma RUG 2024 conference was particularly successful this year, thanks to the support from the R Consortium. We also utilize WeChat groups to call for speakers and interact with others. In addition to GitHub and WeChat, we use Tencent Docs to share documents. This is particularly useful in China, where using company-specific platforms like Google or Microsoft can be hindered by firewalls. Tencent Docs works perfectly in China, making sharing and synchronizing documents easy.\nCan you share some valuable tips for organizing succesful Hybrid events?\n\nWe have a series of planning sessions where we actively communicate using WeChat. We meet at a community center where everyone is open, and we have preset meetings. We test the audio and everything beforehand. This is our second year organizing these events, so we have gained more experience. We are now familiar with the standards and know what needs to be done. For example, when two companies, like MNCs, use different systems, we find it better to use one shared system to ensure everything is synchronized.\nWe’ve found that Microsoft Teams is easy to use for setting up meetings and scheduling them ahead of time. For live demos, we recommend pre-recording the demos and taking questions. In the case of hybrid sessions with multiple locations, we prioritize asking and answering questions based on the primary and secondary locations, as well as online participation. If we cannot answer questions quickly, we host Q&A sessions afterward and share them online.\nI believe that for the event to be successful, timing is crucial. We must stick to the schedule because it’s a hybrid event. However, we should also allow for some flexibility when unexpected things come up. We haven’t created a YouTube account yet because YouTube isn’t accessible in China. One alternative could be setting up a Bilibili web page and account to share the videos. All our files are currently on GitHub, which is convenient. We need to trim the videos to smaller sizes to fit GitHub’s file size limits, maybe at four and a half speeds or similar.\nWhat trends do you currently see in R language and your industry?\nSo, SAS has dominated the software space for the Pharma industry for decades. While it used to be used for exploratory and research purposes, there have been successes with using Office to support missions in recent years. Roche also has success stories in this area. There are several initiatives, with PharmaVerse being a significant player. Roche is part of PharmaVerse, taking inspiration from the tidyverse multiverse concept. The end-to-end clinical reporting process is considered in this space, from data preparation to TLG generations. A lot has happened in the past three to four years, especially in China last year. There’s been significant development in China, and you can see a shift from SAS to R in the tools used. At the PharmaSUG meeting, which was previously dominated by SAS users, in the past few years, a quarter to one-third of the tools are using languages other than SAS. It’s clear that things are moving away from SAS towards software languages like R.\nThis year, I don’t have the complete statistics with me right now, but you do see a lot of topics. In my session, I’m sharing, and you know, many talks use visualization because it’s much likable. So, the trend is that R is becoming more acceptable than before, from PLCs to things in production. There are very high standards for codes and validation.\nIn the end, I would like to thank my dear friends and colleagues for their support and for making this happen\n\nYan Qiao, Associate Director of Scientific Programming, Beigene, \nBaoqin Li, China Head Clinical & Statical Programming, Johnson & Johnson\nDong Guo, China head of Stats Analyst, Eli-lilly&Company\nYun Ma, Director, clinical data Sciences, Boehringer Ingelheim (china) Investment Co.\nYanli Chang, Head of Data Operations China, Novartis\n\nHow do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute." + "text": "The R Consortium and its working groups are dedicated to providing a harassment-free experience for participants at all of our events, whether they are held in person or virtually. R Consortium events are working conferences intended for professional networking and collaboration within the open source community. They exist to encourage the open exchange of ideas and expression and require an environment that recognizes the inherent worth of every person and group. While at R Consortium events or related ancillary or social events, any participants, including members, speakers, attendees, volunteers, sponsors, exhibitors, booth staff and anyone else, should not engage in harassment in any form.\nThis Code of Conduct may be revised at any time by The R Consortium and the terms are non-negotiable. Your registration for or attendance at any R Consortium event, whether it’s held in person or virtually, indicates your agreement to abide by this policy and its terms.\n\n\nAll event participants, whether they are attending an in-person event or a virtual event, are expected to behave in accordance with professional standards, with both this Code of Conduct as well as their respective employer’s policies governing appropriate workplace behavior and applicable laws.\n\n\n\nHarassment will not be tolerated in any form, whether in person or virtually, including, but not limited to, harassment based on sex, gender, sexual orientation, disability, physical appearance, body size, race, age, religion or any other status protected by laws in which the conference or program is being held. Harassment includes the use of abusive, offensive or degrading language, intimidation, stalking, harassing photography or recording, inappropriate physical contact, sexual imagery and unwelcome sexual advances or requests for sexual favors. Any report of harassment at one of our events, whether in person or virtual, will be addressed immediately. Participants asked to stop any harassing behavior are expected to comply immediately. Anyone who witnesses or is subjected to unacceptable behavior should notify a conference organizer at once.\nExhibitors should not use sexualized images, activities, or other material in their booths and must refrain from the use of sexualized clothing, uniforms, costumes, or otherwise creating a sexualized environment. Speakers should not use sexual language, images, or any language or images that would constitute harassment as defined above in their talks.\nIndividuals who participate (or plan to participate) in R Consortium events, whether its an in-person event or a virtual event, should conduct themselves at all times in a manner that comports with both the letter and spirit of this policy prohibiting harassment and abusive behavior, whether before, during or after the event. This includes statements made in social media postings, on-line publications, text messages, and all other forms of electronic communication.\n\n\n\nIf a participant engages in harassing behavior, whether in person or virtually, the conference organizers may take any action they deem appropriate depending on the circumstances, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nIf a participant (or individual wishing to participate in an R Consortium event, in-person and/or virtual), through postings on social media or other online publications or another form of electronic communication, engages in conduct that violates this policy, whether before, during or after a R Consortium event, the R Consortium may take appropriate corrective action, which could include imposing a temporary or permanent ban on an individual’s participation in future R Consortium events, events, working groups, trainings or other activities.\n\n\n\nIf you are being harassed, notice that someone else is being harassed, or have any other concerns relating to harassment, please contact a member of the conference staff immediately. You are also encouraged to contact abuse@r-consortium.org.\n\n\n\nOur staff has taken incident response training and responds to harassment reports quickly and thoroughly. As referenced above, if a participant engages in harassing behavior, whether in-person or virtually, the conference organizers may take any action they deem appropriate, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund, depending on the circumstances. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nConference staff will also provide support to victims, including, but not limited to:\n\nProviding an Escort\nContacting Hotel/Venue Security or Local Law Enforcement\nBriefing Key Event Staff For Response/Victim Assistance\nAnd otherwise assisting those experiencing harassment to ensure that they feel safe for the duration of the conference.\n\n\n\n\nIf you are planning to attend an upcoming event, whether in-person or virtually and have concerns regarding another individual who may be present, please contact conduct@r-consortium.org. Precautions will be taken to ensure your comfort and safety, including, but not limited to providing an escort, prepping onsite event staff, keeping victim and harasser from attending the same talks/social events and providing onsite contact cell phone numbers for immediate contact." }, { - "objectID": "index.html", - "href": "index.html", - "title": "R Consortium", + "objectID": "codeofconduct.html#committed-to-a-safe-and-inclusive-environment-for-the-r-consortium-community", + "href": "codeofconduct.html#committed-to-a-safe-and-inclusive-environment-for-the-r-consortium-community", + "title": "Code of Conduct", "section": "", - "text": "R User Group Program and Small Conference Funding Program now accepting applications Partner with us to support your meetup or local event.\n\n\nLEARN MORE\n\n\n\n\nFind your local R user group Network with fellow statisticians and learn from your peers.\n\n\nFIND A USER GROUP\n\n\n\n\nR Consortium: Supporting the R community, the R Foundation and organizations developing, maintaining and distributing R software.\n\n\n\n\nFind your local R user group Network with fellow statisticians and learn from your peers.\n\n\nLEARN MORE\n\n\n\n\nR/Medicine Webinar: Visualizing Survival Data with the {ggsurvfit} R Package\n\n\nWebinar Recording\n\n\n\n\nTidy Finance Webinar Series\n\n\nWebinar Information\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWHAT IS THE R CONSORTIUM\n\n\nThe central mission of the R Consortium is to work with and provide support to the R Foundation and to the key organizations developing, maintaining, distributing and using R software through the identification, development and implementation of infrastructure projects.\n\n\nThe R language is an open source environment for statistical computing and graphics, and runs on a wide variety of computing platforms. The R language has enjoyed significant growth, and now supports over 2 million users. A broad range of industries have adopted the R language, including biotech, finance, research and high technology industries. The R language is often integrated into third party analysis, visualization and reporting applications.\n\n\n\n \n\n\n\nLEARN MORE\n\n\nREAD OUR ANNUAL REPORT 2023\n\n\n\n\nJoining R Consortium\n\n\nIndustry-leading organizations have joined the R Consortium to support an open source governance and foundation model to provide support to the R community, the R Foundation and groups and individuals, using, maintaining and distributing R software.\n\n\nLEARN MORE ABOUT MEMBERSHIP\n\n\n\n\nNeed Help?\n\n\nIf you need help such as with billing, mailing lists or other wise then please use this service desk for support.\n\n\nGET HELP\n\n\n\n\nBLOG\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nStreamlining API Integration: Jon Harmon’s Journey with the api2r Package\n\n\nThe R package api2r simplifies the process of wrapping APIs in R. The R Consortium interviewed Jon Harmon, Principal Data Solutions Engineer at Atorus, about this R…\n\n\n\nR Consortium\n\n\nOct 30, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers\n\n\nFrans van Dunné, the organizer of the San Carlos R User Group, recently discussed with the R Consortium the development of the R community in Costa Rica and the broader…\n\n\n\nR Consortium\n\n\nOct 23, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEndophytes, Oaks, and R: How R-Ladies Morelia is Cultivating Science and Community in Morelia, Mexico\n\n\nGoretty Mendoza, the organizer of the R-Ladies Morelia, recently spoke to the R Consortium about her experience with the group and her work using R in molecular biology.\n\n\n\nR Consortium\n\n\nOct 18, 2024\n\n\n\n\n\n\n\n\n\n\n\n\nThe U.S. Federal Reserve quarterly model in R\n\n\n\n\n\n\nGuest Blog Post\n\n\nOct 16, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEmpowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative\n\n\nThe Dengue Data Hub, an ambitious initiative funded by the R Consortium ISC, transforms how researchers access and utilize dengue-related data.\n\n\n\nR Consortium\n\n\nOct 15, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nR/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track\n\n\nR/Pharma 2024 is coming up Oct 29-Nov 1, 2024. This is a free event, fully virtual. For the first time, R/Pharma will be including a dedicated Asia-Pacific (APAC) track…\n\n\n\nR Consortium\n\n\nOct 14, 2024\n\n\n\n\n\n\n\n\nNo matching items" + "text": "The R Consortium and its working groups are dedicated to providing a harassment-free experience for participants at all of our events, whether they are held in person or virtually. R Consortium events are working conferences intended for professional networking and collaboration within the open source community. They exist to encourage the open exchange of ideas and expression and require an environment that recognizes the inherent worth of every person and group. While at R Consortium events or related ancillary or social events, any participants, including members, speakers, attendees, volunteers, sponsors, exhibitors, booth staff and anyone else, should not engage in harassment in any form.\nThis Code of Conduct may be revised at any time by The R Consortium and the terms are non-negotiable. Your registration for or attendance at any R Consortium event, whether it’s held in person or virtually, indicates your agreement to abide by this policy and its terms.\n\n\nAll event participants, whether they are attending an in-person event or a virtual event, are expected to behave in accordance with professional standards, with both this Code of Conduct as well as their respective employer’s policies governing appropriate workplace behavior and applicable laws.\n\n\n\nHarassment will not be tolerated in any form, whether in person or virtually, including, but not limited to, harassment based on sex, gender, sexual orientation, disability, physical appearance, body size, race, age, religion or any other status protected by laws in which the conference or program is being held. Harassment includes the use of abusive, offensive or degrading language, intimidation, stalking, harassing photography or recording, inappropriate physical contact, sexual imagery and unwelcome sexual advances or requests for sexual favors. Any report of harassment at one of our events, whether in person or virtual, will be addressed immediately. Participants asked to stop any harassing behavior are expected to comply immediately. Anyone who witnesses or is subjected to unacceptable behavior should notify a conference organizer at once.\nExhibitors should not use sexualized images, activities, or other material in their booths and must refrain from the use of sexualized clothing, uniforms, costumes, or otherwise creating a sexualized environment. Speakers should not use sexual language, images, or any language or images that would constitute harassment as defined above in their talks.\nIndividuals who participate (or plan to participate) in R Consortium events, whether its an in-person event or a virtual event, should conduct themselves at all times in a manner that comports with both the letter and spirit of this policy prohibiting harassment and abusive behavior, whether before, during or after the event. This includes statements made in social media postings, on-line publications, text messages, and all other forms of electronic communication.\n\n\n\nIf a participant engages in harassing behavior, whether in person or virtually, the conference organizers may take any action they deem appropriate depending on the circumstances, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nIf a participant (or individual wishing to participate in an R Consortium event, in-person and/or virtual), through postings on social media or other online publications or another form of electronic communication, engages in conduct that violates this policy, whether before, during or after a R Consortium event, the R Consortium may take appropriate corrective action, which could include imposing a temporary or permanent ban on an individual’s participation in future R Consortium events, events, working groups, trainings or other activities.\n\n\n\nIf you are being harassed, notice that someone else is being harassed, or have any other concerns relating to harassment, please contact a member of the conference staff immediately. You are also encouraged to contact abuse@r-consortium.org.\n\n\n\nOur staff has taken incident response training and responds to harassment reports quickly and thoroughly. As referenced above, if a participant engages in harassing behavior, whether in-person or virtually, the conference organizers may take any action they deem appropriate, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund, depending on the circumstances. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nConference staff will also provide support to victims, including, but not limited to:\n\nProviding an Escort\nContacting Hotel/Venue Security or Local Law Enforcement\nBriefing Key Event Staff For Response/Victim Assistance\nAnd otherwise assisting those experiencing harassment to ensure that they feel safe for the duration of the conference.\n\n\n\n\nIf you are planning to attend an upcoming event, whether in-person or virtually and have concerns regarding another individual who may be present, please contact conduct@r-consortium.org. Precautions will be taken to ensure your comfort and safety, including, but not limited to providing an escort, prepping onsite event staff, keeping victim and harasser from attending the same talks/social events and providing onsite contact cell phone numbers for immediate contact." }, { - "objectID": "media-partners.html", - "href": "media-partners.html", - "title": "Media Partners", + "objectID": "all-projects/submittingforpayment.html", + "href": "all-projects/submittingforpayment.html", + "title": "Submitting for payment", "section": "", - "text": "Media Partners\nThe R Consortium is proud to partner with the following media and associations to amplify information about R community activities around the globe. If you are interested in becoming a media partner, please contact us at info@r-consortium.org.\n\nR news and tutorials contributed by hundreds of R bloggers" + "text": "Submitting for payment\nThe R Consortium provides financial support to a broad range of initiatives, in support of the global R development and user community. When organizations become members of the R Consortium, their membership dues help provide this funding, and help ensure the overall health of the ecosystem.\nThe R Consortium provides funding through a structured process. The primary funding categories are:\n\nISC Grants, which are allocated by the Infrastructure Steering Committee through an application process, and support code and community development efforts.\nRUGs Grants, which support local R User Groups.\n\nAll grant payments must be pre-approved. Please follow the formal process established by each working group to apply for funding.\n\nInvoicing for your grant\nStarting in October 2020, each grant recipient will receive a control number. Please ensure that you include this in all requests for payment. If you are unsure of your control number, please contact operations@r-consortium.org.\nWhen you are ready to submit for payment, please complete the payment request form. You will be asked to provide the following, so please have it ready:\n\nThe control number for your grant.\nA W9 form (if you are in the US and have a SSN/EIN) or an international wire form.\nThe signed contract or a PDF of the email approving your grant.\nA brief description of how the funding was used (e.g., project milestone, RUGs or R-Ladies meetup, etc).\n\nIf you have any questions, please contact operations@r-consortium.org." }, { - "objectID": "all-projects/2019-group-2.html", - "href": "all-projects/2019-group-2.html", - "title": "R Consortium", + "objectID": "all-projects/2021-group-1.html", + "href": "all-projects/2021-group-1.html", + "title": "Funded ISC Grants (2021-1)", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n\n\n\nFunded:\n$8,500\nProposed by:\nAaron Jacobs\nWebsite:\nhttps://github.com/atheriel/xrprof\nSummary:\nMany R users will be familiar with using the built-in sampling profiler ‘Rprof()’ to generate data on what their code is doing, and there are several excellent tools to facilitate understanding these samples (or serve as a front-end), including the ‘profvis’ package. However, the reach of these tools is limited: the profiler is “internal”, in the sense that it must be manually switched on to work, either during interactive work (for example, to profile an individual function), or perhaps by modifying the script to include ‘Rprof()’ calls before running it again. It cannot be used to understand R code that is already running, a capability that has proven extremely useful for diagnosing and fixing performance issues (or other bugs) in production environments.\nSeveral existing programming languages have one or more “external” profilers available, which can attach to a running process and read its memory contents to understand what is currently happening. This project aims to build such a tool for R.\n\n\n\nFunded:\n$9,500\nProposed by:\nDavid W Kang\nWebsite:\nhttps://github.com/cvxgrp/CVXR\nSummary:\nOptimization is at the core of statistical estimation and machine learning methodology. There are a number of R packages such as optimx, nloptr, ROI which either implement solvers for a wide variety of problems, or provide an interface to other solvers. The R package CVXR takes a different approach, implementing a Domain Specific Language (Fu, Narasimhan, and Boyd 2019) for formulating and solving convex optimization problems, just as cvxpy does for python. As shown in a number of examples on the CVXR website, the applications range from finance, machine learning, and to theoretical and applied statistics. Using a disciplined convex programming (DCP) approach, CVXR acts as a great tool for both prototyping and developing new methodologies as well as for quick, high-level, formulation and solution of statistical and machine learning problems.\n\n\n\nFunded:\n$6,699\nProposed by:\nEvangeline Reynolds\nWebsite:\nhttps://github.com/EvaMaeRey/flipbookr\nSummary:\nJust as classic flip books allow their readers to observe changes in a scene, coding Flipbooks allow readers to progressively track the changes of code and its output by “flipping” through their digital pages. Flipbooks are useful tools for communicating and teaching because they break down code for incremental, stepwise presentation so that audiences can easily understand each step. Flipbook-building tools automate the deconstruction and reconstruction of coding pipelines which means that building a Flipbook from existing code poses little additional burden to creators. The next stage for this project is to develop the current Flipbook-building tools into a reliable and easy-to-use R package (development is ongoing at https://github.com/EvaMaeRey/flipbookr) and also to provide educational guidance for creating Flipbooks.\n\n\n\nFunded:\n$16,800\nProposed by:\nAndrew Nicholls\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe R Validation Hub is an active R Consortium Working Group. It is a cross-industry initiative whose mission is to enable the use of R by the Bio-Pharmaceutical Industry in a regulatory setting, where the output may be used in submissions to regulatory agencies. This project sits within phase 2 of the R Validation Hub’s road map. During this phase the group will develop several tools that can be used by those wishing to use R packages within a bio-pharmaceutical regulatory setting. The aim of this specific project is to standardise and simplify the risk assessment of R packages, reducing the burden of package evaluation/testing that would otherwise fall on internal R programming experts. The project will deliver a Shiny application to aid in the assessment and documentation of package risk.\n\n\n\nFunded:\n$34,000\nProposed by:\nToby Hocking\nWebsite:\nhttps://github.com/akhikolla/RcppDeepState\nSummary:\nAbstract: Fuzzers are computer programs that send other programs inputs that may fall outside the domain of expected values, thus revealing subtle bugs. DeepState is a testing framework that allows easy testing of C/C++ programs with sophisticated fuzzers, and supports multiple back-ends for testing. DeepState has been used to test critical C++ software, including Google’s leveldb. R has some simple random testers, but no coverage-driven fuzzers that learn to produce problematic inputs. We propose to create the R packages RcppDeepState and RcppDeepStateTools which will provide easy-to-use functions for using DeepState with R packages that use C/C++ code via Rcpp. This project will thus provide the first easy-to-use solution for R programmers that want to fuzz test their C/C++ code with existing tools such as AFL, and it will provide a framework for interfacing future coverage-driven fuzzers or symbolic execution tools. We also propose to use these new tools on a wide range of R packages in order to identify bugs in their C/C++ code.\nOne masters student will be recruited to implement this project during Jan-Dec 2020 at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. Interested students should apply by emailing a resume/CV along with a cover letter to project supervisors toby.hocking@nau.edu and alex.groce@nau.edu.\n\n\n\nFunded:\n$10,000\nProposed by:\nMikkel Meyer Andersen\nWebsite:\nhttps://github.com/r-cas/caracas/\nSummary:\nR’s ability to do symbolic mathematics is largely restricted to finding derivatives. There are many tasks involving symbolic math that are of interest to R users, e.g. inversion of symbolic matrices, limits and solving non-linear equations. Users must resort to other software for such tasks and many R users (especially outside of academia) do not readily have access to such software.\nThe Python library SymPy is open source, has a stable group of developers and is powerful. As such, R users can just switch to Python and SymPy for symbolic math. However it is often very convenient to stay in the same environment to use familiar syntax and to utilise available libraries (e.g. to generate problems using symbolic math together with the exams package or to first handle symbolic computations and then afterwards move on to a numerical evaluations of the results). We will achieve this by making SymPy functionality available for R users via an R package.\nCurrently only few R packages for doing symbolic mathematics are available: Two of these are Ryacas and rSymPy. Ryacas is built around Yacas, and although Yacas can solve many problems and is extensible, the community is relatively small and Yacas is not as powerful as SymPy for certain routine tasks (e.g. integration and solving equations). rSymPy on the other hand is based on technology that requires much technical work to install and use.\nThe website of the project is:\nhttps://github.com/r-cas/caracas/\nPlease contribute by testing, writing documentation, opening issues, submitting pull requests or something else!\n\n\n\nFunded:\n$9,000\nProposed by:\nLucas van der Meer, Robin Lovelace, Andrea Gilardi, Lorena Abad\nWebsite:\nhttps://luukvdmeer.github.io/sfnetworks/\nSummary:\nR is currently lacking a generally applicable, modern and easy-to-use way of handling all kinds of spatial networks. “Tidy spatial networks in R” aims to address this issue by developing and publishing the sfnetworks package. The package, and documentation around it, will provide a bridge between network analysis and spatial analysis communities. For this, an sfnetwork class that will work with both tidygraph and sf frameworks and functions. R-users will be encouraged to contribute and engage with the package development during a hackathon organized next to the eRum 2020.\n\n\n\nFunded:\n$4,000\nProposed by:\nMauricio Vargas Sepúlveda\nWebsite:\nhttps://github.com/pachamaltese/d3po\nSummary:\nR already features excellent visualization libraries such as D3 (via the r2d3 package), plotly or highcharter. However, though those enable the creation of great looking visualisations they have very steep learning curves, require understanding of JavaScript or rely on non-free software that might be out of reach for governments and NGOs. Our intention is to solve those problems by releasing d3po. It shall be an intermediate layer between the user and D3 by providing “templates”, enabling high quality interactive visualizations oriented to and designed to be used with Shiny and Rmarkdown, and also proving easy internationalization. Please join us, this needs D3 and R skilled minds!\n\n\n\nFunded:\n$6,000\nProposed by:\nEric Scott, Tamas Stirling\nWebsite:\nhttps://github.com/ropensci/webchem\nSummary:\nwebchem: accessing chemical information from the web\nA vast amount of chemical information is freely available on the internet. The data are used by millions of professionals around the world, for purposes like pharmaceutical research, chemical process design, or environmental impact assessment, to name a few. webchem is an R project that aims to help these professionals by providing a single point programmable access to all major chemical databases around the world. The project started in 2016 and currently supports more than 10 databases. If you are interested, join us and help us build the tool that biologists and chemists will absolutely love." + "text": "Funded ISC Grants (2021-1)\nThe R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAccounting/Auditing Gap-Analysis\nExtendr - Rust extensions for R.\nGoogle Earth Engine with R\nImproving Translations in R\nMinimizing wastage of blood products\nR for Engineering Applications\nSetting up an R-Girls-Schools Network\ndeposits: Deposit Research Data Anywhere\n\n\n\nAccounting/Auditing Gap-Analysis\nFunded:\n$7,000\nProposed by:\nFelix Schildorfer\nSummary:\nThere are more and more accountants and auditors who want to start using R and dig into data science. They usually have particular tasks on hand that they want to complete, facilitate, or automate. While they often have some basic stats skills and may be some coding basics, understanding the R landscape and relating tasks and processes to locate and use relevant R packages and tutorials is an extreme challenge. While other areas like finance or pharmaceuticals already have extensive infrastructure to support R newcomers (Working Groups, Courses, Task Views, etc.) accounting and auditing do not. This becomes an obstacle for such professionals - which find the “coding” part difficult on their own but doing so without any support or knowing the appropriate package becomes a nightmare.\nThis is why R Business put together this project with the aim to gauge the landscape of what functionalities are available for Auditors in the R ecosystem and how the existing functionalities can be mapped to routine accounting/auditing tasks. We will complete a systematic survey of the CRAN-ecosystem for accounting/auditing tasks to establish a mapping and identify gaps. The project will contribute to the development of the R Business ISC working group by attracting interested accounting/auditing professionals, industry bodies and R community members. This will then in turn lead to increased use of R/RStudio, development new application domains for data science, and enhancement of the quality of accounting/auditing services.\n\n\nExtendr - Rust extensions for R.\nFunded:\n$15,000\nProposed by:\nAndy Thomason\nSummary:\nRust extension framework for R.\n\n\nGoogle Earth Engine with R\nFunded:\n$5,500\nProposed by:\nCesar Luis Aybar Camacho\nSummary:\nGoogle Earth Engine (GEE) is the most popular and advanced cloud platform designed for planetary-scale environmental data analysis. Its multi-petabyte data catalog and computation services are just accessed via Python and JavaScript client libraries. In order to facilitate its use within R, six months ago, rgee was released on CRAN using reticulate to wrap the GEE Python API. Although rgee provides a familiar interface and simple integration to other R packages (e.g., sf, raster, dplyr), the lack of tutorials and examples makes it difficult for new users to adopt.\nThe main goal of this project is to leverage the documentation. For this purpose, three main tasks have been proposed: (1) create a new version of rgee with support for shiny and markdown, (2) create rgeeExtra, which extends the functionalities of rgee, and finally write (3) rgeebook, a reference book with best practices and examples of GEE API usage.\n\n\nImproving Translations in R\nFunded:\n$0\nProposed by:\nMichael Chirico\nSummary:\nThis project will provide a better formalization of translation procedures for R to be more sustainable and more scalable. In the process, it will broaden the inclusivity of R by growing the sub-community of R users comfortable producing translations and extending the reach of the R project to more non-English audiences.\n\n\nMinimizing wastage of blood products\nFunded:\n$11,200\nProposed by:\nBalasubramanian Narasimhan\nSummary:\nGuan et al. 2017 (Proc Natl Acad Sci U S A 114 (43): 11368–73) used two years worth of data to formulate and solve an optimization problem to predict platelet usage and minimize waste. Two open-source R packages were developed for this purpose:\n- Platelet Inventory Prediction or pip (https://github.com/bnaras/pip) a package that is the core ML prediction engine that uses a given set of features described in the above publication\n- Stanford Blood Center Platelet Inventory Prediction or SBCpip (https://github.com/bnaras/SBCpip) that was customized to the data workflow at SHC. SBCpip was meant to be site specific.\nThere have been a number of requests from sites wishing to deploy the software locally. The current project will generalize the model, generalize it to address more blood products with different shelf lives, provide customizations for local use, and create easily deployable solutions.\n\n\nR for Engineering Applications\nFunded:\n$3,000\nProposed by:\nBenaiah Chibuokem Ubah\nSummary:\nR for Engineering Applications is a proposed project with the aim to attract engineers and diversify the use of the R language to the broad engineering domain – electrical, electronic, communications, robotics, etc engineering. The idea is similar to such projects as R in Finance, R in Insurance, BioConductor (R in Bio-informatics), R in Environmental Statistics, etc.\n\n\nSetting up an R-Girls-Schools Network\nFunded:\n$5,000\nProposed by:\nDr. Razia Ghani\nSummary:\nGlobally, women, especially from deprived socio-economic and diverse ethnic backgrounds, are under-represented in data science. A major factor is that data science does not feature in the school curriculum which means that teachers are unaware of the enhancements data science can bring to learning and development in and beyond the school. We propose an ongoing project, called R-Girls-School Network (short name R-Girls) to address this and are keen to link up with others.\nWe are a multi-disciplinary team that includes an educationalist, subject teachers, a data scientist and administrator who will begin to develop and implement a data science curriculum using R in Green Oak Academy – an inner-city school in the UK serving girls from deprived, ethnically diverse backgrounds aged 11-16 years; independently rated as Good with Outstanding for Behaviour and Attitudes.\nSince GOA follows the UK national curriculum, which is used in 10,000+ schools and 160 countries, our work will have a broad appeal. In due course we will develop ready-to-use bite-sized learning materials (10-15 mins) for teachers of core subjects (maths, statistics, science, geography) to use via RStudio cloud. The lessons will be tested with teachers and pupils and then incorporated into the school timetable across all five-year groups (age 11-16 years), culminating in an R-Data Story project and in due course, an annual R-Girls virtual conference open to any girl and girls’ school in the world.\nR-GS will be supported by a website for showcasing the work of pupils and sharing resources.\n\n\ndeposits: Deposit Research Data Anywhere\nFunded:\n$16,000\nProposed by:\nMark Padgham\nSummary:\nPublicly depositing datasets associated with published research is becoming more common, partly due to journals increasingly requiring data sharing, and partly though more general and ongoing cultural changes in relation to data sharing. Yet data sharing is often seen as time consuming, particularly in order to meet the expectations of individual data repositories. While documentation and training can help get users familiar with processes of data sharing, browser-based data and metadata submission workflows can only be so fast, are not easily reproduced, and do not facilitate regular or automated updates of data and metadata. Better programmatic tools can transform data sharing from a mountainous climb into a pit of success.\nThis project will develop a unified interface to many different research data repositories, and which will function along the lines of dplyr through “verbs” that work identically across many “backend” data repositories. The package will initially provide access to a few of the most common data repositories, yet will implement a modular/plugin system to enable users to contribute their own plugins to extend functionality to other repositories. Users will be able to authenticate, prepare data and metadata, and finally to submit, fetch, and browse data." }, { - "objectID": "all-projects/2019-group-2.html#funded-isc-grants-2019-2", - "href": "all-projects/2019-group-2.html#funded-isc-grants-2019-2", + "objectID": "all-projects/2022-group-1.html", + "href": "all-projects/2022-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n\n\n\nFunded:\n$8,500\nProposed by:\nAaron Jacobs\nWebsite:\nhttps://github.com/atheriel/xrprof\nSummary:\nMany R users will be familiar with using the built-in sampling profiler ‘Rprof()’ to generate data on what their code is doing, and there are several excellent tools to facilitate understanding these samples (or serve as a front-end), including the ‘profvis’ package. However, the reach of these tools is limited: the profiler is “internal”, in the sense that it must be manually switched on to work, either during interactive work (for example, to profile an individual function), or perhaps by modifying the script to include ‘Rprof()’ calls before running it again. It cannot be used to understand R code that is already running, a capability that has proven extremely useful for diagnosing and fixing performance issues (or other bugs) in production environments.\nSeveral existing programming languages have one or more “external” profilers available, which can attach to a running process and read its memory contents to understand what is currently happening. This project aims to build such a tool for R.\n\n\n\nFunded:\n$9,500\nProposed by:\nDavid W Kang\nWebsite:\nhttps://github.com/cvxgrp/CVXR\nSummary:\nOptimization is at the core of statistical estimation and machine learning methodology. There are a number of R packages such as optimx, nloptr, ROI which either implement solvers for a wide variety of problems, or provide an interface to other solvers. The R package CVXR takes a different approach, implementing a Domain Specific Language (Fu, Narasimhan, and Boyd 2019) for formulating and solving convex optimization problems, just as cvxpy does for python. As shown in a number of examples on the CVXR website, the applications range from finance, machine learning, and to theoretical and applied statistics. Using a disciplined convex programming (DCP) approach, CVXR acts as a great tool for both prototyping and developing new methodologies as well as for quick, high-level, formulation and solution of statistical and machine learning problems.\n\n\n\nFunded:\n$6,699\nProposed by:\nEvangeline Reynolds\nWebsite:\nhttps://github.com/EvaMaeRey/flipbookr\nSummary:\nJust as classic flip books allow their readers to observe changes in a scene, coding Flipbooks allow readers to progressively track the changes of code and its output by “flipping” through their digital pages. Flipbooks are useful tools for communicating and teaching because they break down code for incremental, stepwise presentation so that audiences can easily understand each step. Flipbook-building tools automate the deconstruction and reconstruction of coding pipelines which means that building a Flipbook from existing code poses little additional burden to creators. The next stage for this project is to develop the current Flipbook-building tools into a reliable and easy-to-use R package (development is ongoing at https://github.com/EvaMaeRey/flipbookr) and also to provide educational guidance for creating Flipbooks.\n\n\n\nFunded:\n$16,800\nProposed by:\nAndrew Nicholls\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe R Validation Hub is an active R Consortium Working Group. It is a cross-industry initiative whose mission is to enable the use of R by the Bio-Pharmaceutical Industry in a regulatory setting, where the output may be used in submissions to regulatory agencies. This project sits within phase 2 of the R Validation Hub’s road map. During this phase the group will develop several tools that can be used by those wishing to use R packages within a bio-pharmaceutical regulatory setting. The aim of this specific project is to standardise and simplify the risk assessment of R packages, reducing the burden of package evaluation/testing that would otherwise fall on internal R programming experts. The project will deliver a Shiny application to aid in the assessment and documentation of package risk.\n\n\n\nFunded:\n$34,000\nProposed by:\nToby Hocking\nWebsite:\nhttps://github.com/akhikolla/RcppDeepState\nSummary:\nAbstract: Fuzzers are computer programs that send other programs inputs that may fall outside the domain of expected values, thus revealing subtle bugs. DeepState is a testing framework that allows easy testing of C/C++ programs with sophisticated fuzzers, and supports multiple back-ends for testing. DeepState has been used to test critical C++ software, including Google’s leveldb. R has some simple random testers, but no coverage-driven fuzzers that learn to produce problematic inputs. We propose to create the R packages RcppDeepState and RcppDeepStateTools which will provide easy-to-use functions for using DeepState with R packages that use C/C++ code via Rcpp. This project will thus provide the first easy-to-use solution for R programmers that want to fuzz test their C/C++ code with existing tools such as AFL, and it will provide a framework for interfacing future coverage-driven fuzzers or symbolic execution tools. We also propose to use these new tools on a wide range of R packages in order to identify bugs in their C/C++ code.\nOne masters student will be recruited to implement this project during Jan-Dec 2020 at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. Interested students should apply by emailing a resume/CV along with a cover letter to project supervisors toby.hocking@nau.edu and alex.groce@nau.edu.\n\n\n\nFunded:\n$10,000\nProposed by:\nMikkel Meyer Andersen\nWebsite:\nhttps://github.com/r-cas/caracas/\nSummary:\nR’s ability to do symbolic mathematics is largely restricted to finding derivatives. There are many tasks involving symbolic math that are of interest to R users, e.g. inversion of symbolic matrices, limits and solving non-linear equations. Users must resort to other software for such tasks and many R users (especially outside of academia) do not readily have access to such software.\nThe Python library SymPy is open source, has a stable group of developers and is powerful. As such, R users can just switch to Python and SymPy for symbolic math. However it is often very convenient to stay in the same environment to use familiar syntax and to utilise available libraries (e.g. to generate problems using symbolic math together with the exams package or to first handle symbolic computations and then afterwards move on to a numerical evaluations of the results). We will achieve this by making SymPy functionality available for R users via an R package.\nCurrently only few R packages for doing symbolic mathematics are available: Two of these are Ryacas and rSymPy. Ryacas is built around Yacas, and although Yacas can solve many problems and is extensible, the community is relatively small and Yacas is not as powerful as SymPy for certain routine tasks (e.g. integration and solving equations). rSymPy on the other hand is based on technology that requires much technical work to install and use.\nThe website of the project is:\nhttps://github.com/r-cas/caracas/\nPlease contribute by testing, writing documentation, opening issues, submitting pull requests or something else!\n\n\n\nFunded:\n$9,000\nProposed by:\nLucas van der Meer, Robin Lovelace, Andrea Gilardi, Lorena Abad\nWebsite:\nhttps://luukvdmeer.github.io/sfnetworks/\nSummary:\nR is currently lacking a generally applicable, modern and easy-to-use way of handling all kinds of spatial networks. “Tidy spatial networks in R” aims to address this issue by developing and publishing the sfnetworks package. The package, and documentation around it, will provide a bridge between network analysis and spatial analysis communities. For this, an sfnetwork class that will work with both tidygraph and sf frameworks and functions. R-users will be encouraged to contribute and engage with the package development during a hackathon organized next to the eRum 2020.\n\n\n\nFunded:\n$4,000\nProposed by:\nMauricio Vargas Sepúlveda\nWebsite:\nhttps://github.com/pachamaltese/d3po\nSummary:\nR already features excellent visualization libraries such as D3 (via the r2d3 package), plotly or highcharter. However, though those enable the creation of great looking visualisations they have very steep learning curves, require understanding of JavaScript or rely on non-free software that might be out of reach for governments and NGOs. Our intention is to solve those problems by releasing d3po. It shall be an intermediate layer between the user and D3 by providing “templates”, enabling high quality interactive visualizations oriented to and designed to be used with Shiny and Rmarkdown, and also proving easy internationalization. Please join us, this needs D3 and R skilled minds!\n\n\n\nFunded:\n$6,000\nProposed by:\nEric Scott, Tamas Stirling\nWebsite:\nhttps://github.com/ropensci/webchem\nSummary:\nwebchem: accessing chemical information from the web\nA vast amount of chemical information is freely available on the internet. The data are used by millions of professionals around the world, for purposes like pharmaceutical research, chemical process design, or environmental impact assessment, to name a few. webchem is an R project that aims to help these professionals by providing a single point programmable access to all major chemical databases around the world. The project started in 2016 and currently supports more than 10 databases. If you are interested, join us and help us build the tool that biologists and chemists will absolutely love." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n\n\n\nFunded:\n$15,000\nProposed by:\nJulien Brun and Allison Horst\nSummary:\nExpanding the lterdatasampler Package addresses the need for accessible and relevant datasets in data science education. It aims to provide modern, curated, and approachable environmental data samples from the US Long Term Ecological Research Network (LTER) through the lterdatasampler R package. By offering datasets that save time for instructors, engage students with meaningful data, and foster discussions based on real-world questions.The package serves as a valuable resource for teaching introductory statistics and data science in R. The project seeks funding to expand the package to include data samples from all 28 LTER network sites, with the goal of modernizing course materials with real-world environmental datasets.\n\n\n\nFunded:\n$20,000\nProposed by:\nLaura Sangalli\nSummary:\nFemr: There is a need for implementing finite element methods (FEM) in R to solve partial differential equations (PDEs). PDEs are crucial mathematical tools used for modeling complex phenomena in various scientific and engineering fields. However, the absence of FEM implementations in R necessitates the reliance on external software, discouraging the statistical community from developing methods involving PDEs and hindering the learning of this essential mathematical tool. The goal of the project is to develop the femR package, which will provide a finite element basis for solving second-order linear elliptic PDEs on general two-dimensional spatial domains in R.\nThis package will complement the existing deSolve package and enable users to employ finite elements instead of finite differences for solving PDEs on more diverse spatial domains. The development process will include providing comprehensive examples and a final vignette to guide users in utilizing the package’s functionalities.\n\n\n\nFunded:\n$5,000\nProposed by:\nNicholas Tierney\nSummary:\nThe proposal for “Continuing to Improve R’s Ability to Visualise and Explore Missing Values” addresses missing values in data analysis. Missing values are often dropped by default in data analysis in various stages. There is often not even a warning displayed to alert the user of missing values being dropped or discarded. This means values can be dropped without the user knowing, leading to issues such as potential bias, where missing values might be occurring in high numbers in particular groups.\nThe proposal for the ISC-funded project addressed this problem in four parts:\n\nPart one: Initial evaluation of additional missing data visualizations\nPart two: Implementation of missing data visualizations\nPart three: Will provide tutorials and workflows.\nPart four: Future extensions and beyond\n\n\n\n\nFunded:\n$2,000\nProposed by:\nThiyanga Talagala\nSummary:\nThe Dengue Data Hub project helps addresses data packages related to Dengue. Dengue is a mosquito-borne viral disease that has spread fast throughout the world, primarily in urban and semi-urban regions. The goal of the Dengue Data Hub is to provide the research community with a unified dataset helpful for dengue research and reproducibility of research. The project proposes the creation of an R package for aggregating dengue data from several sources and the ability to share them in tidy format. Based on the proposal, there will also be tutorials and good documentation for using the “Dengue Data Hub” interface. This will motivate epidemiology researchers to utilize R to analyze their data." }, { - "objectID": "all-projects/previous-top-level-projects.html", - "href": "all-projects/previous-top-level-projects.html", - "title": "Previous Top Level Projects", + "objectID": "all-projects/2022-group-1.html#funded-isc-grants-2022-1", + "href": "all-projects/2022-group-1.html#funded-isc-grants-2022-1", + "title": "R Consortium", "section": "", - "text": "R Inclusion, Diversity, Equity and Accessibility (IDEA) was a group broadly considering how the R Consortium could best encourage and support diversity and inclusion in the R Community.\nhttps://github.com/RConsortium/RCDI-WG/tree/master\n\n\n\n\nR-Hub was a platform for simplifying and improving the R package development process.\nR-Hub assisted R package developers by providing facilities to test packages across multiple architectures, build binaries, and publish, distribute and maintain their packages. Developed by Gábor Csárdi, it was being leveraged by R package developers to improve the quality of their packages and to enable support for their packages across multiple architectures.\nhttps://github.com/r-hub." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n\n\n\nFunded:\n$15,000\nProposed by:\nJulien Brun and Allison Horst\nSummary:\nExpanding the lterdatasampler Package addresses the need for accessible and relevant datasets in data science education. It aims to provide modern, curated, and approachable environmental data samples from the US Long Term Ecological Research Network (LTER) through the lterdatasampler R package. By offering datasets that save time for instructors, engage students with meaningful data, and foster discussions based on real-world questions.The package serves as a valuable resource for teaching introductory statistics and data science in R. The project seeks funding to expand the package to include data samples from all 28 LTER network sites, with the goal of modernizing course materials with real-world environmental datasets.\n\n\n\nFunded:\n$20,000\nProposed by:\nLaura Sangalli\nSummary:\nFemr: There is a need for implementing finite element methods (FEM) in R to solve partial differential equations (PDEs). PDEs are crucial mathematical tools used for modeling complex phenomena in various scientific and engineering fields. However, the absence of FEM implementations in R necessitates the reliance on external software, discouraging the statistical community from developing methods involving PDEs and hindering the learning of this essential mathematical tool. The goal of the project is to develop the femR package, which will provide a finite element basis for solving second-order linear elliptic PDEs on general two-dimensional spatial domains in R.\nThis package will complement the existing deSolve package and enable users to employ finite elements instead of finite differences for solving PDEs on more diverse spatial domains. The development process will include providing comprehensive examples and a final vignette to guide users in utilizing the package’s functionalities.\n\n\n\nFunded:\n$5,000\nProposed by:\nNicholas Tierney\nSummary:\nThe proposal for “Continuing to Improve R’s Ability to Visualise and Explore Missing Values” addresses missing values in data analysis. Missing values are often dropped by default in data analysis in various stages. There is often not even a warning displayed to alert the user of missing values being dropped or discarded. This means values can be dropped without the user knowing, leading to issues such as potential bias, where missing values might be occurring in high numbers in particular groups.\nThe proposal for the ISC-funded project addressed this problem in four parts:\n\nPart one: Initial evaluation of additional missing data visualizations\nPart two: Implementation of missing data visualizations\nPart three: Will provide tutorials and workflows.\nPart four: Future extensions and beyond\n\n\n\n\nFunded:\n$2,000\nProposed by:\nThiyanga Talagala\nSummary:\nThe Dengue Data Hub project helps addresses data packages related to Dengue. Dengue is a mosquito-borne viral disease that has spread fast throughout the world, primarily in urban and semi-urban regions. The goal of the Dengue Data Hub is to provide the research community with a unified dataset helpful for dengue research and reproducibility of research. The project proposes the creation of an R package for aggregating dengue data from several sources and the ability to share them in tidy format. Based on the proposal, there will also be tutorials and good documentation for using the “Dengue Data Hub” interface. This will motivate epidemiology researchers to utilize R to analyze their data." }, { - "objectID": "all-projects/previous-top-level-projects.html#r-inclusion-diversity-equity-and-accessibility-idea", - "href": "all-projects/previous-top-level-projects.html#r-inclusion-diversity-equity-and-accessibility-idea", - "title": "Previous Top Level Projects", + "objectID": "all-projects/index.html", + "href": "all-projects/index.html", + "title": "Goal of ISC Grants Program", "section": "", - "text": "R Inclusion, Diversity, Equity and Accessibility (IDEA) was a group broadly considering how the R Consortium could best encourage and support diversity and inclusion in the R Community.\nhttps://github.com/RConsortium/RCDI-WG/tree/master" + "text": "The goal of the Infrastructure Steering Committee (the ISC) is to support projects that broadly help the R community. This might be software development, developing new teaching materials, documenting best practices, standardizing APIs or doing research. Currently, the ISC chiefly provides financial support for projects proposed by individuals or teams who have the skills to carry out the work, but we can also provide administrative support, promotion and some collaboration tools for groups who would like to study more ambitious projects.\nThe ISC generally funds two grant cycles per year. Cumulatively, we have awarded over $750k in community development grants over 5 years.\nInterested in strengthening the R community? Submit a Proposal. Please note, grants from the R Consortium are not adjusted to accommodate for internal institutional overhead.\n\n\nFor activities that are well defined and scoped, yet require funding to help bring to fruition, the ISC has established a grant fund. Twice yearly, the ISC awards grants for projects such as code development, workshops, infrastructure, and other projects to help sustain the R community.\nYou can learn more about the in-progress and completed funded projects. If you have a project needing funding, learn more about the grant funding process.\n\n\n\nFor community projects of importance to the R community and needing long-term support by R Consortium, the project and ISC can consider the project for long-term status. This gives the project guaranteed funding for 3 years, along with a voting seat on the ISC. Projects looking for this status will need to justify to the ISC why the project needs long-term funding, as well as submit a 3-year plan and budget for consideration. Top level projects get priority access to grant funds available.\nThree projects are currently Top Level Projects:\n\nDBI\nR-Ladies\nR User Group Support Program (RUGS)\n\nPrevious Top Level Projects" }, { - "objectID": "all-projects/previous-top-level-projects.html#r-hub", - "href": "all-projects/previous-top-level-projects.html#r-hub", - "title": "Previous Top Level Projects", + "objectID": "all-projects/index.html#funded-projects", + "href": "all-projects/index.html#funded-projects", + "title": "Goal of ISC Grants Program", "section": "", - "text": "R-Hub was a platform for simplifying and improving the R package development process.\nR-Hub assisted R package developers by providing facilities to test packages across multiple architectures, build binaries, and publish, distribute and maintain their packages. Developed by Gábor Csárdi, it was being leveraged by R package developers to improve the quality of their packages and to enable support for their packages across multiple architectures.\nhttps://github.com/r-hub." + "text": "For activities that are well defined and scoped, yet require funding to help bring to fruition, the ISC has established a grant fund. Twice yearly, the ISC awards grants for projects such as code development, workshops, infrastructure, and other projects to help sustain the R community.\nYou can learn more about the in-progress and completed funded projects. If you have a project needing funding, learn more about the grant funding process." }, { - "objectID": "all-projects/2018-group-1.html", - "href": "all-projects/2018-group-1.html", - "title": "R Consortium", + "objectID": "all-projects/index.html#top-level-projects", + "href": "all-projects/index.html#top-level-projects", + "title": "Goal of ISC Grants Program", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n\n\n\nFunded:\n$14,000\nProposed by:\nJulie Josse\nWebsite:\nhttps://cran.r-project.org/web/views/MissingData.html\nSummary:\nThe objective is to create a reference platform on the theme of missing data management and to federate contributors. This platform will be the occasion to list the existing packages, the available literature as well as the tutorials that allow to analyze data with missing data. New work on the subject can be easily integrated and we will create examples of analysis workflows with missing data. Anyone who would like to contribute to this exciting project can contact us.\n\n\n\nFunded:\n$10,000\nProposed by:\nFrançois Michonneau\nWebsite:\nhttps://datacarpentry.org/R-ecology-lesson/ and http://swcarpentry.github.io/r-novice-gapminder/\nSummary:\nThe first-class implementation of literate programming in R is one of the reasons for its success. While the seamless integration of code and text made possible by Sweave, knitr, and rmarkdown was designed for writing reproducible reports and documentation, it has also enabled the creation of teaching materials that combine text, code examples, exercises and solutions. However, while people creating lessons in RMarkdown are familiar with R, they often do not have a background in education or UX design. Therefore, they must not only assemble curriculum, but also find a way to present the content effectively and accessibly to both learners and instructors. As the model of open source development is being adapted to the creation of open educational resources, the difficulty to share materials due to a lack of consistency in their construction hinders the collaborative development of these resources.\nThis project will develop an R package that will facilitate the development of consistent teaching resources. It will encourage the use of tools and lesson structure that support and improve learning. By providing the technical framework for developing quality teaching materials, we seek to encourage collaborative lesson development by letting authors focus on the content rather than the formatting, while providing a more consistent experience for the learners.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDBI, R’s database interface, is a set of methods declared in the DBI R package. Communication with the database is implemented by DBI backends, packages that import DBI and implement its methods. A common interface is helpful for both users and backend implementers.\nThe “Maintaining DBI” is a follow-up project to two previous projects supported by the R Consortium, and is mostly about providing ongoing maintenance and support for DBI, the DBItest test suite, and the three backends to open-source databases (RSQLite, RMariaDB and RPostgres) that have been implemented as part of the previous projects.\n\n\n\nFunded:\n$62,400\nProposed by:\nJeroen Ooms\nWebsite:\nhttps://github.com/r-hub/homebrew-cran#how-to-use\nSummary:\nThe majority of R users rely on precompiled installers and binary packages for Windows and MacOS that are made available through CRAN. This project seeks to improve and maintain tools for providing such binaries, and relieve some of the dependence on CRAN maintainers and R-core members for doing so. On Windows we will upgrade the Rtools compiler toolchain, and provide up-to-date Windows builds for the many external C/C++ libraries used by CRAN packages. For MacOS we will expand the r-hub “homebrew-cran” tap with formulas that are needed by CRAN packages but not available from upstream homebrew-core. Eventually we want to lay the foundation for a reproducible build system that is low maintenance, automated as much as possible, and which could be used by CRAN and other R package repositories.\n\n\n\nFunded:\n$4,000\nProposed by:\nLyn Taylor (on behalf of PSI AIMS SIG)\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe documentation available for R packages currently widely varies. The Statisticians in the Pharmaceutical Industry (PSI) Application and Implementation of Methodologies in Statistics (AIMS) Special Interest Group (SIG) will collaborate with the R-Consortium and representatives from pharmaceutical companies on the setting up of an online repository /web portal, where validation which is of regulatory standard for R packages can be submitted and stored for free use. Companies (or individual R users) would still be liable to make their own assessment on whether the validation is suitable for their own use, however the online repository would serve as a portal for sharing existing regulatory standard validation documentation.\n\n\n\nFunded:\n$4,000\nProposed by:\nAri Lamstein\nWebsite:\nhttps://github.com/RConsortium/censusguide\nSummary:\nThe Proposal to Create an R Consortium Working Group Focused on US Census Data aims to make life easier for R programmers who work with data from the US Census Bureau. It will create a working group where R users working with census data can cooperate under the guidance of the Census Bureau. Additionally, it will publish a guide to working with Census data in R that aims to help R programmers a) select packages that meet their needs and b) navigate the various data sets that the Census Bureau publishes.\n\n\n\nFunded:\n$772\nProposed by:\nJohn C Nash\nWebsite:\nhttps://gitlab.com/nashjc/histoRicalg\nSummary:\nMany of the algorithms making up the numerical building-blocks of R were developed several decades ago, particularly in Fortran. Some were translated into C for use by R. Only a modest proportion of R users today are fluent in these languages, and many original authors are no longer active. Yet some of these codes may have bugs or need adjustment for new system capabilities. The histoRicalg project aims to document and test such codes that are still part of R, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future. Our initial task is to establish a ***Working Group on Algorithms Used in R*** and add material to a website/wiki currently at https://gitlab.com/nashjc/histoRicalg. Interested workers are invited to contact John Nash." + "text": "For community projects of importance to the R community and needing long-term support by R Consortium, the project and ISC can consider the project for long-term status. This gives the project guaranteed funding for 3 years, along with a voting seat on the ISC. Projects looking for this status will need to justify to the ISC why the project needs long-term funding, as well as submit a 3-year plan and budget for consideration. Top level projects get priority access to grant funds available.\nThree projects are currently Top Level Projects:\n\nDBI\nR-Ladies\nR User Group Support Program (RUGS)\n\nPrevious Top Level Projects" }, { - "objectID": "all-projects/2018-group-1.html#funded-isc-grants-2018-1", - "href": "all-projects/2018-group-1.html#funded-isc-grants-2018-1", + "objectID": "all-projects/2016-group-1.html", + "href": "all-projects/2016-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n\n\n\nFunded:\n$14,000\nProposed by:\nJulie Josse\nWebsite:\nhttps://cran.r-project.org/web/views/MissingData.html\nSummary:\nThe objective is to create a reference platform on the theme of missing data management and to federate contributors. This platform will be the occasion to list the existing packages, the available literature as well as the tutorials that allow to analyze data with missing data. New work on the subject can be easily integrated and we will create examples of analysis workflows with missing data. Anyone who would like to contribute to this exciting project can contact us.\n\n\n\nFunded:\n$10,000\nProposed by:\nFrançois Michonneau\nWebsite:\nhttps://datacarpentry.org/R-ecology-lesson/ and http://swcarpentry.github.io/r-novice-gapminder/\nSummary:\nThe first-class implementation of literate programming in R is one of the reasons for its success. While the seamless integration of code and text made possible by Sweave, knitr, and rmarkdown was designed for writing reproducible reports and documentation, it has also enabled the creation of teaching materials that combine text, code examples, exercises and solutions. However, while people creating lessons in RMarkdown are familiar with R, they often do not have a background in education or UX design. Therefore, they must not only assemble curriculum, but also find a way to present the content effectively and accessibly to both learners and instructors. As the model of open source development is being adapted to the creation of open educational resources, the difficulty to share materials due to a lack of consistency in their construction hinders the collaborative development of these resources.\nThis project will develop an R package that will facilitate the development of consistent teaching resources. It will encourage the use of tools and lesson structure that support and improve learning. By providing the technical framework for developing quality teaching materials, we seek to encourage collaborative lesson development by letting authors focus on the content rather than the formatting, while providing a more consistent experience for the learners.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDBI, R’s database interface, is a set of methods declared in the DBI R package. Communication with the database is implemented by DBI backends, packages that import DBI and implement its methods. A common interface is helpful for both users and backend implementers.\nThe “Maintaining DBI” is a follow-up project to two previous projects supported by the R Consortium, and is mostly about providing ongoing maintenance and support for DBI, the DBItest test suite, and the three backends to open-source databases (RSQLite, RMariaDB and RPostgres) that have been implemented as part of the previous projects.\n\n\n\nFunded:\n$62,400\nProposed by:\nJeroen Ooms\nWebsite:\nhttps://github.com/r-hub/homebrew-cran#how-to-use\nSummary:\nThe majority of R users rely on precompiled installers and binary packages for Windows and MacOS that are made available through CRAN. This project seeks to improve and maintain tools for providing such binaries, and relieve some of the dependence on CRAN maintainers and R-core members for doing so. On Windows we will upgrade the Rtools compiler toolchain, and provide up-to-date Windows builds for the many external C/C++ libraries used by CRAN packages. For MacOS we will expand the r-hub “homebrew-cran” tap with formulas that are needed by CRAN packages but not available from upstream homebrew-core. Eventually we want to lay the foundation for a reproducible build system that is low maintenance, automated as much as possible, and which could be used by CRAN and other R package repositories.\n\n\n\nFunded:\n$4,000\nProposed by:\nLyn Taylor (on behalf of PSI AIMS SIG)\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe documentation available for R packages currently widely varies. The Statisticians in the Pharmaceutical Industry (PSI) Application and Implementation of Methodologies in Statistics (AIMS) Special Interest Group (SIG) will collaborate with the R-Consortium and representatives from pharmaceutical companies on the setting up of an online repository /web portal, where validation which is of regulatory standard for R packages can be submitted and stored for free use. Companies (or individual R users) would still be liable to make their own assessment on whether the validation is suitable for their own use, however the online repository would serve as a portal for sharing existing regulatory standard validation documentation.\n\n\n\nFunded:\n$4,000\nProposed by:\nAri Lamstein\nWebsite:\nhttps://github.com/RConsortium/censusguide\nSummary:\nThe Proposal to Create an R Consortium Working Group Focused on US Census Data aims to make life easier for R programmers who work with data from the US Census Bureau. It will create a working group where R users working with census data can cooperate under the guidance of the Census Bureau. Additionally, it will publish a guide to working with Census data in R that aims to help R programmers a) select packages that meet their needs and b) navigate the various data sets that the Census Bureau publishes.\n\n\n\nFunded:\n$772\nProposed by:\nJohn C Nash\nWebsite:\nhttps://gitlab.com/nashjc/histoRicalg\nSummary:\nMany of the algorithms making up the numerical building-blocks of R were developed several decades ago, particularly in Fortran. Some were translated into C for use by R. Only a modest proportion of R users today are fluent in these languages, and many original authors are no longer active. Yet some of these codes may have bugs or need adjustment for new system capabilities. The histoRicalg project aims to document and test such codes that are still part of R, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future. Our initial task is to establish a ***Working Group on Algorithms Used in R*** and add material to a website/wiki currently at https://gitlab.com/nashjc/histoRicalg. Interested workers are invited to contact John Nash." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training\n\n\n\n\nFunded:\n$10,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://github.com/RConsortium/Distributed-Computing-WG\nSummary:\nMany Big Data platforms expose R-based interfaces that lack standardization and are therefore difficult to learn. This project will develop a common framework to simplify and standardize how users program distributed applications in R, ultimately reducing duplication of effort.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDatabase access is an important cornerstone of the R ecosystem, but today’s specifications – data type transformation, return values, error conditions – remain vague and result in data analysis errors. This project aims to improve database access in R so that porting code is simplified and less prone to error.\n\n\n\nFunded:\n$10,000\nProposed by:\nMark Hornick\nWebsite:\nhttps://riotworkshop.github.io/\nSummary:\nRIOT 2016 is a one-day workshop to unite R language developers, identify R language development and tooling opportunities, increase involvement of the R user community and more.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Cotton\nWebsite:\nhttps://github.com/RL10N/RL10N and https://libraries.io/github/RL10N\nSummary:\nAlthough the R language is used globally, very few R packages are available in languages other than English. The RL10N project will make it easier for R developers to include translations in their own packages.\n\n\n\nFunded:\n$10,000\nProposed by:\nStephanie Locke\nWebsite:\nhttps://github.com/satrdays\nSummary:\n“SatRDays” are community-led, regional conferences to support collaboration, networking and innovation within the R community. Initially three events will be hosted, with plans for additional meet-ups as the R user base grows.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://github.com/r-spatial/sf/\nSummary:\nUsing the “Simple Features” standard supported by the Open Geospatial Consortium and the International Organization for Standardization, this tool will simplify analysis on modern geospatial data.\n\n\n\nFunded:\n$10,000\nProposed by:\nLaurent Gatto\nWebsite:\nSummary:\nThis two-day in-person training course will introduce the basics of R programming and address the growing demand for training resources for the R language." }, { - "objectID": "all-projects/2023-group-2.html", - "href": "all-projects/2023-group-2.html", + "objectID": "all-projects/2016-group-1.html#funded-isc-grants-2016-1", + "href": "all-projects/2016-group-1.html#funded-isc-grants-2016-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n\n\n\nFunded:\n$1,000\nProposed by:\nBinod Jung Bogati, R User Group Nepal\nSummary:\nThis project aims to bridge language gaps within the R community by translating essential R resources into Nepali. This inclusivity will attract diverse talents and perspectives, fostering innovation and growth within the community. We are working with the R User Group Nepal community for a series of Translation hackathons and follow-up meetings. This initiative started before the R Project Sprint 2023 with the assistance of the R User Group Nepal.\n\n\n\nFunded:\n$1,306.80\nProposed by:\nDan Wilson, The Data Collective Consulting Pty Ltd\nSummary:\nTo help create a place for social connection to the broad R community that isn’t focussed on any specific subgroup of r users, we’d like funding to help establish an RStats Mastodon server. The goal would be to be funded for the first year with a grant from the R Consortium and develop a pathway for user funding like other Mastodon servers.\n\n\n\nFunded:\n$20,800\nProposed by:\nElio Campitelli\nSummary:\nWe propose a system in which either package maintainers or community members could create translation modules of specific packages. Users would then be able to install those translation modules and browse their documentation. By default, help() would display the documentation in the user’s preferred language if available, and fall-back to the canonical documentation otherwise. It would also include a link to the canonical documentation and warnings if translations are not up to date.\n\n\n\nFunded:\n$5,000\nProposed by:\nMalcolm Barrett\nSummary:\nIn response to a growing demand for accessible and comprehensive educational resources in causal inference within the R community, we propose the development of a Causal Inference In a Box course. Leveraging a “teach the teacher” model and building on the successful Data Science in a Box template, we will provide instructional materials, including slide decks, lab exercises, and assessments, all meticulously designed to facilitate effective learning. Additionally, we are committed to ensuring inclusivity by offering alternative formats for diverse learning preferences. This comprehensive course, supported by dedicated pedagogical software tools, will revolutionize how practitioners approach causal inference in the R environment, ultimately enhancing the quality and reliability of their research and analyses.\n\n\n\nFunded:\n$4,000\nProposed by:\nDianne Cook\nSummary:\nThe plan for the use of this funding is to check and enhance the accessibility of published R Journal articles, and to develop tools to help authors and editors ensure that new R Journal articles are at the cutting edge of accessibility. Checking the published articles will involve manual work to read each article and add meaningful alt text to each image. Screen reader accessibility will be checked using available screen readers, with advice from team member Jonathan Godfrey. Jonathan has already used the screen reader JAWS to read a sample of articles converted from the legacy format and confirms that he can now access 90% of the R Journal content as opposed to 10% previously! We will also work closely with the current editors of the R Journal to assist with checking new submissions, especially those produced with the legacy template. This will also help ensure that new articles have accessible content, with appropriate alt text.\n\n\n\nFunded:\n$40,000\nProposed by:\nJeroen Ooms, rOpenSci\nSummary:\nWe are interested to collaborate with the R consortium to make R-universe a top-level ISC in order to get a variety of stakeholders involved, grow adoption and community ownership, and to be able to guarantee the continued availability of the service to the R community. R-universe has the potential to become the central place where one can find everything the R community has to offer, complementing CRAN with open infrastructure that can continuously be adapted to new needs. Moreover, existing r-hub containers for extra checks can be integrated to make these tools more accessible. We hope to become a flagship project for the consortium, and an example of a mutually beneficial collaboration between its members and the R community.\n\n\n\nFunded:\n$24,000\nProposed by:\nAndreas Neudecker, INWT Statistics GmbH\nSummary:\nThe goal of this project is to create a robust and efficient Kafka client library for R that supports essential functionalities to communicate with a Kafka cluster. The proposed Kafka client for R will be built by creating a wrapper around the C++ librdkafka library, which is maintained and developed by Confluent which was founded by the original developers of Kafka. This approach is already common and produces reliable and stable releases in multiple other programming languages (Python, Rust, Go, …). There are packages for the major linux package managers (Debian, RPM, Gentoo) and it also runs on MacOS X and Windows." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training\n\n\n\n\nFunded:\n$10,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://github.com/RConsortium/Distributed-Computing-WG\nSummary:\nMany Big Data platforms expose R-based interfaces that lack standardization and are therefore difficult to learn. This project will develop a common framework to simplify and standardize how users program distributed applications in R, ultimately reducing duplication of effort.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDatabase access is an important cornerstone of the R ecosystem, but today’s specifications – data type transformation, return values, error conditions – remain vague and result in data analysis errors. This project aims to improve database access in R so that porting code is simplified and less prone to error.\n\n\n\nFunded:\n$10,000\nProposed by:\nMark Hornick\nWebsite:\nhttps://riotworkshop.github.io/\nSummary:\nRIOT 2016 is a one-day workshop to unite R language developers, identify R language development and tooling opportunities, increase involvement of the R user community and more.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Cotton\nWebsite:\nhttps://github.com/RL10N/RL10N and https://libraries.io/github/RL10N\nSummary:\nAlthough the R language is used globally, very few R packages are available in languages other than English. The RL10N project will make it easier for R developers to include translations in their own packages.\n\n\n\nFunded:\n$10,000\nProposed by:\nStephanie Locke\nWebsite:\nhttps://github.com/satrdays\nSummary:\n“SatRDays” are community-led, regional conferences to support collaboration, networking and innovation within the R community. Initially three events will be hosted, with plans for additional meet-ups as the R user base grows.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://github.com/r-spatial/sf/\nSummary:\nUsing the “Simple Features” standard supported by the Open Geospatial Consortium and the International Organization for Standardization, this tool will simplify analysis on modern geospatial data.\n\n\n\nFunded:\n$10,000\nProposed by:\nLaurent Gatto\nWebsite:\nSummary:\nThis two-day in-person training course will introduce the basics of R programming and address the growing demand for training resources for the R language." }, { - "objectID": "all-projects/2023-group-2.html#funded-isc-grants-2023-2", - "href": "all-projects/2023-group-2.html#funded-isc-grants-2023-2", + "objectID": "all-projects/2017-group-1.html", + "href": "all-projects/2017-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n\n\n\nFunded:\n$1,000\nProposed by:\nBinod Jung Bogati, R User Group Nepal\nSummary:\nThis project aims to bridge language gaps within the R community by translating essential R resources into Nepali. This inclusivity will attract diverse talents and perspectives, fostering innovation and growth within the community. We are working with the R User Group Nepal community for a series of Translation hackathons and follow-up meetings. This initiative started before the R Project Sprint 2023 with the assistance of the R User Group Nepal.\n\n\n\nFunded:\n$1,306.80\nProposed by:\nDan Wilson, The Data Collective Consulting Pty Ltd\nSummary:\nTo help create a place for social connection to the broad R community that isn’t focussed on any specific subgroup of r users, we’d like funding to help establish an RStats Mastodon server. The goal would be to be funded for the first year with a grant from the R Consortium and develop a pathway for user funding like other Mastodon servers.\n\n\n\nFunded:\n$20,800\nProposed by:\nElio Campitelli\nSummary:\nWe propose a system in which either package maintainers or community members could create translation modules of specific packages. Users would then be able to install those translation modules and browse their documentation. By default, help() would display the documentation in the user’s preferred language if available, and fall-back to the canonical documentation otherwise. It would also include a link to the canonical documentation and warnings if translations are not up to date.\n\n\n\nFunded:\n$5,000\nProposed by:\nMalcolm Barrett\nSummary:\nIn response to a growing demand for accessible and comprehensive educational resources in causal inference within the R community, we propose the development of a Causal Inference In a Box course. Leveraging a “teach the teacher” model and building on the successful Data Science in a Box template, we will provide instructional materials, including slide decks, lab exercises, and assessments, all meticulously designed to facilitate effective learning. Additionally, we are committed to ensuring inclusivity by offering alternative formats for diverse learning preferences. This comprehensive course, supported by dedicated pedagogical software tools, will revolutionize how practitioners approach causal inference in the R environment, ultimately enhancing the quality and reliability of their research and analyses.\n\n\n\nFunded:\n$4,000\nProposed by:\nDianne Cook\nSummary:\nThe plan for the use of this funding is to check and enhance the accessibility of published R Journal articles, and to develop tools to help authors and editors ensure that new R Journal articles are at the cutting edge of accessibility. Checking the published articles will involve manual work to read each article and add meaningful alt text to each image. Screen reader accessibility will be checked using available screen readers, with advice from team member Jonathan Godfrey. Jonathan has already used the screen reader JAWS to read a sample of articles converted from the legacy format and confirms that he can now access 90% of the R Journal content as opposed to 10% previously! We will also work closely with the current editors of the R Journal to assist with checking new submissions, especially those produced with the legacy template. This will also help ensure that new articles have accessible content, with appropriate alt text.\n\n\n\nFunded:\n$40,000\nProposed by:\nJeroen Ooms, rOpenSci\nSummary:\nWe are interested to collaborate with the R consortium to make R-universe a top-level ISC in order to get a variety of stakeholders involved, grow adoption and community ownership, and to be able to guarantee the continued availability of the service to the R community. R-universe has the potential to become the central place where one can find everything the R community has to offer, complementing CRAN with open infrastructure that can continuously be adapted to new needs. Moreover, existing r-hub containers for extra checks can be integrated to make these tools more accessible. We hope to become a flagship project for the consortium, and an example of a mutually beneficial collaboration between its members and the R community.\n\n\n\nFunded:\n$24,000\nProposed by:\nAndreas Neudecker, INWT Statistics GmbH\nSummary:\nThe goal of this project is to create a robust and efficient Kafka client library for R that supports essential functionalities to communicate with a Kafka cluster. The proposed Kafka client for R will be built by creating a wrapper around the C++ librdkafka library, which is maintained and developed by Confluent which was founded by the original developers of Kafka. This approach is already common and produces reliable and stable releases in multiple other programming languages (Python, Rust, Go, …). There are packages for the major linux package managers (Debian, RPM, Gentoo) and it also runs on MacOS X and Windows." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n\n\n\nFunded:\n$15,000\nProposed by:\nDirk Eddelbuettel\nSummary:\nThis project proposes to take the creation of binary Linux packages to the next level by providing R-Hub and eventually CRAN with the ability to deliver directly installable binary packages with properly-resolved dependencies. This will allow large-scale automated use of CRAN packages anywhere: laptops, desktops, servers, cluster farms and cloud-based deployments. The project would like to hear from anyone who could possibly host a dedicated server in a rack for long term use.\n\n\n\nFunded:\n$12,000\nProposed by:\nJeroen Ooms\nSummary:\nWhen installing CRAN packages, Windows and MacOS users often rely on binary packages that contain precompiled source code and any required external C/C++ libraries. By eliminating the need to setup a full compiler environment or manage external libraries this tremendously improves the usability of R on these platforms. Our project will improve the system by adapting the popular homebrew system to facilitate static linking of external libraries\n\n\n\nFunded:\n$32,000\nProposed by:\nHeather Turner\nWebsite:\nhttps://github.com/satrdays\nSummary:\nThis project will evaluate a number of open source conference management systems to assess their suitability for use with useR! and satRdays. Test versions of these systems will be set up to test their functionality and ease of use for all roles (systems administrator, local organizer, program chair, reviewer, conference participant). A system will be selected and a production system set up, with a view to be ready for useR! 2018 and future satRdays events.\n\n\n\nFunded:\n$15,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://wiki.r-consortium.org/view/Distributed_Computing_Working_Group and https://github.com/vertica/ddR/wiki/Design\nSummary:\nThe ISC’s Distributed Computing Working Group explores ways of enabling distributed computing in R. One of its outputs, the CRAN package ddR, defines an idiomatic API that abstracts different distributed computing engines, such as DistributedR and potentially Spark and TensorFlow. The goal of the project is to enable R users to interact with familiar data structures and write code that is portable across distributed systems. The working group will use this R Consortium grant to fund an internship to help improve ddR and implement support for one or more additional backends. Please contact Michael Lawrence to apply or request additional information.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nGetting data in and out of R is an important part of a statistician’s or data scientist’s work. If the data reside in a database, this is best done with a backend to DBI, R’s native DataBase Interface. The ongoing “Improving DBI” project supports the specification of DBI, both in prose and as an automated test, and also the adaptation of the `RSQLite` package to these specs. This follow-up project aims at implementing modern, fully spec-compliant DBI backends to two major open-source RDBMS, MySQL/MariaDB and PostgreSQL.\n\n\n\nFunded:\n$25,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://forwards.github.io/edu/workshops/\nSummary:\nThe proportion of female package authors and maintainers has remained persistently low, at best at 15%, despite 20 years of the R project’s existence. This project will conduct a grassroots effort to increase the participation of women in the R community. One day package development workshops for women engaged in research will be held in Melbourne, Australia and Auckland, New Zealand in 2017, and at locations yet to be determined in the USA and Europe in 2018. Additionally, one day workshops for teenage girls focused on building Shiny apps will be developed to encourage an interest in programming. These will be rolled out in the same locations as the women’s workshops. All materials developed will be made available under a Creative Commons share-alike license on the Forwards website (http://forwards.github.io).\n\n\n\nFunded:\n$11,000\nProposed by:\nKirill Müller\nWebsite:\nhttps://github.com/krlmlr/profile and https://cran.r-project.org/web/packages/profile/index.html\nSummary:\nR has excellent facilities for profiling R code: the main entry point is the [`Rprof()`](https://www.rdocumentation.org/packages/utils/versions/3.3.2/topics/Rprof) function that starts an execution mode where the R call stack is sampled periodically, optionally at source line level, and written to a file. Profiling results can be analyzed with `summaryRprof()`, or visualized using the `profvis`, `aprof`, or `GUIProfiler` packages. However, the execution time of native code is only available in bulk, without detailed source information. This project aims at bridging this gap with a drop-in replacement to `Rprof()` that records call stacks and memory usage information at both R and native levels, and later commingles them to present a unified view to the user.\n\n\n\nFunded:\n$11,200\nProposed by:\nHeidi Seibold\nSummary:\nSchool of Data is a network of data literacy practitioners, both organizations and individuals, implementing training and other data literacy activities in their respective countries and regions. Members of School of Data work to empower civil society organizations (CSOs), journalists, civil servants and citizens with the skills they need to use data effectively in their efforts to create better, more equitable and more sustainable societies Our R consortium will develop learning materials about R for journalists, with a focus on making them accessible and relevant to journalists from various countries. As a consequence, our content will use country-relevant examples and will be translated in several languages (English, French, Spanish, German).\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://cran.r-project.org/web/packages/stars/index.html\nSummary:\nSpatiotemporal and raster data often come as dense, two-dimensional arrays while remote sensing and climate model data are often presented as higher dimensional arrays. Data sets of this kind often do not fit in main memory. This project will make it easier to handle such data with R by using dplyr-style, pipe-based workflows, and also consider the case where the data reside remotely, in a cloud environment. Questions and offers to support are welcome through issues at: https://github.com/edzer/stars" }, { - "objectID": "all-projects/2020-group-2.html", - "href": "all-projects/2020-group-2.html", + "objectID": "all-projects/2017-group-1.html#funded-isc-grants-2017-1", + "href": "all-projects/2017-group-1.html#funded-isc-grants-2017-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n\n\n\nFunded:\n$46,800\nProposed by:\nJeroen Ooms\nSummary:\nAs of R 4.0.0 (released April 2020), R for Windows uses a brand new toolchain bundle called rtools40. This version upgrades the mingw-gcc toolchains to version 8.3.0, and introduces a powerful new build system based on the widely used msys2 platform, which makes it easier to maintain R itself, as well as system libraries needed for developing R and R-packages.\nThe current project seeks to build out this system to improve tooling for building and debugging on Windows, and move towards a scalable build infrastructure, which is transparent, extensible, and fully automated. Thereby we can empower development on Windows, and support further growth of the R ecosystem while relieving work for CRAN and R-core members.\n\n\n\nFunded:\n$9,688\nProposed by:\nChun Fung Kwok\nWebsite:\nhttps://github.com/kcf-jackson/sketch and https://cran.r-project.org/package=sketch\nSummary:\nThis project aims to make creating flexible interactive visualisation accessible to a wider R community. By implementing an R-to-JavaScript transpiler, i.e. a program that translates R code into JavaScript code, it lets R users develop JavaScript(JS) applications using solely the R syntax. This eliminates the need to pick up an entire new language, makes it easy for R users to learn and experiment with JS technologies and gives direct and full access to all existing JS libraries. The transpiler is distributed as a regular R package, and it can be used standalone or to complement existing packages, including Rmarkdown, shiny and V8." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n\n\n\nFunded:\n$15,000\nProposed by:\nDirk Eddelbuettel\nSummary:\nThis project proposes to take the creation of binary Linux packages to the next level by providing R-Hub and eventually CRAN with the ability to deliver directly installable binary packages with properly-resolved dependencies. This will allow large-scale automated use of CRAN packages anywhere: laptops, desktops, servers, cluster farms and cloud-based deployments. The project would like to hear from anyone who could possibly host a dedicated server in a rack for long term use.\n\n\n\nFunded:\n$12,000\nProposed by:\nJeroen Ooms\nSummary:\nWhen installing CRAN packages, Windows and MacOS users often rely on binary packages that contain precompiled source code and any required external C/C++ libraries. By eliminating the need to setup a full compiler environment or manage external libraries this tremendously improves the usability of R on these platforms. Our project will improve the system by adapting the popular homebrew system to facilitate static linking of external libraries\n\n\n\nFunded:\n$32,000\nProposed by:\nHeather Turner\nWebsite:\nhttps://github.com/satrdays\nSummary:\nThis project will evaluate a number of open source conference management systems to assess their suitability for use with useR! and satRdays. Test versions of these systems will be set up to test their functionality and ease of use for all roles (systems administrator, local organizer, program chair, reviewer, conference participant). A system will be selected and a production system set up, with a view to be ready for useR! 2018 and future satRdays events.\n\n\n\nFunded:\n$15,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://wiki.r-consortium.org/view/Distributed_Computing_Working_Group and https://github.com/vertica/ddR/wiki/Design\nSummary:\nThe ISC’s Distributed Computing Working Group explores ways of enabling distributed computing in R. One of its outputs, the CRAN package ddR, defines an idiomatic API that abstracts different distributed computing engines, such as DistributedR and potentially Spark and TensorFlow. The goal of the project is to enable R users to interact with familiar data structures and write code that is portable across distributed systems. The working group will use this R Consortium grant to fund an internship to help improve ddR and implement support for one or more additional backends. Please contact Michael Lawrence to apply or request additional information.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nGetting data in and out of R is an important part of a statistician’s or data scientist’s work. If the data reside in a database, this is best done with a backend to DBI, R’s native DataBase Interface. The ongoing “Improving DBI” project supports the specification of DBI, both in prose and as an automated test, and also the adaptation of the `RSQLite` package to these specs. This follow-up project aims at implementing modern, fully spec-compliant DBI backends to two major open-source RDBMS, MySQL/MariaDB and PostgreSQL.\n\n\n\nFunded:\n$25,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://forwards.github.io/edu/workshops/\nSummary:\nThe proportion of female package authors and maintainers has remained persistently low, at best at 15%, despite 20 years of the R project’s existence. This project will conduct a grassroots effort to increase the participation of women in the R community. One day package development workshops for women engaged in research will be held in Melbourne, Australia and Auckland, New Zealand in 2017, and at locations yet to be determined in the USA and Europe in 2018. Additionally, one day workshops for teenage girls focused on building Shiny apps will be developed to encourage an interest in programming. These will be rolled out in the same locations as the women’s workshops. All materials developed will be made available under a Creative Commons share-alike license on the Forwards website (http://forwards.github.io).\n\n\n\nFunded:\n$11,000\nProposed by:\nKirill Müller\nWebsite:\nhttps://github.com/krlmlr/profile and https://cran.r-project.org/web/packages/profile/index.html\nSummary:\nR has excellent facilities for profiling R code: the main entry point is the [`Rprof()`](https://www.rdocumentation.org/packages/utils/versions/3.3.2/topics/Rprof) function that starts an execution mode where the R call stack is sampled periodically, optionally at source line level, and written to a file. Profiling results can be analyzed with `summaryRprof()`, or visualized using the `profvis`, `aprof`, or `GUIProfiler` packages. However, the execution time of native code is only available in bulk, without detailed source information. This project aims at bridging this gap with a drop-in replacement to `Rprof()` that records call stacks and memory usage information at both R and native levels, and later commingles them to present a unified view to the user.\n\n\n\nFunded:\n$11,200\nProposed by:\nHeidi Seibold\nSummary:\nSchool of Data is a network of data literacy practitioners, both organizations and individuals, implementing training and other data literacy activities in their respective countries and regions. Members of School of Data work to empower civil society organizations (CSOs), journalists, civil servants and citizens with the skills they need to use data effectively in their efforts to create better, more equitable and more sustainable societies Our R consortium will develop learning materials about R for journalists, with a focus on making them accessible and relevant to journalists from various countries. As a consequence, our content will use country-relevant examples and will be translated in several languages (English, French, Spanish, German).\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://cran.r-project.org/web/packages/stars/index.html\nSummary:\nSpatiotemporal and raster data often come as dense, two-dimensional arrays while remote sensing and climate model data are often presented as higher dimensional arrays. Data sets of this kind often do not fit in main memory. This project will make it easier to handle such data with R by using dplyr-style, pipe-based workflows, and also consider the case where the data reside remotely, in a cloud environment. Questions and offers to support are welcome through issues at: https://github.com/edzer/stars" }, { - "objectID": "all-projects/2020-group-2.html#funded-isc-grants-2020-2", - "href": "all-projects/2020-group-2.html#funded-isc-grants-2020-2", - "title": "R Consortium", + "objectID": "all-projects/funded-projects.html", + "href": "all-projects/funded-projects.html", + "title": "Recipients of ISC Grants", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n\n\n\nFunded:\n$46,800\nProposed by:\nJeroen Ooms\nSummary:\nAs of R 4.0.0 (released April 2020), R for Windows uses a brand new toolchain bundle called rtools40. This version upgrades the mingw-gcc toolchains to version 8.3.0, and introduces a powerful new build system based on the widely used msys2 platform, which makes it easier to maintain R itself, as well as system libraries needed for developing R and R-packages.\nThe current project seeks to build out this system to improve tooling for building and debugging on Windows, and move towards a scalable build infrastructure, which is transparent, extensible, and fully automated. Thereby we can empower development on Windows, and support further growth of the R ecosystem while relieving work for CRAN and R-core members.\n\n\n\nFunded:\n$9,688\nProposed by:\nChun Fung Kwok\nWebsite:\nhttps://github.com/kcf-jackson/sketch and https://cran.r-project.org/package=sketch\nSummary:\nThis project aims to make creating flexible interactive visualisation accessible to a wider R community. By implementing an R-to-JavaScript transpiler, i.e. a program that translates R code into JavaScript code, it lets R users develop JavaScript(JS) applications using solely the R syntax. This eliminates the need to pick up an entire new language, makes it easy for R users to learn and experiment with JS technologies and gives direct and full access to all existing JS libraries. The transpiler is distributed as a regular R package, and it can be used standalone or to complement existing packages, including Rmarkdown, shiny and V8." + "text": "Recipients of ISC Grants\n2024 (group 1)\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n2023 (group 2)\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nCausal Inference in a Box\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n2023 (group 1)\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n2022 (group 2)\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n2022 (group 1)\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n2021 (group 2)\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n2021 (group 1)\n\nAccounting/Auditing Gap-Analysis\nExtendr - Rust extensions for R.\nGoogle Earth Engine with R\nImproving Translations in R\nMinimizing wastage of blood products\nR for Engineering Applications\nSetting up an R-Girls-Schools Network\ndeposits: Deposit Research Data Anywhere\n\n2020 (group 2)\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n2020 (group 1)\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n2019 (group 2)\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n2019 (group 1)\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n2018 (group 2)\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n2018 (group 1)\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n2017 (group 2)\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n2017 (group 1)\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n2016 (group 2)\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n2016 (group 1)\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training" }, { - "objectID": "all-projects/2019-group-1.html", - "href": "all-projects/2019-group-1.html", + "objectID": "all-projects/2020-group-1.html", + "href": "all-projects/2020-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n\n\n\nFunded:\n$13,912\nProposed by:\nRichard Webster\nWebsite:\nhttps://cheori.org/samplesize/\nSummary:\nSample size calculation and power analysis are fundamental for study design, yet they are challenging to do in the R programming language due to limited inter-package documentation. It is difficult to find the required functionality within the sea of open source packages. Indeed, there is no systematic R resource that allows users to search for whether a particular study design and corresponding statistical test has a power analysis implemented in R.\nOur aims are to improve usability of power analyses performed in R, to facilitate proper design and analysis of data, and promote reproducible research.\nOur duel approach is to create a Task View page for sample size calculations & power analyses, as well as a series of tutorials to reduce the R users’ learning curve. Addressing the usability of sample size calculation / power analyses will benefit a broad spectrum of R users, as this is a vital component for study design, result interpretability and reproducibility.\n\n\n\nFunded:\n$20,171\nProposed by:\nMartin Westgate\nWebsite:\nhttps://rmetaverse.github.io\nSummary:\nEvidence synthesis is the process of identifying, collating and summarizing primary scientific research to provide reliable, transparent summaries such as systematic reviews and meta-analyses. Despite their importance for linking research with policy, however, evidence synthesis projects are often time-consuming, expensive, and difficult to update. Open and reproducible workflows would help address these problems, but these workflows are poorly supported by the current package environment, preventing access by new users and hindering uptake of the well-developed suite of statistical tools for meta-analysis in R. The metaverse project will integrate and expand tools to support evidence synthesis and meta-research in R; suggest flexible workflows to complete these projects in a straightforward and open manner; and provide a collector package allowing easy access to these developments for new and experienced users.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttp://s2geometry.io/\nSummary:\nCurrently, a number of R spatial functions assume that coordinates are two-dimensional, taken from a “flat” space, and may or may not work for geographical (long/lat) coordinates, depicting points on a globe. This project will try to make such functions more robust and helpful for the the case of geographical coordinates. It will reconsider the concept of a bounding box, and build an interface to the S2 geometry library (http://s2geometry.io/), which powers several modern systems that assume geographic coordinates.\n\n\n\nFunded:\n$10,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftraj\nSummary:\nMovement defined broadly plays a central and growing role in fields as diverse as transportation, sport, ecology, music, medicine, and data science. Sampling movements results in tracking data, in the form of geographic (x,y,z) and temporal coordinates (t). Despite this common nature, there is a critical lack of standard infrastructure to deal with movement. With a sharp increase of the use of R for movement studies (more than 70 % of movement studies used R in 2018), the Movement community in R is at the same time very dynamic and very fragmented; in 2018 there was 57 packages that process, visualize and analyze tracking data, one third of which worked in isolation, not being linked to any other tracking package. We aim to develop a central trajectory class to support all stages of movement studies (pre-processing, post-processing and analysis).\nWe propose a sftraj package offering a generic and flexible approach. The only aim of the package will be to present a central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R. The first stage of the work will specifically involve the Movement community in R. During this stage, we will open contributions of use cases for the package (using GitHub’s issue system), which set practical goals for the development of the package. Use cases describe the workflow that is expected from both users’ and developers’ perspectives, and thus the capabilities that a trajectory package needs to offer. The package specifications and development will aim at addressing all use cases described, to make sure the solution provided is relevant for a wide array of users and package developers." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n\n\n\nFunded:\n$4,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/rladies/starter-kit\nSummary:\nR-Ladies Global is a successful, growing organization aiming at increasing gender diversity in the R community. R-Ladies Global is a Top-Level Project of the ISC. R-Ladies Global guidance for starting and running a chapter, as well as overseeing chapters around the world, and for the rotating curator account, grew organically. The information is fragmented and exists in different formats: several Markdown and PDF Documents and wiki entries in a GitHub repository. This impedes the optimal finding of resources by those who need them, and also impedes contributions. This project aims to consolidate existing R-Ladies Global guidance into a well-structured and continuously deployed online book, with its source open on GitHub, as ( R ) Markdown documents woven together, and whose maintenance will be an R-Ladies major priority task.\nThe project will create a web based manuscript containing all the necessary information to understand what the R-Ladies organization is about, its structure and how to contribute to its mission. Information will be collated and organized leveraging the experience of R-Ladies organizers and volunteers that, over the past 4 years, contributed to the establishment and growth of one of the most active and successful communities in the data science realm. This book will be a crucial resource for R-Ladies and other organizations that are looking to consolidate or create their own guidance.\n\n\n\nFunded:\n$6,000\nProposed by:\nEtienne Racine\nWebsite:\nhttps://github.com/r-spatial/sfdbi\nSummary:\nManipulating spatial data in R sometimes requires interaction with a spatial database: the data doesn’t fit in memory, or simply because this is where the data is. The `sf` package already supports the PostGIS spatial database, but this project will extend the compatibility and make it easier to integrate in the `dplyr` workflow (with `dbplyr`). We also want to make it easier to add support for new database backends. We’ll create a new `sfdbi` package to centralize the interface between `sf` and databases and remove dependencies in `sf`. If you want to contribute, or if you’d like to suggest a database, make sure to join the `sfdbi` repo.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/ropensci-books/http-testing\nSummary:\nMore and more R packages access resources on the web, and play crucial roles in workflows: data access and updates for CRM reports (Hubspot APIs), for scientific publications (scientific web APIs, Open Science Framework). Like for all other packages, appropriate unit testing can make them more robust. Their unit testing brings special challenges: dependence of tests on a good internet connection, testing in the absence of authentication secrets, etc. Having tests fail due to resources being down or slow, during development or on CRAN, means a time loss for everyone involved (slower development, messages from CRAN). Although many packages accessing remote resources are well tested, there is a lack of resources around best practices for HTTP testing in packages using httr, crul, or curl. The best guidance to date about HTTP testing for R packages to our knowledge is a forum entry that pre-dates the development of relatively new packages for HTTP testing that have now been released on CRAN: vcr and webmockr by Scott Chamberlain, httptest by Neal Richardson, presser by Gábor Csárdi. This project aims at curating a free, central reference for developers of R packages accessing web resources, to help them have a faster and more robust development. We shall develop an useful guidance, in the form of a open-source web-based book.\n\n\n\nFunded:\n$35,000\nProposed by:\nOlga Vitek\nWebsite:\nhttps://github.com/kuwisdelu/matter\nSummary:\nThe project develops the MATTER 2.0 package for computing with larger-than-memory data in R. It extends the functionality of the existing MATTER package to any disk data format and in-memory layout. It also extends MATTER’s implementation with ALTREP to provide seamless interoperation with existing code, and various performance improvements critical for rapid prototyping of new statistical methods.\n\n\n\nFunded:\n$10,000\nProposed by:\nBenedikt Gräler\nWebsite:\nhttps://github.com/BenGraeler/STDataAndAnalytics/\nSummary:\nMany data sets are recorded irregular in space and time. Movement of people driving the spread of an disease, or the distribution of current and future cases are per se irregular spatiotemporal data and only two of many examples. Being able to easily visualise, aggregate and model irregular spatiotemporal data will help to better understand and forecast underlying processes. Filling the gap for irregular spatiotemporal data and providing direct interaction with analytical tools will ease the analysis for researchers. We will develop the sftime package to a mature state so that the suite of modern spatial and spatiotemporal data representations in R includes irregular spatiotemporal data. After doing this, we will modify the geostatistical modelling package gstat and the spatial copula modelling package spcopula to support the new data representation classes of sf, stars and sftime.\n\n\n\nFunded:\n$23,300\nProposed by:\nThibaut Jombart\nWebsite:\nhttps://www.repidemicsconsortium.org/2020-06-09-covid-challenge/\nSummary:\nThe RECON COVID-19 challenge aims to bring together the infectious disease modelling, epidemiology and R communities to improve analytics resources for the COVID-19 response via a website which will provide a platform to centralise, curate and update R development tasks relevant to the COVID-19 response. Similar to the Open Street Map Tasking Manager (tasks.hotosm.org), this platform will allow potential contributors to quickly identify outstanding tasks submitted by groups involved in the response to COVID-19 and ensure that developments follow the highest scientific and technical standards.\nWhile this project is aimed at leveraging R tools for helping to respond to COVID-19, we expect that it will lead to long-lasting developments of partnerships between the R and epidemiological communities, and that the resources developed will become key assets for supporting outbreak responses well beyond this pandemic.\n\n\n\nFunded:\n$5,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftrack\nSummary:\nsftrack’ is a modern approach for tracking data in R. In response to the large diversity of ad-hoc solutions, in part outdated, we propose a generic and flexible approach that support all stages of movement studies (pre-processing, post-processing and analysis). ‘sftrack’ provides two central classes for tracking data (points) and movement data (steps), and basic functions to build, handle, summarize and plot them. Version 1.0 of ‘sftrack’ will be finalized and submitted to CRAN, and will already incorporate converters from/to classes of major existing tracking packages. We will further work with all tracking package developers willing to fully integrate the solution offered by ‘sftrack’ into their package data flow." }, { - "objectID": "all-projects/2019-group-1.html#funded-isc-grants-2019-1", - "href": "all-projects/2019-group-1.html#funded-isc-grants-2019-1", + "objectID": "all-projects/2020-group-1.html#funded-isc-grants-2020-1", + "href": "all-projects/2020-group-1.html#funded-isc-grants-2020-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n\n\n\nFunded:\n$13,912\nProposed by:\nRichard Webster\nWebsite:\nhttps://cheori.org/samplesize/\nSummary:\nSample size calculation and power analysis are fundamental for study design, yet they are challenging to do in the R programming language due to limited inter-package documentation. It is difficult to find the required functionality within the sea of open source packages. Indeed, there is no systematic R resource that allows users to search for whether a particular study design and corresponding statistical test has a power analysis implemented in R.\nOur aims are to improve usability of power analyses performed in R, to facilitate proper design and analysis of data, and promote reproducible research.\nOur duel approach is to create a Task View page for sample size calculations & power analyses, as well as a series of tutorials to reduce the R users’ learning curve. Addressing the usability of sample size calculation / power analyses will benefit a broad spectrum of R users, as this is a vital component for study design, result interpretability and reproducibility.\n\n\n\nFunded:\n$20,171\nProposed by:\nMartin Westgate\nWebsite:\nhttps://rmetaverse.github.io\nSummary:\nEvidence synthesis is the process of identifying, collating and summarizing primary scientific research to provide reliable, transparent summaries such as systematic reviews and meta-analyses. Despite their importance for linking research with policy, however, evidence synthesis projects are often time-consuming, expensive, and difficult to update. Open and reproducible workflows would help address these problems, but these workflows are poorly supported by the current package environment, preventing access by new users and hindering uptake of the well-developed suite of statistical tools for meta-analysis in R. The metaverse project will integrate and expand tools to support evidence synthesis and meta-research in R; suggest flexible workflows to complete these projects in a straightforward and open manner; and provide a collector package allowing easy access to these developments for new and experienced users.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttp://s2geometry.io/\nSummary:\nCurrently, a number of R spatial functions assume that coordinates are two-dimensional, taken from a “flat” space, and may or may not work for geographical (long/lat) coordinates, depicting points on a globe. This project will try to make such functions more robust and helpful for the the case of geographical coordinates. It will reconsider the concept of a bounding box, and build an interface to the S2 geometry library (http://s2geometry.io/), which powers several modern systems that assume geographic coordinates.\n\n\n\nFunded:\n$10,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftraj\nSummary:\nMovement defined broadly plays a central and growing role in fields as diverse as transportation, sport, ecology, music, medicine, and data science. Sampling movements results in tracking data, in the form of geographic (x,y,z) and temporal coordinates (t). Despite this common nature, there is a critical lack of standard infrastructure to deal with movement. With a sharp increase of the use of R for movement studies (more than 70 % of movement studies used R in 2018), the Movement community in R is at the same time very dynamic and very fragmented; in 2018 there was 57 packages that process, visualize and analyze tracking data, one third of which worked in isolation, not being linked to any other tracking package. We aim to develop a central trajectory class to support all stages of movement studies (pre-processing, post-processing and analysis).\nWe propose a sftraj package offering a generic and flexible approach. The only aim of the package will be to present a central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R. The first stage of the work will specifically involve the Movement community in R. During this stage, we will open contributions of use cases for the package (using GitHub’s issue system), which set practical goals for the development of the package. Use cases describe the workflow that is expected from both users’ and developers’ perspectives, and thus the capabilities that a trajectory package needs to offer. The package specifications and development will aim at addressing all use cases described, to make sure the solution provided is relevant for a wide array of users and package developers." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n\n\n\nFunded:\n$4,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/rladies/starter-kit\nSummary:\nR-Ladies Global is a successful, growing organization aiming at increasing gender diversity in the R community. R-Ladies Global is a Top-Level Project of the ISC. R-Ladies Global guidance for starting and running a chapter, as well as overseeing chapters around the world, and for the rotating curator account, grew organically. The information is fragmented and exists in different formats: several Markdown and PDF Documents and wiki entries in a GitHub repository. This impedes the optimal finding of resources by those who need them, and also impedes contributions. This project aims to consolidate existing R-Ladies Global guidance into a well-structured and continuously deployed online book, with its source open on GitHub, as ( R ) Markdown documents woven together, and whose maintenance will be an R-Ladies major priority task.\nThe project will create a web based manuscript containing all the necessary information to understand what the R-Ladies organization is about, its structure and how to contribute to its mission. Information will be collated and organized leveraging the experience of R-Ladies organizers and volunteers that, over the past 4 years, contributed to the establishment and growth of one of the most active and successful communities in the data science realm. This book will be a crucial resource for R-Ladies and other organizations that are looking to consolidate or create their own guidance.\n\n\n\nFunded:\n$6,000\nProposed by:\nEtienne Racine\nWebsite:\nhttps://github.com/r-spatial/sfdbi\nSummary:\nManipulating spatial data in R sometimes requires interaction with a spatial database: the data doesn’t fit in memory, or simply because this is where the data is. The `sf` package already supports the PostGIS spatial database, but this project will extend the compatibility and make it easier to integrate in the `dplyr` workflow (with `dbplyr`). We also want to make it easier to add support for new database backends. We’ll create a new `sfdbi` package to centralize the interface between `sf` and databases and remove dependencies in `sf`. If you want to contribute, or if you’d like to suggest a database, make sure to join the `sfdbi` repo.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/ropensci-books/http-testing\nSummary:\nMore and more R packages access resources on the web, and play crucial roles in workflows: data access and updates for CRM reports (Hubspot APIs), for scientific publications (scientific web APIs, Open Science Framework). Like for all other packages, appropriate unit testing can make them more robust. Their unit testing brings special challenges: dependence of tests on a good internet connection, testing in the absence of authentication secrets, etc. Having tests fail due to resources being down or slow, during development or on CRAN, means a time loss for everyone involved (slower development, messages from CRAN). Although many packages accessing remote resources are well tested, there is a lack of resources around best practices for HTTP testing in packages using httr, crul, or curl. The best guidance to date about HTTP testing for R packages to our knowledge is a forum entry that pre-dates the development of relatively new packages for HTTP testing that have now been released on CRAN: vcr and webmockr by Scott Chamberlain, httptest by Neal Richardson, presser by Gábor Csárdi. This project aims at curating a free, central reference for developers of R packages accessing web resources, to help them have a faster and more robust development. We shall develop an useful guidance, in the form of a open-source web-based book.\n\n\n\nFunded:\n$35,000\nProposed by:\nOlga Vitek\nWebsite:\nhttps://github.com/kuwisdelu/matter\nSummary:\nThe project develops the MATTER 2.0 package for computing with larger-than-memory data in R. It extends the functionality of the existing MATTER package to any disk data format and in-memory layout. It also extends MATTER’s implementation with ALTREP to provide seamless interoperation with existing code, and various performance improvements critical for rapid prototyping of new statistical methods.\n\n\n\nFunded:\n$10,000\nProposed by:\nBenedikt Gräler\nWebsite:\nhttps://github.com/BenGraeler/STDataAndAnalytics/\nSummary:\nMany data sets are recorded irregular in space and time. Movement of people driving the spread of an disease, or the distribution of current and future cases are per se irregular spatiotemporal data and only two of many examples. Being able to easily visualise, aggregate and model irregular spatiotemporal data will help to better understand and forecast underlying processes. Filling the gap for irregular spatiotemporal data and providing direct interaction with analytical tools will ease the analysis for researchers. We will develop the sftime package to a mature state so that the suite of modern spatial and spatiotemporal data representations in R includes irregular spatiotemporal data. After doing this, we will modify the geostatistical modelling package gstat and the spatial copula modelling package spcopula to support the new data representation classes of sf, stars and sftime.\n\n\n\nFunded:\n$23,300\nProposed by:\nThibaut Jombart\nWebsite:\nhttps://www.repidemicsconsortium.org/2020-06-09-covid-challenge/\nSummary:\nThe RECON COVID-19 challenge aims to bring together the infectious disease modelling, epidemiology and R communities to improve analytics resources for the COVID-19 response via a website which will provide a platform to centralise, curate and update R development tasks relevant to the COVID-19 response. Similar to the Open Street Map Tasking Manager (tasks.hotosm.org), this platform will allow potential contributors to quickly identify outstanding tasks submitted by groups involved in the response to COVID-19 and ensure that developments follow the highest scientific and technical standards.\nWhile this project is aimed at leveraging R tools for helping to respond to COVID-19, we expect that it will lead to long-lasting developments of partnerships between the R and epidemiological communities, and that the resources developed will become key assets for supporting outbreak responses well beyond this pandemic.\n\n\n\nFunded:\n$5,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftrack\nSummary:\nsftrack’ is a modern approach for tracking data in R. In response to the large diversity of ad-hoc solutions, in part outdated, we propose a generic and flexible approach that support all stages of movement studies (pre-processing, post-processing and analysis). ‘sftrack’ provides two central classes for tracking data (points) and movement data (steps), and basic functions to build, handle, summarize and plot them. Version 1.0 of ‘sftrack’ will be finalized and submitted to CRAN, and will already incorporate converters from/to classes of major existing tracking packages. We will further work with all tracking package developers willing to fully integrate the solution offered by ‘sftrack’ into their package data flow." }, { - "objectID": "all-projects/2024-group-1.html", - "href": "all-projects/2024-group-1.html", + "objectID": "all-projects/2018-group-2.html", + "href": "all-projects/2018-group-2.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n\n\n\nFunded:\n$18,000\nProposed by:\nCory Brunson and Aymeric Stamm\nSummary:\nThe goal of this project is to seamlessly integrate popular techniques from topological data analysis (TDA) into common statistical workflows in R. The expected benefit is that these extensions will be more widely used by non-specialist researchers and analysts, which will create sufficient awareness and interest in the community to extend the individual packages and the collection.\n\n\n\nFunded:\n$13,750\nProposed by:\nEmmanuel Blondel\nSummary:\nThe present project enhances the geometa package for handling the new ISO 19115-3 geographic information standard as part of its object-oriented data model developed with R6. The user community, especially data managers working in research national institutes and international organizations, will take advantage of the features to start adopting the new standard for managing their geographic metadata, progressively promoted in Geographic information management web platforms, especially those from the OpenSource Geospatial Foundation (OSGeo) such as GeoNetwork, PyCSW or GeoNode.\n\n\n\nFunded:\n$20,000\nProposed by:\nWill Landau\nSummary:\nThe implementation of R-multiverse to date has been both straightforward and achievable. It builds directly upon the proven technologies of R-universe and GitHub Actions. By the end of the milestones, the entire project will be in a ready state to be launched to the public as a production solution for non-CRAN non-Bioconductor packages.\n\n\n\nFunded:\n$8,000\nProposed by:\nAidan Lakshman, University of Pittsburgh\nSummary:\nBiostrings is a core Bioconductor package providing efficient containers for storing, manipulating, and analyzing biological sequences. Biostrings is the method to access biological sequence data in R; nearly every analysis working with genomic data depends on the Biostrings package to handle sequencing data.\nThis project proposes to clear out accumulated technical debt by addressing open issues, implementing robust tests for long-term sustainability, improving user experience, and adding features that will keep Biostrings relevant for modern sequencing technologies. For end-users, this will result in numerous bugfixes, a host of new features to support genomic analyses, and a variety of performance improvements to bolster R as one of the top programming languages for bioinformatics. For developers, this will make the Biostrings package more sustainable, allowing for more community contribution and faster bug resolution in the future.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon, cynkra\nSummary:\nThis project is aimed at improving the quality of igraph codebase itself and of the user interface (messages including error messages, documentation indicating the status of exported functions). It has the goal of improving the user-friendliness of the installation from source.\n\n\n\nFunded:\n$15,912\nProposed by:\nEric Scott, University of Arizona\nSummary:\nThe goal of this project is to create a package that makes using targets for geospatial analysis in R as seamless as possible. To that end, geotargets will provide custom functions for defining geospatial targets that take care of translating and saving R objects for the user. In addition, the project will provide vignettes demonstrating how to use various geospatial R packages with targets. Where appropriate, the project will identify contributions to existing R packages to make them easier to use with targets and geotargets." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n\n\n\nFunded:\n$46,050\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://blog.r-hub.io\nSummary:\nAfter the continuing technical progress of R-hub over the last two years, this project aims at catalizing its adoption by R package developers of all levels through developer advocacy. Indeed, R-hub is currently a successful and very valuable project, but it is not documented thoroughly, which hinders its wider adoption by package developers. This project shall answer this concern by three main actions: improving R-hub documentation, making R-hub better known in the community and making the R-hub web site more attractive to, and easier to use by, R developers and users via the ingestion of METACRAN services and the creation of a R-hub blog.\n\n\n\nFunded:\n$5,250\nProposed by:\nBenaiah Chibuokem Ubah\nWebsite:\nhttps://benubah.github.io/r-community-explorer/rugs.html\nSummary:\nThis project proposes an infrastructure that provides a data-driven approach to render the yearly activities of the R Consortium, by deploying web pages for discovering and tracking ISC Funded Projects, RUGS and Marketing activities. These pages are planned to appear like dashboards summarizing activities in interactive tables and charts, presenting several views, trends and insights to what R Consortium has achieved over time. The project hopes that presenting these achievements in a data-driven manner to the R community, the data science community and prospective R Consortium members will promote greater transparency, productivity and community inclusiveness around R Consortium activities.\n\n\n\nFunded:\n$50,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://rjpilot.netlify.app/\nSummary:\nThis project supports the operation of the R Journal. There are two aspects, one is to fund an editorial assistant to send reminders about reviews, and assist with typesetting and copyediting issues. The second part is to explore updating the technical operations of the journal production.\n\n\n\nFunded:\n$6,000\nProposed by:\nColin Fay\nWebsite:\nhttps://github.com/ThinkR-open/isc-proposal-licence/ and https://thinkr-open.github.io/licensing-r/intro.html#getting-a-more-global-idea and https://github.com/ThinkR-open/isc-proposal-licence/blob/master/proposal_licence.md\nSummary:\nLicensing is a vital part of Open Source. It provides guidelines for interacting with a program, and for making code accessible and reusable (or not). It provides a way to make code open source, in a way one wants to share it, protecting how it will be used and reused. Licensing is also challenging and complex: there are a lot of available licenses, and the choice is influenced by how you import and interact with elements from other packages and/or programs.\nWith this project, we propose to explore and document the current state of open source licenses in R, and to decipher compatibility and incompatibly elements inside these licenses, to help developers chose the best suited licence for their project.\n\n\n\nFunded:\n$25,000\nProposed by:\nClaus Wilke\nWebsite:\nhttps://wilkelab.org/gridtext/\nSummary:\nText is a key component of any data visualization. We need to label axes and legends, we need to annotate or highlight specific data points, and we need to provide plot titles and captions. The R graphics package ggplot2 provides numerous features to customize the labeling and annotation of plots, but ultimately it is limited by the current capabilities of the underlying graphics libary it uses, grid. Grid can draw simple text strings or mathematical expressions (via plotmath) in different colors, sizes, and fonts. However, it lacks functionality for changing formatting within a string (e.g., draw a single word in italics or in a different color), and it also cannot draw text boxes, where the text is enclosed in a box with defined margins, padding, or background color. This project will support the development of a new package, gridtext, that will alleviate these text formatting limitations. The project will also support efforts to make these new capabilities available from within ggplot2.\n\n\n\nFunded:\n$20,000\nProposed by:\nEmmanuel Blondel\nWebsite:\nSummary:\nThe project aims to strengthen the role of R in support of Spatial Data Infrastructures (SDI) management, through major enhancements of the geometa R package which offers tools for reading and writing ISO/OGC geographic metadata, including ISO 19115, 19110, and 19119 through the ISO 19139 XML format. This also extends to the Geographic Markup Language (GML - ISO 19136) used for describing geographic data. The use of geometa in combination with publication tools such as ows4R ( https://cran.r-project.org/package=ows4R ) and geosapi (https://cran.r-project.org/package=geosapi) fosters the use of R software to ease the management and publication of metadata documents and related datasets in web catalogues, and then allows to move forward with a real R implementation of spatial data management plans based on FAIR (Findable, Accessible Interoperable and Reusable) principles.\nThe workplan includes several activities such as working on the completeness of the ISO 19115 (ISO 19115-1 and 19115-2) data model in geometa, functions to read/write multilingual metadata documents, and an increased metadata validation capability with a validator targeting the EU INSPIRE directive. Finally, functions will be made available to convert between geometa ISO/OGC metadata objects and other known metadata objects such as NetCDF-CF and EML (Ecological Metadata Language) to foster metadata interoperability. By providing these R tools, we seek to facilitate the work of spatial data (GIS) managers, but also data scientists, whatever the thematic domain, whose daily tasks consist in handling data, describing them with metadata and publishing datasets.\n\n\n\nFunded:\n$6,000\nProposed by:\nEmi Tanaka\nWebsite:\nSummary:\nSymbolic model formulae define the structural component of a statistical model in an easier and often more accessible terms for practitioners. The earlier instance of symbolic model formulae for linear models was applied in Genstat with further generalisation by Wilkinson and Rogers (1973). Chambers and Hastie (1993) describe the symbolic model formulae implementation for linear models in the S language which remains much the same in the R language (Venables et al. 2018).\nLinear mixed models (LMMs) are widely used across many disciplines (e.g. ecology, psychology, agriculture, finance etc) due to its flexibility to model complex, correlated structures in the data. While the symbolic formula of linear models generally have a consistent representation and evaluation rule as implemented in stats::formula, this is not the case for LMMs. The inconsistency of symbolic formulae arises mainly in the representation of random effects, with the additional need to specify the variance-covariance structure of the random effects as well as structure of the associated model matrix that governs how the random effects are mapped to (groups of) the observational units. The differences give rise to confusion of equivalent model specification in different R-packages.\nThe lack of consistency in symbolic formula and model representation across mixed model software motivates the need to formulate a unified symbolic model formulae for LMMs with: (1) extension of the evaluation rules described in Wilkinson and Rogers (1973); and (2) ease of comprehension of the specified model for the user. This symbolic model formulae can be a basis for creating a common API to mixed models with wrappers to popular mixed model R-packages, thereby achieving a similar feat to parsnip R-package (Kuhn 2018) which implements a tidy unified interface to many predictive modelling functions (e.g. random forest, logistic regression, survival models etc).\nWe would like to find out what are your experiences with fitting linear mixed model in R! Please fill out the survey below to help us understand your problems: https://docs.google.com/forms/d/e/1FAIpQLSeblEoPtDmPS-dH2dmsHjLxLuKl19UY1JdmTrZux-AUSq3N7Q/viewform?usp=sf_link\n\n\n\nFunded:\n$10,000\nProposed by:\nChristoph Bodner, Florian Schwendinger, Thomas Laber\nWebsite:\nhttps://github.com/harlecin/serverless\nSummary:\nR is a great language for rapid prototyping and experimentation, but putting an R model in production is still more complex and time-consuming than it needs to be. With the growing popularity of serverless computing frameworks such as AWS Lambda and Azure Functions we see a a huge chance to allow R developers to more easily deploy their code into production. We want to build an R package called ‘serverless’ to allow R users to easily deploy scripts and custom R packages to AWS Lambda and in a second step to Azure Functions. Our main goal is to build a user-friendly cloud agnostic wrapper that can be extended to include additional cloud providers later on. We want to build on the work already done for deploying R functions to AWS Lambda by Philipp Schirmer and on the work already done by Neal Fultz and Gergely Daróczi on a gRPC client/server for R, which is necessary for Azure Functions. If you like our idea and want to help us, feel free to reach out to us on Github at https://github.com/harlecin/serverless\nBest,\nChristoph, Florian and Thomas" }, { - "objectID": "all-projects/2024-group-1.html#funded-isc-grants-2024-1", - "href": "all-projects/2024-group-1.html#funded-isc-grants-2024-1", + "objectID": "all-projects/2018-group-2.html#funded-isc-grants-2018-2", + "href": "all-projects/2018-group-2.html#funded-isc-grants-2018-2", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n\n\n\nFunded:\n$18,000\nProposed by:\nCory Brunson and Aymeric Stamm\nSummary:\nThe goal of this project is to seamlessly integrate popular techniques from topological data analysis (TDA) into common statistical workflows in R. The expected benefit is that these extensions will be more widely used by non-specialist researchers and analysts, which will create sufficient awareness and interest in the community to extend the individual packages and the collection.\n\n\n\nFunded:\n$13,750\nProposed by:\nEmmanuel Blondel\nSummary:\nThe present project enhances the geometa package for handling the new ISO 19115-3 geographic information standard as part of its object-oriented data model developed with R6. The user community, especially data managers working in research national institutes and international organizations, will take advantage of the features to start adopting the new standard for managing their geographic metadata, progressively promoted in Geographic information management web platforms, especially those from the OpenSource Geospatial Foundation (OSGeo) such as GeoNetwork, PyCSW or GeoNode.\n\n\n\nFunded:\n$20,000\nProposed by:\nWill Landau\nSummary:\nThe implementation of R-multiverse to date has been both straightforward and achievable. It builds directly upon the proven technologies of R-universe and GitHub Actions. By the end of the milestones, the entire project will be in a ready state to be launched to the public as a production solution for non-CRAN non-Bioconductor packages.\n\n\n\nFunded:\n$8,000\nProposed by:\nAidan Lakshman, University of Pittsburgh\nSummary:\nBiostrings is a core Bioconductor package providing efficient containers for storing, manipulating, and analyzing biological sequences. Biostrings is the method to access biological sequence data in R; nearly every analysis working with genomic data depends on the Biostrings package to handle sequencing data.\nThis project proposes to clear out accumulated technical debt by addressing open issues, implementing robust tests for long-term sustainability, improving user experience, and adding features that will keep Biostrings relevant for modern sequencing technologies. For end-users, this will result in numerous bugfixes, a host of new features to support genomic analyses, and a variety of performance improvements to bolster R as one of the top programming languages for bioinformatics. For developers, this will make the Biostrings package more sustainable, allowing for more community contribution and faster bug resolution in the future.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon, cynkra\nSummary:\nThis project is aimed at improving the quality of igraph codebase itself and of the user interface (messages including error messages, documentation indicating the status of exported functions). It has the goal of improving the user-friendliness of the installation from source.\n\n\n\nFunded:\n$15,912\nProposed by:\nEric Scott, University of Arizona\nSummary:\nThe goal of this project is to create a package that makes using targets for geospatial analysis in R as seamless as possible. To that end, geotargets will provide custom functions for defining geospatial targets that take care of translating and saving R objects for the user. In addition, the project will provide vignettes demonstrating how to use various geospatial R packages with targets. Where appropriate, the project will identify contributions to existing R packages to make them easier to use with targets and geotargets." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n\n\n\nFunded:\n$46,050\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://blog.r-hub.io\nSummary:\nAfter the continuing technical progress of R-hub over the last two years, this project aims at catalizing its adoption by R package developers of all levels through developer advocacy. Indeed, R-hub is currently a successful and very valuable project, but it is not documented thoroughly, which hinders its wider adoption by package developers. This project shall answer this concern by three main actions: improving R-hub documentation, making R-hub better known in the community and making the R-hub web site more attractive to, and easier to use by, R developers and users via the ingestion of METACRAN services and the creation of a R-hub blog.\n\n\n\nFunded:\n$5,250\nProposed by:\nBenaiah Chibuokem Ubah\nWebsite:\nhttps://benubah.github.io/r-community-explorer/rugs.html\nSummary:\nThis project proposes an infrastructure that provides a data-driven approach to render the yearly activities of the R Consortium, by deploying web pages for discovering and tracking ISC Funded Projects, RUGS and Marketing activities. These pages are planned to appear like dashboards summarizing activities in interactive tables and charts, presenting several views, trends and insights to what R Consortium has achieved over time. The project hopes that presenting these achievements in a data-driven manner to the R community, the data science community and prospective R Consortium members will promote greater transparency, productivity and community inclusiveness around R Consortium activities.\n\n\n\nFunded:\n$50,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://rjpilot.netlify.app/\nSummary:\nThis project supports the operation of the R Journal. There are two aspects, one is to fund an editorial assistant to send reminders about reviews, and assist with typesetting and copyediting issues. The second part is to explore updating the technical operations of the journal production.\n\n\n\nFunded:\n$6,000\nProposed by:\nColin Fay\nWebsite:\nhttps://github.com/ThinkR-open/isc-proposal-licence/ and https://thinkr-open.github.io/licensing-r/intro.html#getting-a-more-global-idea and https://github.com/ThinkR-open/isc-proposal-licence/blob/master/proposal_licence.md\nSummary:\nLicensing is a vital part of Open Source. It provides guidelines for interacting with a program, and for making code accessible and reusable (or not). It provides a way to make code open source, in a way one wants to share it, protecting how it will be used and reused. Licensing is also challenging and complex: there are a lot of available licenses, and the choice is influenced by how you import and interact with elements from other packages and/or programs.\nWith this project, we propose to explore and document the current state of open source licenses in R, and to decipher compatibility and incompatibly elements inside these licenses, to help developers chose the best suited licence for their project.\n\n\n\nFunded:\n$25,000\nProposed by:\nClaus Wilke\nWebsite:\nhttps://wilkelab.org/gridtext/\nSummary:\nText is a key component of any data visualization. We need to label axes and legends, we need to annotate or highlight specific data points, and we need to provide plot titles and captions. The R graphics package ggplot2 provides numerous features to customize the labeling and annotation of plots, but ultimately it is limited by the current capabilities of the underlying graphics libary it uses, grid. Grid can draw simple text strings or mathematical expressions (via plotmath) in different colors, sizes, and fonts. However, it lacks functionality for changing formatting within a string (e.g., draw a single word in italics or in a different color), and it also cannot draw text boxes, where the text is enclosed in a box with defined margins, padding, or background color. This project will support the development of a new package, gridtext, that will alleviate these text formatting limitations. The project will also support efforts to make these new capabilities available from within ggplot2.\n\n\n\nFunded:\n$20,000\nProposed by:\nEmmanuel Blondel\nWebsite:\nSummary:\nThe project aims to strengthen the role of R in support of Spatial Data Infrastructures (SDI) management, through major enhancements of the geometa R package which offers tools for reading and writing ISO/OGC geographic metadata, including ISO 19115, 19110, and 19119 through the ISO 19139 XML format. This also extends to the Geographic Markup Language (GML - ISO 19136) used for describing geographic data. The use of geometa in combination with publication tools such as ows4R ( https://cran.r-project.org/package=ows4R ) and geosapi (https://cran.r-project.org/package=geosapi) fosters the use of R software to ease the management and publication of metadata documents and related datasets in web catalogues, and then allows to move forward with a real R implementation of spatial data management plans based on FAIR (Findable, Accessible Interoperable and Reusable) principles.\nThe workplan includes several activities such as working on the completeness of the ISO 19115 (ISO 19115-1 and 19115-2) data model in geometa, functions to read/write multilingual metadata documents, and an increased metadata validation capability with a validator targeting the EU INSPIRE directive. Finally, functions will be made available to convert between geometa ISO/OGC metadata objects and other known metadata objects such as NetCDF-CF and EML (Ecological Metadata Language) to foster metadata interoperability. By providing these R tools, we seek to facilitate the work of spatial data (GIS) managers, but also data scientists, whatever the thematic domain, whose daily tasks consist in handling data, describing them with metadata and publishing datasets.\n\n\n\nFunded:\n$6,000\nProposed by:\nEmi Tanaka\nWebsite:\nSummary:\nSymbolic model formulae define the structural component of a statistical model in an easier and often more accessible terms for practitioners. The earlier instance of symbolic model formulae for linear models was applied in Genstat with further generalisation by Wilkinson and Rogers (1973). Chambers and Hastie (1993) describe the symbolic model formulae implementation for linear models in the S language which remains much the same in the R language (Venables et al. 2018).\nLinear mixed models (LMMs) are widely used across many disciplines (e.g. ecology, psychology, agriculture, finance etc) due to its flexibility to model complex, correlated structures in the data. While the symbolic formula of linear models generally have a consistent representation and evaluation rule as implemented in stats::formula, this is not the case for LMMs. The inconsistency of symbolic formulae arises mainly in the representation of random effects, with the additional need to specify the variance-covariance structure of the random effects as well as structure of the associated model matrix that governs how the random effects are mapped to (groups of) the observational units. The differences give rise to confusion of equivalent model specification in different R-packages.\nThe lack of consistency in symbolic formula and model representation across mixed model software motivates the need to formulate a unified symbolic model formulae for LMMs with: (1) extension of the evaluation rules described in Wilkinson and Rogers (1973); and (2) ease of comprehension of the specified model for the user. This symbolic model formulae can be a basis for creating a common API to mixed models with wrappers to popular mixed model R-packages, thereby achieving a similar feat to parsnip R-package (Kuhn 2018) which implements a tidy unified interface to many predictive modelling functions (e.g. random forest, logistic regression, survival models etc).\nWe would like to find out what are your experiences with fitting linear mixed model in R! Please fill out the survey below to help us understand your problems: https://docs.google.com/forms/d/e/1FAIpQLSeblEoPtDmPS-dH2dmsHjLxLuKl19UY1JdmTrZux-AUSq3N7Q/viewform?usp=sf_link\n\n\n\nFunded:\n$10,000\nProposed by:\nChristoph Bodner, Florian Schwendinger, Thomas Laber\nWebsite:\nhttps://github.com/harlecin/serverless\nSummary:\nR is a great language for rapid prototyping and experimentation, but putting an R model in production is still more complex and time-consuming than it needs to be. With the growing popularity of serverless computing frameworks such as AWS Lambda and Azure Functions we see a a huge chance to allow R developers to more easily deploy their code into production. We want to build an R package called ‘serverless’ to allow R users to easily deploy scripts and custom R packages to AWS Lambda and in a second step to Azure Functions. Our main goal is to build a user-friendly cloud agnostic wrapper that can be extended to include additional cloud providers later on. We want to build on the work already done for deploying R functions to AWS Lambda by Philipp Schirmer and on the work already done by Neal Fultz and Gergely Daróczi on a gRPC client/server for R, which is necessary for Azure Functions. If you like our idea and want to help us, feel free to reach out to us on Github at https://github.com/harlecin/serverless\nBest,\nChristoph, Florian and Thomas" }, { - "objectID": "all-projects/2023-group-1.html", - "href": "all-projects/2023-group-1.html", + "objectID": "all-projects/2016-group-2.html", + "href": "all-projects/2016-group-2.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n\n\n\nFunded:\n$10,000\nProposed by:\nKirill Müller\nSummary:\nThis proposal mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Keeping compatibility with the evolving ecosystem (OS, databases, R itself, other packages) is vital for the long-term success of the project.\n\n\n\nFunded:\n$10,000\nProposed by:\nCharlie Gao\nSummary:\nThe project aims to implement secure connections with a TLS layer for encrypted communications in distributed systems used by statisticians and data scientists. The current lack of secure communication tools restricts the use of existing R packages for long-running tasks to trusted local networks, posing security risks in compromised or untrusted environments. The proposed solution addresses this gap by providing encryption and authentication of endpoints, ensuring data security in line with industry standards.\n\n\n\nFunded:\n$12,265\nProposed by:\nKristina Riemer\nSummary:\nThis ISC funded project focuses on the development of the volcalc R package, which automates the estimation of compound volatility based on their chemical structure. The package streamlines the process by downloading chemical structure data, parsing it to identify functional groups, and utilizing the SIMPOL.1 algorithm to predict volatility using functional groups and molecular weight. The compounds are then assigned volatility categories based on a reference environment. This project aims to enhance the package by expanding its compatibility to work with any chemical compound with structural information from various databases. Additionally, improvements in testing and documentation will be implemented to enhance the reliability of the package.\n\n\n\nFunded:\n$3,000\nProposed by:\nMark Padgham\nSummary:\nThe project aims to develop an R package to automate property-based testing procedures in R, building upon the existing “typetracer” package. The new package will utilize “typetracer” to infer properties of function parameters and systematically mutate or randomize these properties to facilitate automated testing. The package will inherit the GPL-3 license from its predecessor and will be submitted to CRAN for wider dissemination. This initiative aligns with the goal of promoting efficient and reliable testing practices within the R community.\n\n\n\nFunded:\n$15,750\nProposed by:\nJon Harmon\nSummary:\nThis project aims to develop an R package called api2r, which will automate the creation of R package structures for APIs that adhere to the OpenAPI Specification (OAS). By leveraging the OAS as a foundation, api2r will significantly reduce the time and effort required to build API clients in R. This initiative hopes to have a widespread impact within the R community, benefiting data scientists, researchers, and developers who regularly interact with diverse APIs. To ensure its functionality and effectiveness, the development process will involve generating packages based on at least three authentic OpenAPI specifications." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n\n\n\nFunded:\n$9,100\nProposed by:\nTim Appelhans\nWebsite:\nhttps://github.com/environmentalinformatics-marburg/mapview_toolchain and https://cran.r-project.org/package=mapview\nSummary:\nThe ISC awarded $9,100 to Tim Appelhans, Florian Detsch and Christoph Reudenbach the authors of the Interactive data manipulation in mapview project which aims to extend the capabilities of R for visualizing geospatial data by implementing a two-way data exchange mechanism between R and JavaScript. The central idea is to extend the capabilities of existing tools to enhance the user experience of interactively working with geospatial data by implementing mechanisms for two way data transfer. For example, although htmlwidgets has proven itself to be a powerful framework for enabling interactive, JavaScript based data visualizations, data flow from R to Javascript runs on a one-way street. There is currently no way to pass manipulated data back into the user’s R environment. This project aims to first develop a general framework to provide a bridge between htmlwidgets and R to enable a workflow of R -> htmlwidgets -> R and then to use this framework to implement standard interactive spatial data manipulation tools for packages mapview and leaflet. The plan section of the project proposal provides considerable detail on the steps required to achieve the project’s goals.\n\n\n\nFunded:\n$10,000\nProposed by:\nAndrew Redd\nWebsite:\nhttps://github.com/RDocTaskForce/documentation\nSummary:\nAndrew Redd received $10,000 to lead a new ISC working group, The R Documentation Task Force, which has a mission to design and build the next generation R documentation system. The task force will identify issues with documentation that currently exist, abstract the current Rd system into an R compatible structure, and extend this structure to include new considerations that were not concerns when the Rd system was first implemented. The goal of the project is to create a system that allows for documentation to exist as objects that can be manipulated inside R. This will make the process of creating R documentation much more flexible enabling new capabilities such as porting documentation from other languages or creating inline comments. The new capabilities will add rigor to the documentation process and enable the the system to operate more efficiently than any current methods allow." }, { - "objectID": "all-projects/2023-group-1.html#funded-isc-grants-2023-1", - "href": "all-projects/2023-group-1.html#funded-isc-grants-2023-1", + "objectID": "all-projects/2016-group-2.html#funded-isc-grants-2016-2", + "href": "all-projects/2016-group-2.html#funded-isc-grants-2016-2", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n\n\n\nFunded:\n$10,000\nProposed by:\nKirill Müller\nSummary:\nThis proposal mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Keeping compatibility with the evolving ecosystem (OS, databases, R itself, other packages) is vital for the long-term success of the project.\n\n\n\nFunded:\n$10,000\nProposed by:\nCharlie Gao\nSummary:\nThe project aims to implement secure connections with a TLS layer for encrypted communications in distributed systems used by statisticians and data scientists. The current lack of secure communication tools restricts the use of existing R packages for long-running tasks to trusted local networks, posing security risks in compromised or untrusted environments. The proposed solution addresses this gap by providing encryption and authentication of endpoints, ensuring data security in line with industry standards.\n\n\n\nFunded:\n$12,265\nProposed by:\nKristina Riemer\nSummary:\nThis ISC funded project focuses on the development of the volcalc R package, which automates the estimation of compound volatility based on their chemical structure. The package streamlines the process by downloading chemical structure data, parsing it to identify functional groups, and utilizing the SIMPOL.1 algorithm to predict volatility using functional groups and molecular weight. The compounds are then assigned volatility categories based on a reference environment. This project aims to enhance the package by expanding its compatibility to work with any chemical compound with structural information from various databases. Additionally, improvements in testing and documentation will be implemented to enhance the reliability of the package.\n\n\n\nFunded:\n$3,000\nProposed by:\nMark Padgham\nSummary:\nThe project aims to develop an R package to automate property-based testing procedures in R, building upon the existing “typetracer” package. The new package will utilize “typetracer” to infer properties of function parameters and systematically mutate or randomize these properties to facilitate automated testing. The package will inherit the GPL-3 license from its predecessor and will be submitted to CRAN for wider dissemination. This initiative aligns with the goal of promoting efficient and reliable testing practices within the R community.\n\n\n\nFunded:\n$15,750\nProposed by:\nJon Harmon\nSummary:\nThis project aims to develop an R package called api2r, which will automate the creation of R package structures for APIs that adhere to the OpenAPI Specification (OAS). By leveraging the OAS as a foundation, api2r will significantly reduce the time and effort required to build API clients in R. This initiative hopes to have a widespread impact within the R community, benefiting data scientists, researchers, and developers who regularly interact with diverse APIs. To ensure its functionality and effectiveness, the development process will involve generating packages based on at least three authentic OpenAPI specifications." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n\n\n\nFunded:\n$9,100\nProposed by:\nTim Appelhans\nWebsite:\nhttps://github.com/environmentalinformatics-marburg/mapview_toolchain and https://cran.r-project.org/package=mapview\nSummary:\nThe ISC awarded $9,100 to Tim Appelhans, Florian Detsch and Christoph Reudenbach the authors of the Interactive data manipulation in mapview project which aims to extend the capabilities of R for visualizing geospatial data by implementing a two-way data exchange mechanism between R and JavaScript. The central idea is to extend the capabilities of existing tools to enhance the user experience of interactively working with geospatial data by implementing mechanisms for two way data transfer. For example, although htmlwidgets has proven itself to be a powerful framework for enabling interactive, JavaScript based data visualizations, data flow from R to Javascript runs on a one-way street. There is currently no way to pass manipulated data back into the user’s R environment. This project aims to first develop a general framework to provide a bridge between htmlwidgets and R to enable a workflow of R -> htmlwidgets -> R and then to use this framework to implement standard interactive spatial data manipulation tools for packages mapview and leaflet. The plan section of the project proposal provides considerable detail on the steps required to achieve the project’s goals.\n\n\n\nFunded:\n$10,000\nProposed by:\nAndrew Redd\nWebsite:\nhttps://github.com/RDocTaskForce/documentation\nSummary:\nAndrew Redd received $10,000 to lead a new ISC working group, The R Documentation Task Force, which has a mission to design and build the next generation R documentation system. The task force will identify issues with documentation that currently exist, abstract the current Rd system into an R compatible structure, and extend this structure to include new considerations that were not concerns when the Rd system was first implemented. The goal of the project is to create a system that allows for documentation to exist as objects that can be manipulated inside R. This will make the process of creating R documentation much more flexible enabling new capabilities such as porting documentation from other languages or creating inline comments. The new capabilities will add rigor to the documentation process and enable the the system to operate more efficiently than any current methods allow." }, { - "objectID": "all-projects/rugsprogram.html", - "href": "all-projects/rugsprogram.html", - "title": "R User Groups, Conferences, and Special Project Grants", + "objectID": "all-projects/isc-working-groups.html", + "href": "all-projects/isc-working-groups.html", + "title": "ISC Working Groups", "section": "", - "text": "R User Groups, Conferences, and Special Project Grants\nThis page describes how to apply for grants to support R user groups, conferences featuring R, and R Special Projects.\nFor any problems or information, please email operations@r-consortium.org\n\n\n2024 RUGS Program\nThe RUGS mission is to facilitate the person-to-person exchange of knowledge in small group settings on a global scale. We continue to believe that the most effective way for people to learn from and about each other, and to set and accomplish common goals is to meet face-to-face on a regular basis. Nevertheless, occasional virtual meetings are acceptable.\nRUGS grants are intended to help people form enduring R user group communities. Active user groups may apply for grants once every calendar year.\nThe R Consortium RUGS Program has grown from being a relatively modest R user group support program to being the primary vehicle for the R Consortium to award Social Infrastructure Grants. Social Infrastructure includes meetings, events, conferences, and other activities to strengthen the R Community.\nThese grants do not include support for software development or technical projects. Grants to support the R ecosystem’s technical infrastructure are awarded and administered through the ISC Grant Program, which issues a call for proposals two times each year.\n\n📌 Find your local R User Group here\n\n\n\n\nStructure\nIn 2024, there will be three categories of RUGS Program grants that are described in detail below:\n\nUser Group Grants\nConference Grants\nSpecial Projects Grants\n\n\nDuration of the 2024 RUGS Program\nThe 2024 RUGS Program will open on January 8, 2024, and close at midnight PST on September 30, 2024. We reserve the right to close the grant window earlier than anticipated based on the number of applications.\n\n\nHow to apply for a RUGS Program Grant\nTo apply for a grant fill out this form. Be sure to select the correct box to indicate whether you are applying for a use group, conference, or special projects grant.\n\n\n\nUser Group Grants\n\nRequirements\nTo be eligible for a RUGS grant, a user group must:\n\nGroup Organizer must have at least five people in the R User Group\nHave R as a primary focus\nAdhere to the Code of Conduct published on the R Consortium website\nAgree to participate in the RUGS meetup.com Pro program and use their meetup.com site to announce and track meetings\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on the group’s website\nAgree to write at least two blog posts per year about their group’s activities for possible publication on the R Consortium Blog\nComply with the instructions by completing a W9 Form (US-based groups only) or Wire Transfer form (Groups based outside of the US)\nAgree to the above in a grant agreement via DocuSign\n\n\n\nStructure\nR user groups grants under the RUGS 2024 program come in two parts:\n\nR user groups that are not already participating in the RUGS meetup.com Pro account will be enrolled into this program. The R Consortium will pay the group’s meetup.com fees for twelve months after acceptance into the program. Thereafter, the R Consortium will continue to pay meetup.com dues for participating groups as long as the groups comply with the requirements above, remain active, continue to meet at least once every three months, and use meetup.com to schedule and announce meetings. User group organizers do not need to re-apply for meetup.com Pro account participation if the group’s meetup.com account remains active.\nCash grants typically vary between $200 and $1,000 and depend on group size and special needs.\n\n\n\n\nGeneral Requirements\n\nMust agree to write 2 blog posts a year\nPost photos of their meetings onto Meetup.com as appropriate\nUpload available material to the R Consortium GitHub Repository\n\n\n\nRUGs Grant Amounts and Groups’ Responsibilities\nBrand new R User Group\n\nThe group receives a grant of $250 and membership in Meetup pro\nThe group must show 5 people committed to the group\nR Consortium will provide the blog link and best practice guide\nThe group must agree to write two blog posts per year\n\nTo get a grant of up to $500, all of the above plus:\n\nThe group must meet at least 1 time every 3 months\nThe group must have more than 25 people at the meeting\nThe group must have photos of the meeting\nThe group must show R Consortium Sponsorship\n\nTo get a grant of up to $1,000, all of the above plus:\n\nThe group must meet at least twice every 3 months\nThe group must have more than 50 people at the meeting\nThe group should provide presentations available for others (The R Consortium will host on GitHub)\n\n\nNotes\n\nR-Ladies maintains a separate meetup.com Pro account. R-Ladies groups must apply directly to R-Ladies for acceptance into their program. They will not be automatically entered into the RUGS meetup.com Pro account.\nThe R Consortium maintains the right to terminate the RUG’s Pro program at any time. Additionally, The R Consortium has the right to terminate a group’s participation in the meetup.com Pro program if they do not comply with the requirements specified in the Code of Conduct.\n\n\n\n\n2024 Conference Grants\nTo qualify for a RUGS program conference grant, an event must be focused on the R language, offer at least one full day of technical talks and presentations, and aim to attract participants with diverse backgrounds. RUGS conference grants are for conferences organized by non-profit or volunteer groups. If you seek a sponsorship for your professional event, please contact sponsorship@r-consortium.org.\nFor good examples of conferences, please see Bioconductor, Rencontres, and LatinR.\n\n\nRequirements\n\nTo be eligible for consideration, a conference must:\n\nBe organized around the R Language or demonstrate that there will be significant R content.\nThese are NOT workshops.\nHave a web page that provides basic typical information such as:\n\nThe theme or purpose of the conference\nThe date, time and location of the conference\nRegistration fees listed for classes of attendees (e.g. corporate, student etc.) and mechanism for people to register\nSponsorship details (R Consortium logo should not be posted until grant is approved and contract is signed) along with details on classes of sponsorship and any associated benefits\nA list of sponsors or alternate sources of funding\nA section on how to submit talks and a mechanism for people to submit talks\nA list of keynote speakers (if any)\nA schedule of talks and events\nA list of confirmed speakers\nInformation about travel and housing\nA code of conduct that uses or is compatible with the R Consortium’s Code of Conduct that provides information about how conference participants can report violations or seek help\n\n\n\n\nAfter Receiving a Grant\n\nApplicants must submit billing documentation (W9 or wire transfer form) within one week of contract signature.\nConference organizers must:\n\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on the conference website.\nProvide at least one full admission ticket for an R Consortium member.\nWrite a short report after the conference summarizing what happened, describing highlights, and providing key metrics for the conference, including demographics for the attendees, in a way that would be suitable for publication as an R Consortium blog post.\nOffer the R Consortium the same benefits that the conference offers to other sponsors at the same level of support.\nComply with local Covid-19 public health protocols.\n\n\nNote\nAny grant relating to a specific activity will be canceled if (a) the activity to which it relates is canceled without rescheduling or (b) the activity has otherwise not occurred within 365 days of the grant date.\n\n\n\nSpecial Projects Grants\nWe do not believe that these kinds of events comprise everything that can be done to support the R Community. With our Special Projects Grants categories, we hope to stimulate the imagination of local R community builders.\n\n\nRequirements\n\nA request for a special purpose grant must take the form of a formal proposal and include:\n\nA business case for the project\nThese are NOT workshops\nA description of how it will benefit the R Community\nA description of who will participate\nThe cost to participate\nExplaining how it will happen\nListing the work products that might result\nDetailing when and where the project will happen\nListing who will manage and produce the project\nDetailing how much it will cost\nInclude a detailed breakdown of how grant money will be spent\nHave a Code of Conduct\n\n\n\nAfter Receiving a Grant\n\nApplicants must submit billing documentation (W9 or wire transfer form) within one week of contract signature\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on any associated online websites or promotional material\nApplicant billing information must match applicant contact information\nParticipants must:\n\nEvent participants must adhere to the Code of Conduct\nComply with local COVID-19 public health protocols\n\n\n\n\nAlso, note that any training materials developed with R Consortium funds must be made publically available with an open source license.\n\n\nHow to Apply for a RUGS, Conference, or Special Projects Grant\nApply for a grant by filling out this form. Be sure to select the correct box on the form that indicates whether you are applying for a RUGS grant, a conference grant, or a special projects grant" + "text": "ISC working groups provide the mechanism through which the ISC can explore, fund, and manage large collaborative projects. There are primary two modes of collaboration that may make a proposal well suited to be a WG:\n\nThe advice or collaboration of subject matter experts is required to decide the merit or feasibility of a project.\nThe work required for the project requires the skills not possessed by a single individual, or the amount of work required is more than can be accomplished by a single person in a reasonable amount of time.\n\n\n\nYour project will be:\n\nVetted by the relevant experts\nSanctioned by the R Consortium\nReceive the attention of the R Foundation\nBecome visible to the greater R Community\nAdministrative support from the R Consortium\n\n\n\n\nMany working groups are open for anyone. Please see the R Consortium Public Calendar for the next WG meeting you might want to attend.\n\n\n\nCensus: Is developing package recommendations, and other materials for working with census data.\nHealth Technology Assessment (HTA): To cultivate a more collaborative and unified approach to Health Technology Assessment (HTA) analytics work that leverages the power of R to enhance transparency, efficiency, and consistency, accelerating the delivery of innovative treatments to patients.\nMarshaling and Serialization in R: Developing standard practices for marshalling and unmarshalling of R objects. Involve identifying current problems, raising awareness, coming up with technical solutions, which might require additions to base R.\nMultilingual R Documentation: Support multilingual documentation in R.\nR7 Package: Object-Oriented Programming. The R7 package is a new OOP system designed to be a successor to S3 and S4. It has been designed and implemented collaboratively by the R Consortium Object-Oriented Programming Working Group, which includes representatives from R-Core, BioConductor, RStudio/tidyverse, and the wider R community.\nR Certification: Is working to establish a common certification program for proficiency in R.\nR Repositories: Collaboratively exploring how to support, maintain, and improve the tooling for R package distribution.\nR Tables for Regulatory Submission (RTRS): Develop standards for creating tables that meet the requirements of FDA submission documents.\nR Validation Hub: Working to devise a standard for validating packages for the regulated Pharmaceutical industry and create a online repository that will be free to use.\nSubmissions: Focus on IT and platform challenges that must be addressed in order to make “all R” regulatory submissions.\n\n\nActive working groups have public mailing lists to facilitate discussions.\n\n\n\n\nhistoRicalg: This project aims to document and test older Fortran and C and other code that is still essential to the R ecosystem, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future.\nFuture-proof native APIs for R: Is working to assess current native API usage, gather community input, and work towards an easy-to-understand, consistent and verifiable API that will drive R language adoption.\nR IDEA: Now a Top Level Project. R Community Diversity and Inclusion is a group broadly considering how the R Consortium can best encourage and support diversity and inclusion in the R Community.\nUnified Framework for Distributed Computing in R: Exploring the feasibility of developing a common framework to standardize the programming of distributed applications in R.\nDistributed Computing: Endorse the design of a common abstraction for distributed data structures in R.\n\n\n\nR / Business: R users from different areas of business and financial services collaborating on events and advocacy of R.\nCode Coverage: Develop a tool that addresses feature and platform limitations of existing tools. Helping to improve R software quality through the development of a code coverage tool and promoting the use of code coverage more systematically within the R ecosystem.\n\n\n\n\n\nThe purpose of ISC working groups is to organize collaborative projects under governance of the ISC. Membership in ISC working groups is in principle open to anyone from the R Community who desires to participate. There is no requirement that membership in working groups be restricted to individuals who are employed by R Consortium member companies. Working groups are expected to undertake projects that will bring benefits to the R Community.\n\n\n\nR Consortium Working Groups are authorized by the Infrastructure Steering Committee and operate in accordance with the R Consortium By-Laws and the Charter of the ISC.\nThe ISC may disband a working group at any time at its sole discretion.\n\n\n\nWorking groups may or may not receive funding from the ISC according to the needs of the working group and the budget of the ISC. Budgeting periods are aligned with the R Consortium budgeting year, from January 1 to December 31.\nIf a working group receives funding from the ISC members can manage this budget and dispose of available funds for purposes and projects that have been previously determined by the ISC to be in the scope of the working group’s charter. Spending that represents a significant part of the working group’s budget must be approved by the Executive Director.\nWorking groups may not solicit funds from outside sources without permission of the ISC or the R Consortium’s Executive Director. This includes applying for grants organizations outside of the R Consortium.\nWorking groups may supplement their budgets with income from conferences or other activities. Working groups may not spend in excess of their R Consortium budget grant plus income collected to date without authorization in the form of an additional budget grant from the R Consortium.\nAny income generated by working groups from conferences or activities in excess of the amount to cover the working group’s expenses will be returned to the R Consortium’s general fund at the end of the budgeting period. It is expected that working groups will request a budget each year that is commensurate with the expected income earned and the activities planned for that year.\n\n\n\nWorking group members are expected to represent the best interests of the R Consortium at all times, being cognizant that their activities and behavior reflect directly on the reputation of the R Consortium.\nNo member of a working group, including its leader, may enter into any financial relationship, or legal contract that pertains to their role as a working group member.\nWhen speaking at conferences or other venues about work accomplished by a working group, working group members must properly attribute the work to the working group and promote the R Consortium and working group brand when appropriate.\n\n\n\nWorking groups are required to operate transparently in full public view to the greatest extent possible. This does not preclude holding smaller invitation-only working sessions or “executive” when privacy is warranted.\nWorking groups must keep minutes for all substantial meetings and place the meeting minutes in an appropriate folder of the GitHub repository allocated to the working group. Exceptions to this practice require the approval of the ISC or the Executive Director.\nAll working group activities must be in accordance with city, state and federal laws. Working group members should be regularly reminded that their activities must:\n\ncomply with United States Antitrust laws\nbe conducted according to the R Consortium Code of Conduct\ncomply with appropriate international regulations such as the GDPR regulations of the European Union" }, { - "objectID": "all-projects/2017-group-2.html", - "href": "all-projects/2017-group-2.html", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#benefits-of-forming-an-isc-working-group", + "href": "all-projects/isc-working-groups.html#benefits-of-forming-an-isc-working-group", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n\n\n\nFunded:\n$5,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://r-spatial.github.io/stars/\nSummary:\nThe stars project enables the processing Earth imagery data that is held on servers, without the need to download it to local hard driver. This project will (i) create software to run a back-end, (ii) develop scripts and tutorials that explain how such a data server and processing backend can be set up, and (iii) create an instance of such a backend in the AWS cloud that can be used for testing and evaluation purposes.\n\n\n\nFunded:\n$10,000\nProposed by:\nHenrik Bengtsson\nWebsite:\nhttps://github.com/HenrikBengtsson/\nSummary:\nThe objective of the Future Framework implemented in the future package is to simplify how parallel and distributed processing is conducted in R. This project aims to provide a formal Future API specification and provide a test framework for validating the conformance of existing (e.g. future.batchtools and future.callr) and to-come third-party parallel backends to the Future framework.\n\n\n\nFunded:\n$10,000\nProposed by:\nInaki Ucar\nWebsite:\nhttps://github.com/r-quantities/quantities and https://www.r-spatial.org/r/2018/08/31/quantities-final.html\nSummary:\nThe ‘units’ package has become the reference for quantity calculus in R, with a wide and welcoming response from the R community. Along the same lines, the ‘errors’ package integrates and automatises error propagation and printing for R vectors. A significant fraction of R users, both practitioners and researchers, use R to analyse measurements, and would benefit from a joint processing of quantity values with errors.\nThis project not only aims at orchestrating units and errors in a new data type, but will also extend the existing frameworks (compatibility with base R as well as other frameworks such as the tidyverse) and standardise how to import/export data with units and errors.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Beare\nWebsite:\nhttps://github.com/richardbeare/RConsortiumSwig\nSummary:\nThe Simplified Wrapper and Interface Generator (SWIG) is a tool for automatically generating interface code between interpreters, including R, and a C or C++ library. The R module needs to be updated to support modern developments in R and the rest of SWIG. This project aims to make the R module conform to the recommended SWIG standards and thus ensure that there is support for R in the future. We hope that this project will be the first step in allowing SWIG generated R code using reference classes." + "text": "Your project will be:\n\nVetted by the relevant experts\nSanctioned by the R Consortium\nReceive the attention of the R Foundation\nBecome visible to the greater R Community\nAdministrative support from the R Consortium" }, { - "objectID": "all-projects/2017-group-2.html#funded-isc-grants-2017-2", - "href": "all-projects/2017-group-2.html#funded-isc-grants-2017-2", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#join-a-working-group", + "href": "all-projects/isc-working-groups.html#join-a-working-group", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n\n\n\nFunded:\n$5,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://r-spatial.github.io/stars/\nSummary:\nThe stars project enables the processing Earth imagery data that is held on servers, without the need to download it to local hard driver. This project will (i) create software to run a back-end, (ii) develop scripts and tutorials that explain how such a data server and processing backend can be set up, and (iii) create an instance of such a backend in the AWS cloud that can be used for testing and evaluation purposes.\n\n\n\nFunded:\n$10,000\nProposed by:\nHenrik Bengtsson\nWebsite:\nhttps://github.com/HenrikBengtsson/\nSummary:\nThe objective of the Future Framework implemented in the future package is to simplify how parallel and distributed processing is conducted in R. This project aims to provide a formal Future API specification and provide a test framework for validating the conformance of existing (e.g. future.batchtools and future.callr) and to-come third-party parallel backends to the Future framework.\n\n\n\nFunded:\n$10,000\nProposed by:\nInaki Ucar\nWebsite:\nhttps://github.com/r-quantities/quantities and https://www.r-spatial.org/r/2018/08/31/quantities-final.html\nSummary:\nThe ‘units’ package has become the reference for quantity calculus in R, with a wide and welcoming response from the R community. Along the same lines, the ‘errors’ package integrates and automatises error propagation and printing for R vectors. A significant fraction of R users, both practitioners and researchers, use R to analyse measurements, and would benefit from a joint processing of quantity values with errors.\nThis project not only aims at orchestrating units and errors in a new data type, but will also extend the existing frameworks (compatibility with base R as well as other frameworks such as the tidyverse) and standardise how to import/export data with units and errors.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Beare\nWebsite:\nhttps://github.com/richardbeare/RConsortiumSwig\nSummary:\nThe Simplified Wrapper and Interface Generator (SWIG) is a tool for automatically generating interface code between interpreters, including R, and a C or C++ library. The R module needs to be updated to support modern developments in R and the rest of SWIG. This project aims to make the R module conform to the recommended SWIG standards and thus ensure that there is support for R in the future. We hope that this project will be the first step in allowing SWIG generated R code using reference classes." + "text": "Many working groups are open for anyone. Please see the R Consortium Public Calendar for the next WG meeting you might want to attend." }, { - "objectID": "all-projects/2022-group-2.html", - "href": "all-projects/2022-group-2.html", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#active-working-groups", + "href": "all-projects/isc-working-groups.html#active-working-groups", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n\n\n\nFunded:\n$8,000\nProposed by:\nMauricio “Pacho” Vargas Sepulveda\nSummary:\nThe D3po: R Package for Easy Interactive D3 Visualization With Shiny project plans to finish a new version of d3po and include maps and other plot types available in highcharts. This project aims to provide out-of-the-box high-quality visualizations with minimum time and coding effort.\nThe ultimate aim of the project is to produce a package that:\n\nOffers integration with Shiny\nEnables downloading the charts in different image formats (png, jpeg, svg)\nEnables downloading the data in different formats (json, csv, xlsx)\nCan produce high-quality results with a minimal number of lines of code\n\n“I figured out that d3po sounded like c3po from Star Wars, also a Chilean will read it as “dee three POH”, and “poh” is Chilean slang that reflects the “necessity is the mother of invention” spirit that Chileans have.” - Mauricio “Pacho” Vargas Sepulveda\n\n\n\nFunded:\n$8,000\nProposed by:\nMaëlle Salmon\nSummary:\nTooling and Guidance for Translations of Markdown-Based R Content (Quarto, R Markdown) focuses on the achievement of a first version of translated material, both technically (tooling to create an automatically translated document) and linguistically (glossary). With this proposal, the project will aim to share the rOpenSci workflow with others via the creation of an R package including extensive documentation.\n\n\n\nFunded:\n$22,000\nProposed by:\nSimon Urbanek\nSummary:\nThe Online Submission and Review Infrastructure for the R Journal ISC-funded project aims to address problems with the current all-manual revision infrastructure for submissions in the R Journal. The project proposes the development and deployment of an online, web-based system that ties into the existing status management infrastructure but allows for reviews and submission management to be performed online. The ISC funds will be used to assist with the development of an online front-end for the management of articles for the R Journal, including submission, checking, and peer-review tracking of articles. The system will leverage the existing rj and rjtools packages which provide the back-end, but will add a web interface to the process from submission to reviews and article management.\n\n\n\nFunded:\n$6,000\nProposed by:\nBen Ubah\nSummary:\nThe Upgrading SatRdays Website Template project addresses the SatRdays event website templates, which are used by the R community looking to run a SatRday event. The goal of this project is to upgrade the SatRdays website template with a view to make it easy for R community organizers to spin up their own SatRday website without deep knowledge of technologies like Hugo (upon which the current template is based using an R package like blogdown. There will also be documentation of this development with easy-to-follow instructions that are beginner-friendly.\n\n\n\nFunded:\n$25,000\nProposed by:\nOrhun Aydin\nSummary:\nThe Building the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure project proposes to deliver a set of self-contained online training modules on spatial and spatiotemporal data science with R. The modules will consist of focus-areas pertinent to topics frequently requested by the spatial R community using a large number of packages from CRAN Spatial Task View and Spatiotemporal Task View. The deliverable will provide the R Consortium and community with the materials needed to solicit more lessons from the community while ensuring uniformity across lessons." + "text": "Census: Is developing package recommendations, and other materials for working with census data.\nHealth Technology Assessment (HTA): To cultivate a more collaborative and unified approach to Health Technology Assessment (HTA) analytics work that leverages the power of R to enhance transparency, efficiency, and consistency, accelerating the delivery of innovative treatments to patients.\nMarshaling and Serialization in R: Developing standard practices for marshalling and unmarshalling of R objects. Involve identifying current problems, raising awareness, coming up with technical solutions, which might require additions to base R.\nMultilingual R Documentation: Support multilingual documentation in R.\nR7 Package: Object-Oriented Programming. The R7 package is a new OOP system designed to be a successor to S3 and S4. It has been designed and implemented collaboratively by the R Consortium Object-Oriented Programming Working Group, which includes representatives from R-Core, BioConductor, RStudio/tidyverse, and the wider R community.\nR Certification: Is working to establish a common certification program for proficiency in R.\nR Repositories: Collaboratively exploring how to support, maintain, and improve the tooling for R package distribution.\nR Tables for Regulatory Submission (RTRS): Develop standards for creating tables that meet the requirements of FDA submission documents.\nR Validation Hub: Working to devise a standard for validating packages for the regulated Pharmaceutical industry and create a online repository that will be free to use.\nSubmissions: Focus on IT and platform challenges that must be addressed in order to make “all R” regulatory submissions.\n\n\nActive working groups have public mailing lists to facilitate discussions." }, { - "objectID": "all-projects/2022-group-2.html#funded-isc-grants-2022-2", - "href": "all-projects/2022-group-2.html#funded-isc-grants-2022-2", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#completed-working-groups", + "href": "all-projects/isc-working-groups.html#completed-working-groups", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n\n\n\nFunded:\n$8,000\nProposed by:\nMauricio “Pacho” Vargas Sepulveda\nSummary:\nThe D3po: R Package for Easy Interactive D3 Visualization With Shiny project plans to finish a new version of d3po and include maps and other plot types available in highcharts. This project aims to provide out-of-the-box high-quality visualizations with minimum time and coding effort.\nThe ultimate aim of the project is to produce a package that:\n\nOffers integration with Shiny\nEnables downloading the charts in different image formats (png, jpeg, svg)\nEnables downloading the data in different formats (json, csv, xlsx)\nCan produce high-quality results with a minimal number of lines of code\n\n“I figured out that d3po sounded like c3po from Star Wars, also a Chilean will read it as “dee three POH”, and “poh” is Chilean slang that reflects the “necessity is the mother of invention” spirit that Chileans have.” - Mauricio “Pacho” Vargas Sepulveda\n\n\n\nFunded:\n$8,000\nProposed by:\nMaëlle Salmon\nSummary:\nTooling and Guidance for Translations of Markdown-Based R Content (Quarto, R Markdown) focuses on the achievement of a first version of translated material, both technically (tooling to create an automatically translated document) and linguistically (glossary). With this proposal, the project will aim to share the rOpenSci workflow with others via the creation of an R package including extensive documentation.\n\n\n\nFunded:\n$22,000\nProposed by:\nSimon Urbanek\nSummary:\nThe Online Submission and Review Infrastructure for the R Journal ISC-funded project aims to address problems with the current all-manual revision infrastructure for submissions in the R Journal. The project proposes the development and deployment of an online, web-based system that ties into the existing status management infrastructure but allows for reviews and submission management to be performed online. The ISC funds will be used to assist with the development of an online front-end for the management of articles for the R Journal, including submission, checking, and peer-review tracking of articles. The system will leverage the existing rj and rjtools packages which provide the back-end, but will add a web interface to the process from submission to reviews and article management.\n\n\n\nFunded:\n$6,000\nProposed by:\nBen Ubah\nSummary:\nThe Upgrading SatRdays Website Template project addresses the SatRdays event website templates, which are used by the R community looking to run a SatRday event. The goal of this project is to upgrade the SatRdays website template with a view to make it easy for R community organizers to spin up their own SatRday website without deep knowledge of technologies like Hugo (upon which the current template is based using an R package like blogdown. There will also be documentation of this development with easy-to-follow instructions that are beginner-friendly.\n\n\n\nFunded:\n$25,000\nProposed by:\nOrhun Aydin\nSummary:\nThe Building the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure project proposes to deliver a set of self-contained online training modules on spatial and spatiotemporal data science with R. The modules will consist of focus-areas pertinent to topics frequently requested by the spatial R community using a large number of packages from CRAN Spatial Task View and Spatiotemporal Task View. The deliverable will provide the R Consortium and community with the materials needed to solicit more lessons from the community while ensuring uniformity across lessons." + "text": "histoRicalg: This project aims to document and test older Fortran and C and other code that is still essential to the R ecosystem, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future.\nFuture-proof native APIs for R: Is working to assess current native API usage, gather community input, and work towards an easy-to-understand, consistent and verifiable API that will drive R language adoption.\nR IDEA: Now a Top Level Project. R Community Diversity and Inclusion is a group broadly considering how the R Consortium can best encourage and support diversity and inclusion in the R Community.\nUnified Framework for Distributed Computing in R: Exploring the feasibility of developing a common framework to standardize the programming of distributed applications in R.\nDistributed Computing: Endorse the design of a common abstraction for distributed data structures in R." }, { - "objectID": "all-projects/2021-group-2.html", - "href": "all-projects/2021-group-2.html", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#inactive-working-groups", + "href": "all-projects/isc-working-groups.html#inactive-working-groups", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n\n\n\nFunded:\n$17,000\nProposed by:\nEdzer Pebesma\nSummary:\nThe retirement of rgdal, rgeos, and maptools presents a significant impact on the CRAN community, these packages are scheduled for retirement by the end of 2023. In response, a proposal for an ISC Funded project has been put forward to tackle this challenge. Preparing CRAN for the Retirement of rgdal, rgeos and maptools focuses on finding suitable alternatives for the functionalities offered by the retiring packages and providing guidance to package maintainers on necessary adjustments and migration steps. By doing so, it aims to minimize disruption to CRAN packages and existing R scripts, ensuring the overall stability and robustness of the CRAN ecosystem. The retirement process will simplify the maintenance of the “R Spatial stack” and contribute to the long-term health of the CRAN ecosystem.\n\n\n\nFunded:\n$4,840\nProposed by:\nLampros Mouselimis\nSummary:\nR Package for the ICESat-2 Altimeter Data aims to create an R package specifically designed for accessing ICESat-2 satellite data through the OpenAltimetry API. Addressing the lack of existing R packages for downloading geospatial data in specific formats, the package will enable R users to download ICESat-2 data, list available data based on a bounding box or named location, create simple feature objects using the sf package, and visualize the output data using popular geospatial R packages such as leaflet or mapview. The proposed ISC-funded project will enhance the capabilities of R users working with geospatial datasets, facilitating data exploration, analysis, and visualization within the R environment for improved geospatial research and applications.\n\n\n\nFunded:\n$17,000\nProposed by:\nKirill Müller\nSummary:\nThe Future of DBI focuses on the advancements achieved with support from the ISC, including bringing the existing DBI backend, RSQLite, up to specification and implementing two new compliant backends, RMariaDB and RPostgres. This project mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Ensuring compatibility with evolving elements such as OS, databases, R, and other packages is vital for long-term success. The proposal also includes modules for redesigning the database interface, efficient storage, and arithmetic for big integers, decimals with fixed width and precision, investigating Apache Arrow as an interface, and relational data models with R, with the option to adjust the scope as needed.\n\n\n\nFunded:\n$5,200\nProposed by:\nTimothy A. Ogunleye\nSummary:\nWe want to conduct training workshops on data science and machine learning with R. Out of nearly 60 countries that form the continent, we carefully selected four countries – one from each of the North, South, West, and East Africa. Nigeria is considered for the West Africa, Kenya is chosen from the East Africa, Sudan from the North Africa, while Zimbabwe is selected from the South African countries. We have 2 volunteers each, who are experts in the field of data science and machine learning with R, from the selected countries. We have also recruited 2 tutors for each country, making a total of 8. These tutors would serve as training assistants to the coordinators. Training materials are to be prepared by the coordinators. Therefore, the coordinators are expected to teach the contents of the training materials." + "text": "R / Business: R users from different areas of business and financial services collaborating on events and advocacy of R.\nCode Coverage: Develop a tool that addresses feature and platform limitations of existing tools. Helping to improve R software quality through the development of a code coverage tool and promoting the use of code coverage more systematically within the R ecosystem." }, { - "objectID": "all-projects/2021-group-2.html#funded-isc-grants-2021-2", - "href": "all-projects/2021-group-2.html#funded-isc-grants-2021-2", - "title": "R Consortium", + "objectID": "all-projects/isc-working-groups.html#isc-regulations-and-guidelines", + "href": "all-projects/isc-working-groups.html#isc-regulations-and-guidelines", + "title": "ISC Working Groups", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n\n\n\nFunded:\n$17,000\nProposed by:\nEdzer Pebesma\nSummary:\nThe retirement of rgdal, rgeos, and maptools presents a significant impact on the CRAN community, these packages are scheduled for retirement by the end of 2023. In response, a proposal for an ISC Funded project has been put forward to tackle this challenge. Preparing CRAN for the Retirement of rgdal, rgeos and maptools focuses on finding suitable alternatives for the functionalities offered by the retiring packages and providing guidance to package maintainers on necessary adjustments and migration steps. By doing so, it aims to minimize disruption to CRAN packages and existing R scripts, ensuring the overall stability and robustness of the CRAN ecosystem. The retirement process will simplify the maintenance of the “R Spatial stack” and contribute to the long-term health of the CRAN ecosystem.\n\n\n\nFunded:\n$4,840\nProposed by:\nLampros Mouselimis\nSummary:\nR Package for the ICESat-2 Altimeter Data aims to create an R package specifically designed for accessing ICESat-2 satellite data through the OpenAltimetry API. Addressing the lack of existing R packages for downloading geospatial data in specific formats, the package will enable R users to download ICESat-2 data, list available data based on a bounding box or named location, create simple feature objects using the sf package, and visualize the output data using popular geospatial R packages such as leaflet or mapview. The proposed ISC-funded project will enhance the capabilities of R users working with geospatial datasets, facilitating data exploration, analysis, and visualization within the R environment for improved geospatial research and applications.\n\n\n\nFunded:\n$17,000\nProposed by:\nKirill Müller\nSummary:\nThe Future of DBI focuses on the advancements achieved with support from the ISC, including bringing the existing DBI backend, RSQLite, up to specification and implementing two new compliant backends, RMariaDB and RPostgres. This project mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Ensuring compatibility with evolving elements such as OS, databases, R, and other packages is vital for long-term success. The proposal also includes modules for redesigning the database interface, efficient storage, and arithmetic for big integers, decimals with fixed width and precision, investigating Apache Arrow as an interface, and relational data models with R, with the option to adjust the scope as needed.\n\n\n\nFunded:\n$5,200\nProposed by:\nTimothy A. Ogunleye\nSummary:\nWe want to conduct training workshops on data science and machine learning with R. Out of nearly 60 countries that form the continent, we carefully selected four countries – one from each of the North, South, West, and East Africa. Nigeria is considered for the West Africa, Kenya is chosen from the East Africa, Sudan from the North Africa, while Zimbabwe is selected from the South African countries. We have 2 volunteers each, who are experts in the field of data science and machine learning with R, from the selected countries. We have also recruited 2 tutors for each country, making a total of 8. These tutors would serve as training assistants to the coordinators. Training materials are to be prepared by the coordinators. Therefore, the coordinators are expected to teach the contents of the training materials." + "text": "The purpose of ISC working groups is to organize collaborative projects under governance of the ISC. Membership in ISC working groups is in principle open to anyone from the R Community who desires to participate. There is no requirement that membership in working groups be restricted to individuals who are employed by R Consortium member companies. Working groups are expected to undertake projects that will bring benefits to the R Community.\n\n\n\nR Consortium Working Groups are authorized by the Infrastructure Steering Committee and operate in accordance with the R Consortium By-Laws and the Charter of the ISC.\nThe ISC may disband a working group at any time at its sole discretion.\n\n\n\nWorking groups may or may not receive funding from the ISC according to the needs of the working group and the budget of the ISC. Budgeting periods are aligned with the R Consortium budgeting year, from January 1 to December 31.\nIf a working group receives funding from the ISC members can manage this budget and dispose of available funds for purposes and projects that have been previously determined by the ISC to be in the scope of the working group’s charter. Spending that represents a significant part of the working group’s budget must be approved by the Executive Director.\nWorking groups may not solicit funds from outside sources without permission of the ISC or the R Consortium’s Executive Director. This includes applying for grants organizations outside of the R Consortium.\nWorking groups may supplement their budgets with income from conferences or other activities. Working groups may not spend in excess of their R Consortium budget grant plus income collected to date without authorization in the form of an additional budget grant from the R Consortium.\nAny income generated by working groups from conferences or activities in excess of the amount to cover the working group’s expenses will be returned to the R Consortium’s general fund at the end of the budgeting period. It is expected that working groups will request a budget each year that is commensurate with the expected income earned and the activities planned for that year.\n\n\n\nWorking group members are expected to represent the best interests of the R Consortium at all times, being cognizant that their activities and behavior reflect directly on the reputation of the R Consortium.\nNo member of a working group, including its leader, may enter into any financial relationship, or legal contract that pertains to their role as a working group member.\nWhen speaking at conferences or other venues about work accomplished by a working group, working group members must properly attribute the work to the working group and promote the R Consortium and working group brand when appropriate.\n\n\n\nWorking groups are required to operate transparently in full public view to the greatest extent possible. This does not preclude holding smaller invitation-only working sessions or “executive” when privacy is warranted.\nWorking groups must keep minutes for all substantial meetings and place the meeting minutes in an appropriate folder of the GitHub repository allocated to the working group. Exceptions to this practice require the approval of the ISC or the Executive Director.\nAll working group activities must be in accordance with city, state and federal laws. Working group members should be regularly reminded that their activities must:\n\ncomply with United States Antitrust laws\nbe conducted according to the R Consortium Code of Conduct\ncomply with appropriate international regulations such as the GDPR regulations of the European Union" }, { - "objectID": "blog/index.html", - "href": "blog/index.html", - "title": "R Consortium", + "objectID": "all-projects/callforproposals.html", + "href": "all-projects/callforproposals.html", + "title": "The 2024 ISC Grant Program", "section": "", - "text": "Want to contribute to the R Consortium blog? Please review our Blog Post Guidelines.\nR Consortium blog archive (2015-2024)\n\n\n\n\n\n\n \n \n \n Order By\n Default\n \n Date - Oldest\n \n \n Date - Newest\n \n \n Title\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n\nDate\n\n\nTitle\n\n\nAuthor\n\n\n\n\n\n\nOct 30, 2024\n\n\nStreamlining API Integration: Jon Harmon’s Journey with the api2r Package\n\n\nR Consortium\n\n\n\n\nOct 23, 2024\n\n\nConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers\n\n\nR Consortium\n\n\n\n\nOct 18, 2024\n\n\nEndophytes, Oaks, and R: How R-Ladies Morelia is Cultivating Science and Community in Morelia, Mexico\n\n\nR Consortium\n\n\n\n\nOct 16, 2024\n\n\nThe U.S. Federal Reserve quarterly model in R\n\n\nGuest Blog Post\n\n\n\n\nOct 15, 2024\n\n\nEmpowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative\n\n\nR Consortium\n\n\n\n\nOct 14, 2024\n\n\nR/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track\n\n\nR Consortium\n\n\n\n\nOct 9, 2024\n\n\nUsing R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research\n\n\nR Consortium\n\n\n\n\nOct 8, 2024\n\n\nCakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group\n\n\nR Consortium\n\n\n\n\nOct 1, 2024\n\n\nAnnouncing the Health Technology Assessment (HTA) Working Group\n\n\nR Consortium\n\n\n\n\nSep 23, 2024\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\n\nR Consortium\n\n\n\n\nSep 20, 2024\n\n\nFree Boba Tea and Technical R Topics Lure Young Learners to New Brunei R User Group\n\n\nR Consortium\n\n\n\n\nSep 12, 2024\n\n\nEmpowering Data Science: How R is Transforming Research in Cameroon\n\n\nR Consortium\n\n\n\n\nSep 10, 2024\n\n\nThank You, Joseph Rickert: A Legacy of Leadership and Innovation in the R Community\n\n\nR Consortium\n\n\n\n\nSep 6, 2024\n\n\nR-Ladies Bariloche in Argentina: Fostering a Different Approach to Leadership\n\n\nR Consortium\n\n\n\n\nAug 30, 2024\n\n\nThe 2024 ISC Grant Program will begin Accepting Applications Soon!\n\n\nR Consortium\n\n\n\n\nAug 27, 2024\n\n\nR4SocialScience: Empowering Social Science Research with R in India\n\n\nR Consortium\n\n\n\n\nAug 26, 2024\n\n\nNews from R Submissions Working Group – Pilot 3 Successfully Reviewed by FDA\n\n\nR Consortium\n\n\n\n\nAug 20, 2024\n\n\nBuilding Bridges in Haifa, Israel: How the New R User Group in Haifa is Establishing a Diverse R Community\n\n\nR Consortium\n\n\n\n\nAug 12, 2024\n\n\nA New R Community in Ahmedabad, India, focused on Clinical Research and Pharmaceutical Industries\n\n\nR Consortium\n\n\n\n\nAug 2, 2024\n\n\nR Consortium Grants Committee Announces New Chair\n\n\nR Consortium\n\n\n\n\nAug 1, 2024\n\n\nPharma RUG: The Rise of R in China’s Pharmaceutical Industry\n\n\nR Consortium\n\n\n\n\nJul 26, 2024\n\n\nR-Ladies Rome: Empowering Women in Data Science Through Collaboration and Innovation\n\n\nR Consortium\n\n\n\n\nJul 22, 2024\n\n\nEmpowering the R Community: Insights from Myles Mitchell of the Leeds Data Science Group\n\n\nR Consortium\n\n\n\n\nJul 12, 2024\n\n\nKolkata R User Group: A Rich History with Statistics\n\n\nR Consortium\n\n\n\n\nJul 3, 2024\n\n\nDiving into R with Isabella Velasquez: Perspectives from R-Ladies Seattle\n\n\nR Consortium\n\n\n\n\nJul 2, 2024\n\n\nR Consortium’s Submission Working Group: Advancing R for Regulatory Success at PharmaSUG 2024\n\n\nR Consortium\n\n\n\n\nJun 25, 2024\n\n\nR Addicts Paris: Promoting Diversity in R\n\n\nR Consortium\n\n\n\n\nJun 24, 2024\n\n\nThe Crucial Role of Release Control in R for Healthcare Organizations\n\n\nGuest Blog Post\n\n\n\n\nJun 17, 2024\n\n\nBridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students\n\n\nR Consortium\n\n\n\n\nJun 11, 2024\n\n\nKeith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R\n\n\nR Consortium\n\n\n\n\nJun 4, 2024\n\n\nFull-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks\n\n\nR Consortium\n\n\n\n\nMay 30, 2024\n\n\nR4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions\n\n\nR Consortium\n\n\n\n\nMay 29, 2024\n\n\nEnhancing Clinical Trial Data Sharing with R Consortium’s R Submissions Working Group\n\n\nR Consortium\n\n\n\n\nMay 29, 2024\n\n\nOne More Step Forward: The R Consortium Submission Working Group’s Presentation to Swissmedic on Regulatory Submission using R and Shiny\n\n\nGuest Authors\n\n\n\n\nMay 24, 2024\n\n\nCollaborative Growth: The Botswana R User Group and Regional Partnerships\n\n\nR Consortium\n\n\n\n\nMay 16, 2024\n\n\nGergely Daróczi’s Journey: Empowering R Users in Hungary\n\n\nR Consortium\n\n\n\n\nMay 15, 2024\n\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\n\nR Consortium\n\n\n\n\nMay 14, 2024\n\n\nTackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research\n\n\nR Consortium\n\n\n\n\nMay 13, 2024\n\n\nThe Evolution of Melbourne’s Business Analytics and R Business User Group\n\n\nR Consortium\n\n\n\n\nApr 30, 2024\n\n\nR/Medicine is coming June 10-14, 2024 – See Top Five R Medicine Talks from Previous Years\n\n\nR Consortium\n\n\n\n\nApr 26, 2024\n\n\nBridging Gaps: Tunis R User Group’s Journey in Democratizing R in Bioinformatics\n\n\nR Consortium\n\n\n\n\nApr 19, 2024\n\n\nNavigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors\n\n\nR Consortium\n\n\n\n\nApr 18, 2024\n\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database\n\n\nR Consortium\n\n\n\n\nApr 15, 2024\n\n\nDecade of Data: Celebrating 10 Years of Innovation at the New York R Conference\n\n\nR Consortium\n\n\n\n\nApr 10, 2024\n\n\nThe Impact of R on Academic Excellence in Manchester, UK\n\n\nR Consortium\n\n\n\n\nApr 8, 2024\n\n\nEARL Early Bird Tickets Are Now Available!\n\n\nR Consortium\n\n\n\n\nApr 5, 2024\n\n\nR/Medicine Coming June 10-14, 2024 – Call for Abstracts Open – Keynotes Announced\n\n\nR Consortium\n\n\n\n\nApr 4, 2024\n\n\nUnlocking Financial Insights: Join Us at the R Finance Conference\n\n\nR Consortium\n\n\n\n\nMar 28, 2024\n\n\nEmpowering R Enthusiasts: SatRDays London 2024 Unveiled\n\n\nR Consortium\n\n\n\n\nMar 27, 2024\n\n\nAligning Beliefs and Profession: Using R in Protecting the Penobscot Nation’s Traditional Lifeways\n\n\nR Consortium\n\n\n\n\nMar 26, 2024\n\n\nElevate Your R Community with the 2024 RUGS Grant Program\n\n\nR Consortium\n\n\n\n\nMar 19, 2024\n\n\nOffa R Users Group: Empowering Data-Driven Education in Nigeria\n\n\nR Consortium\n\n\n\n\nMar 13, 2024\n\n\nR-Ladies Goiânia: Promoting Diversity and Inclusion in Local R Community\n\n\nR Consortium\n\n\n\n\nMar 12, 2024\n\n\nISC-funded Grant: Secure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\n\nR Consortium\n\n\n\n\nMar 7, 2024\n\n\nThe Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics\n\n\nR Consortium\n\n\n\n\nMar 1, 2024\n\n\nApply Now! R Consortium Infrastructure Steering Committee (ISC) Grant Program Open for Proposals!\n\n\nR Consortium\n\n\n\n\nFeb 28, 2024\n\n\nThe R Consortium 2023: A Year of Growth and Innovation\n\n\nR Consortium\n\n\n\n\nFeb 27, 2024\n\n\nMoffitt Cancer Center Bio-Data Club’s New Chapter in Spatial Data Analysis and Enhanced Hackathon Collaboration\n\n\nR Consortium\n\n\n\n\nFeb 23, 2024\n\n\nRecap: R Validation Hub Community Meeting\n\n\nR Consortium\n\n\n\n\nFeb 21, 2024\n\n\nJoin our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts\n\n\nR Consortium\n\n\n\n\nFeb 20, 2024\n\n\nR-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women\n\n\nR Consortium\n\n\n\n\nFeb 14, 2024\n\n\nUnlocking the Power of R for Insurance and Actuarial Science: Webinar Series Recap\n\n\nR Consortium\n\n\n\n\nFeb 13, 2024\n\n\nAnn Arbor R User Group: Harnessing the Power of R and GitHub\n\n\nR Consortium\n\n\n\n\nFeb 12, 2024\n\n\nUnraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024\n\n\nR Consortium\n\n\n\n\nFeb 8, 2024\n\n\nR Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!\n\n\nR Consortium\n\n\n\n\nFeb 7, 2024\n\n\nImproving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade\n\n\nR Consortium\n\n\n\n\nFeb 6, 2024\n\n\nJoin Our Upcoming Webinar: Master Tidy Finance & Access Financial Data with Expert Christoph Scheuch\n\n\nR Consortium\n\n\n\n\nFeb 2, 2024\n\n\nNatalia Andriychuk on RUGs, Pfizer R Center of Excellence, and Open Source Projects: Fostering R Communities Inside and Out\n\n\nR Consortium\n\n\n\n\n\nNo matching items" + "text": "A major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nTechnical Infrastructure projects that have be funded include:\n\nR-hub, a centralized tool for checking R packages\nTesting DBI and improving key open source database backends.\nImprovements in packages such as mapview and sf\nImproving Translations in R\nOngoing infrastructural development for R on Windows and macOS\n\nSocial Infrastructure projects include:\n\nSatRDays, bootstrapping a system for local R conferences.\nData-Driven Discovery and Tracking of R Consortium Activities\n\nThe Infrastructure Steering Committee (ISC) projects should have a focus on technical infrastructure or involve software development to support social infrastructure. Conferences, training sessions, and user groups will be funded through the RUGS program.\nTo apply for an ISC grant please continue with the instructions below. To seek funding for a conference, training session or user group please apply through the RUGS program page.\n\n\nThe ISC is interested in projects that:\n\nAre likely to have a broad impact on the R community.\nHave a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it up into smaller chunks (a good example of this done is with the DBI/DBItest project submission, where multiple proposals came in over time to address the various needs).\nHave a low-to-medium risk with a low-to-medium reward. The ISC tends not fund high-risk, high-reward projects.\n\nWhile all projects are considered, the ISC generally does not accept projects that:\n\nImpact only a small part of the R community\nRequest conference, workshop, or meetup sponsorship. For these, you should look at our user group program or connect with the marketing committee for larger events.\nAre very exploratory. These are better to be pursued through the working group program.\n\n\n\n\nPlease provide a 2 to 5 page proposal that describes the problem you want to solve. We expect submissions to include these components:\n\nThe Problem: What problem do you want to solve? Why is it a problem? Who does it affect? What will solving the problem enable? This section should include a brief summary of existing work, such as R packages that may be relevant. If you are proposing a change to R itself, you must include a letter of support from a member of R Core.\nThe Plan: How are you going to solve the problem? Include the concrete actions you will take and an estimated timeline. What are likely failure modes and how will you recover from them?\nThe Team: Who will work on the project? Briefly describe all participants, and the skills they will bring to the project.\nProject Milestones: Outline the milestones for development and how much funding will be required for each stage (as payments will be tied to project milestone completion). Each milestone should specify the work to be done and the expected outcomes, providing enough detail for the ISC to understand the scope of the project work and assess the likelihood of success.\nHow Can The ISC Help: Please describe how you think the ISC can help. If you are looking for a cash grant include a detailed itemized budget and spending plan. We expect that most of the budget will be allocated for labor costs. We do not cover indirect costs. The ISC grants cannot cover such things as travel, lodging, food, journal publication fees, or personal hardware. Cloud services may be covered if they are specific to the project and the project period. The ISC reserves the right to vet how funds are used for each project separately. If in doubt, please reach out to us. If you are seeking to start an ISC working group, then please describe the goals of the group and provide the name of the individual who will be committed to leading and managing the group’s activities. Also, describe how you think the ISC can help promote your project.\nDissemination: How will you ensure that your work is available to the widest number of people? Please specify the open-source or creative commons license(s) you will use, how you will host your code so that others can contribute, and how you will publicize your work. We encourage you to plan content to be shared quarterly on the R Consortium blog.\n\nThe ISC has a limited grant budget, and we want to ensure that funded projects deliver the maximum benefit to the community. Successful proposals show well-defined milestones, with initial work completed to minimize delivery risk, e.g., upfront research and well-defined action plans.\nIf you would like a template to help you structure your proposal, we encourage you to use one contributed by Steph Locke at https://github.com/RConsortium/isc-proposal.\nWe encourage you to seek feedback from the community before formally submitting your proposal. You are welcome to email individual committee members who might be particularly interested in your proposal to get their informal opinion, and you may want to publicize it more widely to get feedback from the broader R community.\n\n\n\nOnce you have completed your proposal, create a self-contained PDF and complete this form (requires signing in via a Google Account). When you submit the form, you should see a response page saying “Thank you for your proposal!” Soon thereafter, you will receive an email from forms-receipts-noreply@google.com with all the details of your submission. If you do not receive that email, please be sure to check your spam folder. If you do not see it, reach out to us as soon as possible.\nPlease note that the R Consortium utilizes a standard agreement for all funded projects selected in an effort to streamline the award process and to fund the greatest amount of projects as possible. The standard agreement is available for review in advance: Individual Consultant Agreement for R Consortium ISC Projects – 20170622.\nIf you have any questions please email proposal@r-consortium.org.\n\n\n\n\n\n\nMarch 1, 2024 – Grant Application period opens\nApril 1, 2024 – Grant Application period closes, 11:59pm US ET\nMay 1, 2024 – All accepted grantees are contacted by the ISC\nJune 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nSeptember 1, 2024 – Grant Application period opens\nOctober 1, 2024 – Grant Application period close, 11:59pm US ET\nNovember 1, 2024 – All accepted grantees are contacted by the ISC\nDecember 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nAll proposals will be read and reviewed by the Chair of the ISC and assigned to a committee member for detailed review. Proposals will be reviewed as a group, and you will be notified of the decision by the dates listed above.\n50% of the grant will be paid out when the contract is signed and 50% upon completion.\nAll accepted projects will be published on the R Consortium blog.\nWe review this process yearly to ensure that the process is as smooth as possible, and to incorporate the knowledge gained from putting it into practice. All decisions to accept or reject proposals will be made by R Consortium in its sole discretion and shall be final.\nIf you have any questions about the proposals or submission process write to proposal@r-consortium.org." }, { - "objectID": "blog/guidelines.html", - "href": "blog/guidelines.html", - "title": "Blog Guidelines", + "objectID": "all-projects/callforproposals.html#projects-the-isc-funds", + "href": "all-projects/callforproposals.html#projects-the-isc-funds", + "title": "The 2024 ISC Grant Program", "section": "", - "text": "The R Consortium blog will serve as a channel for the members, ISC grant recipients and the community at large to broadcast to a wide audience how their work and engagement is growing opportunities for the R language for data science and statistical computing.\nThis may include summaries of how leading institutions, companies and developers are using, developing and advancing R.\nThose involved with developing, maintaining, distributing, and using R software are encouraged to contribute to the blog.\nGuest posts from the R Consortium community at large or projects funded by the ISC that enhance R and support users are welcomed. Updates about R-related conferences (including useR!), meetings (including SatRDays and RLadies), local user groups worldwide, new working groups or programs for R language certification and training are of interest. Other topics would certainly be considered, but it should be something of interest to the broader R community.\nAccepted blog posts are at the sole discretion of the R Consortium." + "text": "The ISC is interested in projects that:\n\nAre likely to have a broad impact on the R community.\nHave a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it up into smaller chunks (a good example of this done is with the DBI/DBItest project submission, where multiple proposals came in over time to address the various needs).\nHave a low-to-medium risk with a low-to-medium reward. The ISC tends not fund high-risk, high-reward projects.\n\nWhile all projects are considered, the ISC generally does not accept projects that:\n\nImpact only a small part of the R community\nRequest conference, workshop, or meetup sponsorship. For these, you should look at our user group program or connect with the marketing committee for larger events.\nAre very exploratory. These are better to be pursued through the working group program." }, { - "objectID": "blog/guidelines.html#r-consortium-blog-overview", - "href": "blog/guidelines.html#r-consortium-blog-overview", - "title": "Blog Guidelines", + "objectID": "all-projects/callforproposals.html#submitting-a-proposal", + "href": "all-projects/callforproposals.html#submitting-a-proposal", + "title": "The 2024 ISC Grant Program", "section": "", - "text": "The R Consortium blog will serve as a channel for the members, ISC grant recipients and the community at large to broadcast to a wide audience how their work and engagement is growing opportunities for the R language for data science and statistical computing.\nThis may include summaries of how leading institutions, companies and developers are using, developing and advancing R.\nThose involved with developing, maintaining, distributing, and using R software are encouraged to contribute to the blog.\nGuest posts from the R Consortium community at large or projects funded by the ISC that enhance R and support users are welcomed. Updates about R-related conferences (including useR!), meetings (including SatRDays and RLadies), local user groups worldwide, new working groups or programs for R language certification and training are of interest. Other topics would certainly be considered, but it should be something of interest to the broader R community.\nAccepted blog posts are at the sole discretion of the R Consortium." + "text": "Please provide a 2 to 5 page proposal that describes the problem you want to solve. We expect submissions to include these components:\n\nThe Problem: What problem do you want to solve? Why is it a problem? Who does it affect? What will solving the problem enable? This section should include a brief summary of existing work, such as R packages that may be relevant. If you are proposing a change to R itself, you must include a letter of support from a member of R Core.\nThe Plan: How are you going to solve the problem? Include the concrete actions you will take and an estimated timeline. What are likely failure modes and how will you recover from them?\nThe Team: Who will work on the project? Briefly describe all participants, and the skills they will bring to the project.\nProject Milestones: Outline the milestones for development and how much funding will be required for each stage (as payments will be tied to project milestone completion). Each milestone should specify the work to be done and the expected outcomes, providing enough detail for the ISC to understand the scope of the project work and assess the likelihood of success.\nHow Can The ISC Help: Please describe how you think the ISC can help. If you are looking for a cash grant include a detailed itemized budget and spending plan. We expect that most of the budget will be allocated for labor costs. We do not cover indirect costs. The ISC grants cannot cover such things as travel, lodging, food, journal publication fees, or personal hardware. Cloud services may be covered if they are specific to the project and the project period. The ISC reserves the right to vet how funds are used for each project separately. If in doubt, please reach out to us. If you are seeking to start an ISC working group, then please describe the goals of the group and provide the name of the individual who will be committed to leading and managing the group’s activities. Also, describe how you think the ISC can help promote your project.\nDissemination: How will you ensure that your work is available to the widest number of people? Please specify the open-source or creative commons license(s) you will use, how you will host your code so that others can contribute, and how you will publicize your work. We encourage you to plan content to be shared quarterly on the R Consortium blog.\n\nThe ISC has a limited grant budget, and we want to ensure that funded projects deliver the maximum benefit to the community. Successful proposals show well-defined milestones, with initial work completed to minimize delivery risk, e.g., upfront research and well-defined action plans.\nIf you would like a template to help you structure your proposal, we encourage you to use one contributed by Steph Locke at https://github.com/RConsortium/isc-proposal.\nWe encourage you to seek feedback from the community before formally submitting your proposal. You are welcome to email individual committee members who might be particularly interested in your proposal to get their informal opinion, and you may want to publicize it more widely to get feedback from the broader R community." }, { - "objectID": "blog/guidelines.html#quality", - "href": "blog/guidelines.html#quality", - "title": "Blog Guidelines", - "section": "Quality", - "text": "Quality\nWe are looking for posts that teach and give value to our community. Blogs should include the meta-narrative that “R is a fast-growing language for statistical computing and graphics” and “the R Consoritum supports the worldwide community of users, maintainers and developers of R software.”\nGuest posts must be vendor neutral, though it may mention vendors involved in specific deployment or adoption paths, or their hosting of an in-person event or speaking at an event, or other indications of meaningful participation in the community. It shouldn’t feel like an advertisement for your product, services or company though. Your post must be your content, but can be published elsewhere on the Internet with permission from that website. All content should have a byline (preferably by a company engineer) and be published under Creative Commons with Attribution, so you’re welcome to re-publish on your own blog.\nThe most interesting posts are those that teach or show how to do something in a way maybe others haven’t thought of. Good blog posts show hurdles that were encountered and explain how they were overcome (not that everything is rainbows and unicorns). When showing upstreaming of a patch fixing an issue for others, link back to the Github issue, so readers can follow along. We don’t avoid critical commentary or broad issues, but approach them with sensitivity, professionalism and tact in a way that is beneficial and positive for the community. It would be helpful to the R Consortium to discuss how to choose between different technologies and how to accommodate different legacy issues and cloud platforms.\nBe interesting and inspiring!" + "objectID": "all-projects/callforproposals.html#how-to-apply", + "href": "all-projects/callforproposals.html#how-to-apply", + "title": "The 2024 ISC Grant Program", + "section": "", + "text": "Once you have completed your proposal, create a self-contained PDF and complete this form (requires signing in via a Google Account). When you submit the form, you should see a response page saying “Thank you for your proposal!” Soon thereafter, you will receive an email from forms-receipts-noreply@google.com with all the details of your submission. If you do not receive that email, please be sure to check your spam folder. If you do not see it, reach out to us as soon as possible.\nPlease note that the R Consortium utilizes a standard agreement for all funded projects selected in an effort to streamline the award process and to fund the greatest amount of projects as possible. The standard agreement is available for review in advance: Individual Consultant Agreement for R Consortium ISC Projects – 20170622.\nIf you have any questions please email proposal@r-consortium.org." }, { - "objectID": "blog/guidelines.html#promotion", - "href": "blog/guidelines.html#promotion", - "title": "Blog Guidelines", - "section": "Promotion", - "text": "Promotion\nYour blog will be shared on R Consortium’s Twitter channel. Please feel free to retweet or share. Don’t forget to share your work on your own social channels and favorite news aggregator sites. Suggested sites: Twitter, LinkedIn, Reddit, Hacker News, DZone, TechBeacon. Plus industry sites like: https://www.r-bloggers.com/about/, rweekly.org and reddit.com/r/rstats." + "objectID": "all-projects/callforproposals.html#proposal-dates-for-2024", + "href": "all-projects/callforproposals.html#proposal-dates-for-2024", + "title": "The 2024 ISC Grant Program", + "section": "", + "text": "March 1, 2024 – Grant Application period opens\nApril 1, 2024 – Grant Application period closes, 11:59pm US ET\nMay 1, 2024 – All accepted grantees are contacted by the ISC\nJune 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nSeptember 1, 2024 – Grant Application period opens\nOctober 1, 2024 – Grant Application period close, 11:59pm US ET\nNovember 1, 2024 – All accepted grantees are contacted by the ISC\nDecember 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter." }, { - "objectID": "blog/guidelines.html#how-to-submit-for-consideration", - "href": "blog/guidelines.html#how-to-submit-for-consideration", - "title": "Blog Guidelines", - "section": "How to submit for consideration", - "text": "How to submit for consideration\nPlease submit the blog post or a brief summary and the topic of the post to r-marketing@lists.r-consortium.org (with the Subject line: “Proposed Blog: BLOG TITLE”) for consideration. The PR team will review your submission in a timely manner and provide the green light to draft the entire article or provide feedback on next steps. If you are submitting an article or presentation that already exists, please send it in its entirety with a note on the expressed permission from the owner of content. Once your submission has been approved, it will be added to our blog publishing calendar and a publish date will be provided, so you may plan to promote accordingly through your personal and company social media channels. Blog posts should be no longer than 1,000 words and no shorter than 300 words. Diagrams, code examples or photos are strongly encouraged.\nThis document last updated July 17, 2024" + "objectID": "all-projects/callforproposals.html#the-process", + "href": "all-projects/callforproposals.html#the-process", + "title": "The 2024 ISC Grant Program", + "section": "", + "text": "All proposals will be read and reviewed by the Chair of the ISC and assigned to a committee member for detailed review. Proposals will be reviewed as a group, and you will be notified of the decision by the dates listed above.\n50% of the grant will be paid out when the contract is signed and 50% upon completion.\nAll accepted projects will be published on the R Consortium blog.\nWe review this process yearly to ensure that the process is as smooth as possible, and to incorporate the knowledge gained from putting it into practice. 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Whether you’re an experienced R user or just starting out, this session will offer valuable perspectives and opportunities for engagement!\nPresentation used in the webinar available here.\nAgenda\n\nThe Evolution of LatinR and its Impact on the Community: LatinR’s history, the growth of the community, and the role of the conference in fostering international and regional collaboration.\nLatinR Success Stories and Featured Projects: conference format, examples of experts who came, workshops, and collaborative projects that have emerged from LatinR.\nFuture of LatinR: what we will see in the 2024 edition, future perspectives for LatinR, and how the community can get more involved." + "objectID": "blog/how_to_post.html", + "href": "blog/how_to_post.html", + "title": "R Consortium Blog", + "section": "", + "text": "Topic\n\n\n\n\nCloning the Repo\n\n\nInitial Setup\n\n\nInstall R on Linux\n\n\nR Packages Installation Method #1\n\n\nR Packages Installation Method #2\n\n\nInstall the Vscode extension “Quarto”\n\n\nRunning the Project in a Live Preview\n\n\nAdding a Blog post\n\n\nUploading your Post\n\n\n\n\n\n\nOn our GitHub repository, click “Code“ and then “Open with GitHub Desktop”.\n\nIn GitHub Desktop click “Clone”\n\n\n\n\n\nIn Github Desktop click on “Fetch origin” to get the most up to date blog on your local computer.\n\nIn Github Desktop click on “Open in Visual Studio Code” to start working on your blog\n\nIn VSCode click on “View” and then “Terminal”\n\nIn the Vscode Terminal make sure you are on a Linux terminal by switching to Ubuntu (WSL)\n\n\n\n\nInstall R using sudo apt-get install r-base and sudo apt-get install r-base-dev\n\n\n\n\nInstall R packages on Linux; type R in terminal and then install.packages(‘rmarkdown’)\nGGPLOT2 installation: install.packages(“ggplot2”)\ndygraphs installation: install.packages(“dygraphs”)\nhere installation: install.packages(“here”)\n\n\n\n\nUse RStudio Desktop on Windows then click on “install”\n\nSearch for the package you want for example “here” package and click “install”\n\n\n\n\n\n\nRecommended (optional) in the Quarto Extension settings enable the “Render on Save” option\n\n\n\n\n\n\nIn VSCode click on “View” and then “Command Palette”\n\nSearch for “Quarto: Preview” and click on that command\n\n\n\n\n\nIn Github desktop click “Branch” and then “New branch” make a new branch for example “Adding-new-elephant-post”\n\n\nIn VSCode add a new Folder in the “posts” directory and name it. 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On the bottom left is an indication of a successful commit.\n\nMake a pull request in Github desktop and then 1 reviewer should check the post and make sure it is looking good!\n\n\nClick on “Create pull request” on Github\n\nApproval Process and Timing\n\nEmail info@r-consortium.org" }, { - "objectID": "webinars/unlocking-insights-from-latinr.html#speakers", - "href": "webinars/unlocking-insights-from-latinr.html#speakers", - "title": "Unlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar", - "section": "Speakers", - "text": "Speakers\n\nYanina Bellini\n\nYanina shares her experience teaching computational skills and building welcoming communities of practice for programming scientists. She is one of the co-founders and chairs of LatinR. She is also the rOpenSci Community Manager and part of the R-Ladies Leadership Team. She has 30 years of experience in education and 24 years as a researcher.\n\n\nNatalia Da Silva\n\nNatalia is an Assistant Professor of Statistics at Universidad de la República in Montevideo, Uruguay, with a Ph.D. in Statistics from Iowa State University, whose research focuses on supervised learning, exploratory data analysis, statistical graphics, and reproducible research, and who co-founded LatinR, R-Ladies Montevideo, and the Montevideo R User Group (GURU), while also serving as an Associate Editor for Reproducibility at the Journal of the American Statistical Association.\n\n\nRiva Quiroga\n\nRiva Quiroga is a Linguist based in Valparaíso, Chile. 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I will discuss how biomedical researchers can make use of containerization technology, particularly the tools provided by the Rocker Project, which publishes powerful standardized containers for the R language.\n\nRegister here: https://zoom.us/webinar/register/WN_aWMKlQngTUqgp4G_qkkD_g" + "objectID": "blog/how_to_post.html#initial-setup", + "href": "blog/how_to_post.html#initial-setup", + "title": "R Consortium Blog", + "section": "", + "text": "In Github Desktop click on “Fetch origin” to get the most up to date blog on your local computer.\n\nIn Github Desktop click on “Open in Visual Studio Code” to start working on your blog\n\nIn VSCode click on “View” and then “Terminal”\n\nIn the Vscode Terminal make sure you are on a Linux terminal by switching to Ubuntu (WSL)\n\n\n\n\nInstall R using sudo apt-get install r-base and sudo apt-get install r-base-dev\n\n\n\n\nInstall R packages on Linux; type R in terminal and then install.packages(‘rmarkdown’)\nGGPLOT2 installation: install.packages(“ggplot2”)\ndygraphs installation: install.packages(“dygraphs”)\nhere installation: install.packages(“here”)\n\n\n\n\nUse RStudio Desktop on Windows then click on “install”\n\nSearch for the package you want for example “here” package and click “install”\n\n\n\n\n\n\nRecommended (optional) in the Quarto Extension settings enable the “Render on Save” option" }, { - "objectID": "webinars/containerization-and-r-for-reproducibility.html#speaker", - "href": "webinars/containerization-and-r-for-reproducibility.html#speaker", - "title": "Containerization and R for Reproducibility and More", - "section": "Speaker", - "text": "Speaker\n\nNoam Ross is a computational disease ecologist and Executive Director of rOpenSci, a nonprofit dedicated to promoting open science and validating data science and computational methods. He is a core member of the Rocker Project, which maintains standardized containers for the R computer language. Noam’s work includes spearheading rOpenSci’s work in software peer review, developing a widely emulated system for leveraging the academic peer-review process coupled with state-of-the art automated code analysis to improve code quality in the scientific software in ecosystem, as well as using review as a mechanism for community building and training. His research interests and contributions span a wide range of topics, including disease ecology, zoonotic spillover, mechanistic modeling of disease dynamics, and non-parametric data science methods. His applied work includes creating early outbreak assessment models for the U.S. Defense Threat Reduction Agency, and modeling and forecasting for New York State’s COVID-19 emergency response. Noam holds a Ph.D. in theoretical ecology from the University of California-Davis and a B.Sc. from Brown University." + "objectID": "blog/how_to_post.html#running-the-project-in-a-live-preview", + "href": "blog/how_to_post.html#running-the-project-in-a-live-preview", + "title": "R Consortium Blog", + "section": "", + "text": "In VSCode click on “View” and then “Command Palette”\n\nSearch for “Quarto: Preview” and click on that command" }, { - "objectID": "webinars/escape-the-data-dungeon.html#summary", - "href": "webinars/escape-the-data-dungeon.html#summary", - "title": "Escape the Data Dungeon: Unlock Scalable R Analytics and ML", - "section": "Summary:", - "text": "Summary:\nTired of sluggish R data processing and limited Machine Learning (ML) options with large databases? Imagine swiftly predicting customer churn and deploying solutions with ease. Watch our in-depth Oracle Machine Learning for R (OML4R) webinar to learn more!\nKey topics included:\n\nSeamless In-Database Access: Jump straight into your data without the drag of extractions.\nScalable High-Performance Data Processing: Handle huge datasets effortlessly.\nIntegrated In-Database ML: Develop and deploy potent models right within your database.\nEffortless Production Deployment: Streamline your R scripts from development to production.\n\nFound out more about OML4R through practical examples in product bundling, demand forecasting, and customer churn prediction. Escape the data grind and transformed your R experience." + "objectID": "blog/how_to_post.html#adding-a-blog-post", + "href": "blog/how_to_post.html#adding-a-blog-post", + "title": "R Consortium Blog", + "section": "", + "text": "In Github desktop click “Branch” and then “New branch” make a new branch for example “Adding-new-elephant-post”\n\n\nIn VSCode add a new Folder in the “posts” directory and name it. 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He has been involved with R technology for the past 15 years.  Mark is Oracle’s representative to the R Consortium and is an Oracle Adviser of the Analytics and Data Oracle User Community. He has been issued seven US patents. Mark holds a bachelor’s degree from Rutgers University and a master’s degree from Brown University, both in computer science. Follow him on Twitter @MarkHornick and connect on LinkedIn.\n\n\n\nSherry LaMonica, Consulting MTS, Oracle Machine Learning\nSherry is a member of the Oracle Machine Learning Product Management team. She has 20 years of software experience focused on enabling the commercial use of the open-source data analysis software systems with R and Python for data science and machine learning projects. She has worked with customers in fields as diverse as pharmaceutical research, financial analysis, manufacturing, and healthcare IT." + "objectID": "webinars/webinars-auto-not-being-used.html", + "href": "webinars/webinars-auto-not-being-used.html", + "title": "R Consortium", + "section": "", + "text": "Containerization and R for Reproducibility and More\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEscape the Data Dungeon: Unlock Scalable R Analytics and ML\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFrom Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTidy Finance and Accessing Financial Data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nR/Insurance Series: For Everyone in Insurance or Actuarial Science\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nR/Medicine: Quarto for Reproducible Medical Manuscripts\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTidy Finance Webinar Series\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nUnlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWebinars\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNo matching items" }, { - "objectID": "webinars/escape-the-data-dungeon.html#the-r-adoption-series", - "href": "webinars/escape-the-data-dungeon.html#the-r-adoption-series", - "title": "Escape the Data Dungeon: Unlock Scalable R Analytics and ML", - "section": "The R Adoption Series", - "text": "The R Adoption Series\nThis is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." + "objectID": "webinars/webinars.html", + "href": "webinars/webinars.html", + "title": "Webinars", + "section": "", + "text": "This is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series.  If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org" }, { - "objectID": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#summary", - "href": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#summary", - "title": "From Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption", - "section": "Summary", - "text": "Summary\nThe webinar by the R consortium titled “From Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption” was not just a case study of Pfizer’s journey. It was a platform for sharing valuable insights and strategies applicable across industries and experience levels. Viewers can learn about the importance of an engaged R community and practical approaches to building and maintaining such a community within their organizations." + "objectID": "webinars/webinars.html#the-r-adoption-series", + "href": "webinars/webinars.html#the-r-adoption-series", + "title": "Webinars", + "section": "", + "text": "This is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series.  If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org" }, { - "objectID": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#speaker", - "href": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#speaker", - "title": "From Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption", - "section": "Speaker", - "text": "Speaker\n\n\nNatalia Andriychuk is a Statistical Data Scientist in the R Center of Excellence SWAT (Scientific Workflows and Analytic Tools) team at Pfizer. In her current role, Natalia provides robust technical solutions to business lines across Pfizer utilizing strong technical knowledge of R, R packages, Shiny, and other associated data science and data analytics tools. She develops training on R and associated tools for Pfizer colleagues and helps to build an R community at Pfizer. 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If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." + "objectID": "webinars/webinars.html#archived-webinars-full-recordings-available", + "href": "webinars/webinars.html#archived-webinars-full-recordings-available", + "title": "Webinars", + "section": "Archived Webinars – Full Recordings Available", + "text": "Archived Webinars – Full Recordings Available\n\nLearn more: Unlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar\n\nLearn more: R/Medicine: Quarto for Reproducible Medical Manuscripts\n\nLearn more: Tidy Finance and Accessing Financial Data\n\nLearn more: Escape the Data Dungeon: Unlock Scalable R Analytics and ML\n\nLearn more: From Vision to Action: The Pfizer R Center of Excellence-led journey to R Adoption\n\nLearn more: R/Insurance Series: For Everyone in Insurance or Actuarial Science\nThe R/Insurance Series is offered four webinars this January. The video recordings of the previous R/Insurance Series webinar, “From Excel to Programming in R,” “From programming in R to putting R into production,” and “R performance culture,” are now available at the link above.\n\nLearn more: R/Medicine Webinar: Visualizing Survival Data with the {ggsurvfit} R Package\n\nLearn more: R/Adoption Series: The Adoption of R in Japan’s Pharma Industry Confirmation\n\nLearn more: R/Adoption Series: R and shiny in regulatory submission\n\nLearn More: R/Adoption Series: Learnings and Reflection from R Validation Case Studies\n\nJuliane Manitz, Senior Expert Biostatistician at EMD Serono\nDoug Kelkhoff, Principal Data Scientist / Statistical Software Engineer at Roche\nUday Preetham Palukuru, Standards lead at Merck & Co.\nEric Milliman, Senior Principal Data Scientist at Biogen\n\n\n\n \n\nLearn More: Teal: An R-Shiny Framework to Unlock the Power of Interactive Data Exploration Chendi Liao, Principal Statistical Programmer Analyst, Roche Canada • Dony Unardi, Principal Data Scientist, Genentech\n\n\n\n \n\nLearn More: R Adoption Series: Introducing the Software Engineering Working Group and {mmrm} Ben Arancibia, Data Scientist – Senior Manager At GSK • Yoni Sidi, Director of Modeling and Simulation at Sage Therapeutics\n\n\n\n\n\n \n\nLearn More: R/Database: Using R at Scale on Database Data \nMark Hornick, Senior Director, Oracle Machine Learning • Sherry LaMonica, Consulting MTS, Oracle Machine Learning\n\n\n\n \n\nLearn More: Upskilling on Data Handling and Communication at Swiss Re \nClaudio T. Rebelo, Model Validation Actuary for Group Risk Management at Swiss Re • Georgios Bakoloukas, Head Model Development & Analytics, Risk Management at Swiss Re • Daniela E. Damm, Divisional Operational Officer for Group Risk Management at Swiss Re\n\n\n\n \n\nLearn More: Using Metadata for Speedy Delivery Re \nChristina Fillmore, Data Scientists and R developer at GSK • Yujie Zhao, is a Senior Scientist (Biostatistics) at Merck & Co., Inc • Keaven Anderson, Scientific Assistant VP of Methodology Research in the Biostatistics and Clinical Research Decision Sciences group at Merck\n\n\n\n \n\nLearn More: Using R in Regulatory Review \nHye Soo Cho, Statistical Analyst, FDA/CDER • Tae Hyun (Ryan) Jung, Ph.D., Senior Statistical Reviewer in FDA/CDER/OTS/OB/DBVI • Paul Schuette, Scientific Computing Coordinator, FDA • Ning Leng, Director, Product Development Data Sciences, Roche • Coline Zeballos, R Strategy Lead, Roche\n\n\n\n \n\nLearn More: Speaking Different Languages \nMichael Rimler, Head of Technical Excellence and Innovation at GlaxoSmithKline • Mike Stackhouse, Chief Innovation Officer at Atorus\n\n\n\n \n\nLearn More: Table Creation in R \nGabriel Becker, Statistical Computing Consultant\n\n\n\n \n\nLearn More: R Management at Roche \nKieran Martin, R Enablement Lead: PD Data Sciences at Roche • Tadeusz Lewandowski, Pan-Pharma collaboration product lead at Roche • Adrian Waddell, Chief Engineer NEST Project\n\n\n\n \n\nLearn More: R Training Strategies at Janssen \nPaulo R. Bargo, Ph.D., Head of R&D Data and Advanced Analytics, Ethicon • Dan Hofstaedter, is a statistical programmer within the Janssen Clinical & Statistical Programming group • Gayathri Kolandaivelu, has over 13 years of experience in the pharmaceutical industry\n\n\n\n \n\nLearn More: Scaling R at GSK \nAndy Nicholls, Head of Data Science within GSK Biostatistics" }, { - "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html", - "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html", - "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", - "section": "", - "text": "Slides available here:\nQuarto Manuscript\nGithub – Quarto Manuscript\nManuscript:\nmine-cetinkaya-rundel.github.io/indo-rct\ngithub.com/mine-cetinkaya-rundel/indo-rct" + "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#slide-deck-available", + "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#slide-deck-available", + "title": "Tidy Finance and Accessing Financial Data", + "section": "Slide deck available:", + "text": "Slide deck available:\nTidy Finance and Accessing Financial Data (PDF)" }, { - "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#summary", - "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#summary", - "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", - "section": "Summary ", - "text": "Summary \nIn this talk, Mine Cetinkaya-Rundel, Professor of the Practice of Statistical Science at Duke University,  presents a new capability in Quarto that provides a straightforward and user-friendly approach to creating reproducible manuscripts that are publication-ready for submission to science journals. \nThis new feature, Quarto manuscripts, includes the ability to produce a bundled output containing a standardized journal format, source documents, source computations, referenced resources, and execution information into a single bundle that be ingested into journal review and production processes. \nIn this talk, we’ll demo how Quarto manuscripts work and how you can incorporate them into your current manuscript development process as well as touch on pain points in your current workflow that Quarto manuscripts help alleviate." - }, - { - "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#speaker", - "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#speaker", - "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", - "section": "Speaker", - "text": "Speaker\n\n\n\n\n\nMine Çetinkaya-Rundelis, is Professor of the Practice of Statistical Science and the Director of Undergraduate Studies in the Department of Statistical Science, as well as an affiliated faculty member in the Computational Media, Arts, and Cultures program at Duke University. Her work is dedicated to advancing innovation in statistics and data science pedagogy, focusing particularly on computing, reproducible research, student-centered learning, and open-source education. She emphasizes integrating computation into the undergraduate statistics curriculum, employing reproducible research methodologies, and analyzing real and complex datasets. In Spring 2024, she will be teaching STA 199 – Introduction to Data Science and Statistical Thinking, along with STA 313 – Advanced Data Visualization. Further details about her work can be explored below, or she can be found on Mastodon and Bluesky." + "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#summary", + "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#summary", + "title": "Tidy Finance and Accessing Financial Data", + "section": "Summary", + "text": "Summary\nThis webinar focuses on Tidy Finance and accessing financial data. Tidy Finance is an opinionated approach to empirical research in financial economics. It provided a fully transparent, open source code base in R and Python. The website provides the tools for students to learn about empirical applications based on a fully transparent code base and for instructors the materials for teaching the importance of reproducible research using tidy principles.\nChristoph Scheuch introduces Tidy Finance and illustrates the underlying principles. The webinar then focuses on accessing and managing financial data using R. It shows how to import different open source and proprietary data sets and organize them in a database." }, { - "objectID": "about/join.html", - "href": "about/join.html", - "title": "Why Join the R Consortium?", - "section": "", - "text": "The R Consortium is the mechanism for corporate entities and other organizations to support  and engage with the R Community. Membership in the R Consortium signals community leadership, a long term viewpoint, and an appreciation for the efforts of R’s open source contributors. Membership shows commitment and a desire to contribute to the community, strengthening it for the benefit of all.\n\n\n\nHelps fund key R infrastructure such as the R-Hub build system, database interfaces, distributed computing architecture, regional conferences, local R user groups and more.\nProvides a way for companies to generate industry-wide support for projects that they see as valuable.\n\nThe bulk of the R Consortium budget goes directly to funding key community projects.\n\nThrough participation in the R Consortium Infrastructure Steering Committee (ISC), members have a voice in the process of selecting projects and the opportunity to guide their development.\nGives companies direct access to the R Foundation:\n\nBoard members interact with the R Foundation’s representative on the R Consortium Board of Directors.\nISC members:\n\nWork side-by-side with R Foundation members engaged in technical projects,\nParticipate in regular meetings with R Foundation members.\n\n\nProvides insight and access to accurate and up-to-date knowledge about important developments in the the R Community and the extended R ecosystem.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBenefits by member class\nPlatinum\nSilver\n\n\n\n\nOne seat on the Board of Directors with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nOne seat on the ISC with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nElect Silver representatives to the Board and ISC (1 Board seat per 3 Silver members, 1 ISC seat for all Silver members)\n\n\n\nXmark\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nCompany logo on R Consortium website and collateral\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nR Consortium logo on company website\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nMembership dues (annually)\nUS$100,000\n100+ FTE US $25,000 <100 FTE / non-profits, universities US $10,000\n\n\n\n\n\n\n\n\n\n\nReview the Membership Documents.\n\n\nR Consortium Membership Datasheet (PDF)\nR Consortium Bylaws (PDF)\nR Consortium Membership Agreement (PDF)\nR Consortium – Certificate of Incorporation (PDF)\n\n\nFill out our online membership application form.\nRemit the annual dues payment that is applicable for your membership level.\nBegin participating in Events, Discussions, Projects and working Groups.\n\nIf you have questions about membership or joining the R Consortium, please contact our member support desk and you will be contacted as soon as possible. Thank you." + "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#agenda", + "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#agenda", + "title": "Tidy Finance and Accessing Financial Data", + "section": "Agenda:", + "text": "Agenda:\n\nIntroduction to Tidy Finance\nAccessing and Managing Financial Data\nWRDS & Other Data Providers\nQ&A Session" }, { - "objectID": "about/join.html#membership-in-the-r-consortium", - "href": "about/join.html#membership-in-the-r-consortium", - "title": "Why Join the R Consortium?", - "section": "", - "text": "Helps fund key R infrastructure such as the R-Hub build system, database interfaces, distributed computing architecture, regional conferences, local R user groups and more.\nProvides a way for companies to generate industry-wide support for projects that they see as valuable.\n\nThe bulk of the R Consortium budget goes directly to funding key community projects.\n\nThrough participation in the R Consortium Infrastructure Steering Committee (ISC), members have a voice in the process of selecting projects and the opportunity to guide their development.\nGives companies direct access to the R Foundation:\n\nBoard members interact with the R Foundation’s representative on the R Consortium Board of Directors.\nISC members:\n\nWork side-by-side with R Foundation members engaged in technical projects,\nParticipate in regular meetings with R Foundation members.\n\n\nProvides insight and access to accurate and up-to-date knowledge about important developments in the the R Community and the extended R ecosystem." + "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#speaker", + "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#speaker", + "title": "Tidy Finance and Accessing Financial Data", + "section": "Speaker", + "text": "Speaker\n\n\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG. He is responsible for researching, designing, and prototyping of cutting-edge AI-driven products using R and Python. Before his focus on AI, he was responsible for product management and business intelligence at wikifolio Financial Technologies AG and an external lecturer at the Vienna University of Economics and Business, where he taught finance students how to manage empirical projects" }, { - "objectID": "about/join.html#how-r-consortium-membership-helps-support-the-r-community", - "href": "about/join.html#how-r-consortium-membership-helps-support-the-r-community", - "title": "Why Join the R Consortium?", - "section": "", - "text": "Benefits by member class\nPlatinum\nSilver\n\n\n\n\nOne seat on the Board of Directors with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nOne seat on the ISC with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nElect Silver representatives to the Board and ISC (1 Board seat per 3 Silver members, 1 ISC seat for all Silver members)\n\n\n\nXmark\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nCompany logo on R Consortium website and collateral\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nR Consortium logo on company website\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nMembership dues (annually)\nUS$100,000\n100+ FTE US $25,000 <100 FTE / non-profits, universities US $10,000\n\n\n\n\n\n\n\n\n\n\nReview the Membership Documents.\n\n\nR Consortium Membership Datasheet (PDF)\nR Consortium Bylaws (PDF)\nR Consortium Membership Agreement (PDF)\nR Consortium – Certificate of Incorporation (PDF)\n\n\nFill out our online membership application form.\nRemit the annual dues payment that is applicable for your membership level.\nBegin participating in Events, Discussions, Projects and working Groups.\n\nIf you have questions about membership or joining the R Consortium, please contact our member support desk and you will be contacted as soon as possible. Thank you." + "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#the-r-adoption-series", + "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#the-r-adoption-series", + "title": "Tidy Finance and Accessing Financial Data", + "section": "The R Adoption Series", + "text": "The R Adoption Series\nThis is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." }, { - "objectID": "about/contact.html", - "href": "about/contact.html", - "title": "Contact Us", - "section": "", - "text": "Contact Us\nFor general inquiries, membership inquiries, or requests for access to collaborative infrastructure, please feel free to visit our service desk.\nYou can also send us email directly at info@r-consortium.org\nIf you would like information on becoming a member of the R Consortium, please visit the Join page." + "objectID": "webinars/r-insurance-series.html#summary", + "href": "webinars/r-insurance-series.html#summary", + "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", + "section": "Summary", + "text": "Summary\nThese four webinars focused on insurance and actuarial science. The webinars were led by two experts in the field, Georgios Bakoloukas, Head Model Development and Analytics at Swiss Re, and Benedikt Schamberger, Head Atelier Technology & AI Consulting at Swiss Re.\nThese sessions offered a hands-on exploration of the transition from Excel to basic R, highlighting the benefits of working with R and one possible way to straddle across Excel and R. The subsequent webinars then moved to production-level R, and ultimately to high-performance R applications.\nThe webinars were tailored to be accessible to all, requiring no previous experience with the R programming language or specialized knowledge in insurance or actuarial science. Anyone with basic spreadsheet experience or who is considering applying for a bank loan has the necessary background to benefit from these webinars.\n\nFrom Excel to Programming in R\nSpeaker: Georgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\n\n\nQuick summary:\nThis video provided an in-depth exploration into the enduring relevance of Excel in the workplace while also emphasizing the benefits of learning to code for increased flexibility and resilience. It highlighted the common working patterns shared between Excel and R, demonstrating how transitioning from traditional spreadsheet computing to best-practice programming can be highly beneficial.\nThe webinar featured a straightforward, specific example from the insurance industry to illustrate the advantages of using the R programming language. It also presented a practical approach for integrating the thought processes and methodologies of both Excel and R, showcasing how professionals can effectively straddle these two powerful tools in their work.\n\n\n\n\nFrom programming in R to putting R into production\nSpeaker: Georgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\n\n\nQuick summary:\nWe could solve problems using coding, but how could we help others solve the same problem in the future? Sharing data and solutions was critical for real-world insurance professionals and actuarial scientists.\nContinuing the example from the first webinar, Georgios illustrated ways to document and test the solution and made it available to others using R’s frameworks for packaging, Web API creation, and graphical user interface generation (Shiny).\n\n\n\n\nR performance culture\nSpeaker: Benedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\n\n\nQuick summary:\nPremature optimization was the root of all evil. But there were occasions when we needed to improve the performance of critical code. Benedikt covered how performance fit into R’s design, what tools were available to tune it, and examples of what other aspects should be considered beyond pure runtime.\n\n\n\n\nHigh performance programming in R\nSpeaker: Benedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\n\n\nQuick summary:\nIn this webinar, Benedikt discussed how comma-separated values (CSV) files were commonly used when working with data files, as they were easy to read for humans and supported by tools like Excel or R. However, these files had a downside in terms of performance and file size. To address this, the industry developed binary formats that were more efficient. Benedikt focused on the Arrow R package and the Parquet file format and how they could help save time and disk space." }, { - "objectID": "about/faq.html", - "href": "about/faq.html", - "title": "FAQ", - "section": "", - "text": "FAQ\n\nIs the R Consortium committed to R as an open-source project?\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nWas the R community consulted about the projects considered by the R Consortium?\nWhat kinds of projects will the R Consortium undertake?\nHow are R Consortium projects selected and managed?\nAre the leaders of the R Consortium R users?\nCan I review the governance documents for the R Consortium?\nHow is the R Consortium governed?\nAre membership dues tax-deductible?\nCan an individual become a member of the R Consortium?\nWhy the focus on organizations rather than individuals?\nWhat is the relationship between the R Consortium and the Linux Foundation?\nWhat is the relationship between the R Consortium and the R Foundation?\nWho are the members of the R Consortium?\nWhy an R Consortium?\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nCan I review the governance documents for the R Consortium?\nWhat wouldn’t the R Consortium do?\nWhat kinds of projects will the R Consortium undertake?\nWho will be involved?\n\n\n\nIs the R Consortium committed to R as an open-source project?\nDefinitely! The R Consortium’s explicit mission is to “advance the worldwide promotion of and support for the R open source language”, and all of its activities are in support of the Open Source R Project. It will support and promote the use of Open Source R in all contents, including in commercial and business settings.\nAs defined in its charter (PDF), the projects of the Infrastructure Steering Committee will focus on support of the user base, support of developers, and general advancement of Open Source R. In particular, a commercial fork of R isn’t compatible with that mission, and won’t be a project of the R Consortium.\n\nBack to Top\n\n\n\n\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nNo. The R Consortium welcomes contributions of time, effort and ideas for all passionate users and developers of the R language.\n\nBack to Top\n\n\n\n\nWas the R community consulted about the projects considered by the R Consortium?\nYes. R Consortium projects are proposed by the community to the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nWhat kinds of projects will the R Consortium undertake?\nThe R Consortium will coordinate and support projects that directly benefit stakeholders within the R user community. Here are some examples of the types of projects the R Consortium might undertake\n\nImproving documentation and tools.\nSponsoring and helping execute conferences and events.\nHelping to scale and build out R infrastructure.\nMaintaining an enhanced website focused on the R user community.\n\nThis is not an exhaustive list. Anyone may propose a project to the Infrastructure Steering Committee, which selects and executes projects.\n\nBack to Top\n\n\n\n\nHow are R Consortium projects selected and managed?\nThe technical projects undertaken by the R Consortium in support of the R Project and the R Community are overseen by the Infrastructure Steering Committee. The charter of the Infrastructure Steering Committee (ISC) describes its mission, which is to advance the worldwide promotion of and support for R, and to develop projects, technical and infrastructure collaboration initiatives, support specific initiatives related to R. The membership of the ISC is drawn from the Platinum Members, Silver Members and the R Foundation. As the ISC appoints top-level projects, it is expected that those project leads will join the ISC as voting members.\n\nBack to Top\n\n\n\n\nAre the leaders of the R Consortium R users?\nThe Board Members (including the Chairperson) are appointed or elected by members (depending on the membership class). There is always one board member representing the R Foundation, to provide guidance to the R Consortium in its mission to support the R Project. The remaining Board members are drawn from the membership, and represent the organizations that have joined the R Consortium. All of the current board members have extensive R experience.\nThe members of the Infrastructure Steering Committee are appointed by the Platinum Members, Silver Members, and the R Foundation member, and includes representatives with significant technical experience, including R package developers, community leaders, and the individuals from the R Core Group.\n\nBack to Top\n\n\n\n\nCan I review the governance documents for the R Consortium?\nYes! You can review the by-laws for the R Consortium, Inc. (PDF)and the charter for the Infrastructure Steering Committee (PDF).\n\nBack to Top\n\n\n\n\nHow is the R Consortium governed?\nThe R Consortium is governed by the R Consortium Board of Directors, which is made up of representatives determined by its members. (Members of the board are elected or appointed depending on membership levels; for details please see the by-laws.) The Board meets regularly to manage the business of the Consortium. Meetings are led by the Chairperson of the R Consortium, a rotating position held by a board member elected by the Board as a whole.\nThe technical projects undertaken by the R Consortium in support of the R Project and the R Community are overseen by the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nAre membership dues tax-deductible?\nThe R Consortium is a US-based 501(c)6 non-profit organization. Dues are not tax-deductible as charitable donations by individuals, but under US IRS rules (PDF) may be deductible as trade or business expenses.\n\nBack to Top\n\n\n\n\nCan an individual become a member of the R Consortium?\nYes, individuals may support the R Consortium by joining as a non-voting associate member. You can also support the R project by contributing to the R Foundation directly.\n\nBack to Top\n\n\n\n\nWhy the focus on organizations rather than individuals?\nHundreds of companies around the world have invested heavily in R, by building systems on the R platform and by hiring thousands of R developers. The R Consortium provides a means for those companies to invest in the R Project directly, to collaborate on projects of mutual interest to support the R Community as a whole, and to support the ongoing success of the R Project.\n\nBack to Top\n\n\n\n\nWhat is the relationship between the R Consortium and the Linux Foundation?\nThe R Consortium is an independent organization, but as Collaborative Project of the Linux Foundation, the Linux Foundation provides operational support and guidance.\n\nBack to Top\n\n\n\n\nWhat is the relationship between the R Consortium and the R Foundation?\nThe R Foundation is the leader of the R Project and the custodian of the R source code and copyright. The R Foundation determines the definition and evolution of the R language.\nThe R Consortium, as an independent entity, exists to support the R Community and the R Project as a whole — and that includes providing support to the R Foundation. That’s why the R Foundation has a guaranteed seat on the Board and the Infrastructure Steering Committee, to represent the interests of the R Foundation and to propose projects to support R itself.\n\nBack to Top\n\n\n\n\nWho are the members of the R Consortium?\nMembers of the R Consortium include the following types of organizations (PDF): any association, partnership, organization, governmental agency, company, corporation, academic entity, or non-profit entity with an interest in supporting R. (Individuals may also join as associate members.) In addition, the R Foundation is automatically a member and always has a seat on the Board and the Infrastructure Steering Committee. You can see a current list of members here.\n\nBack to Top\n\n\n\n\nWhy an R Consortium?\nThe R user community has experienced tremendous growth. With growth there is a greater need for cooperation and communication among R users and R stakeholders. R will continually benefit from improvements to its technical tools and resources. The mission of the R Consortium is to help with support and coordination of the important activities of the R Community, via projects selected and executed its Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nNo! The R Consortium welcomes contributions of time, effort and ideas for all passionate users and developers of the R language. After formal meetings of the Infrastructure Steering Committee have begun (which we anticipate will occur soon), we will distribute information on how project ideas can be submitted to the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nCan I review the governance documents for the R Consortium?\nYes! You can find copies of the by-laws (PDF) for the R Consortium, Inc. and the charter for the infrastructure steering committee.\n\nBack to Top\n\n\n\n\nWhat wouldn’t the R Consortium do?\nInterfere with the R language itself and its development.\n\nBack to Top\n\n\n\n\nWhat kinds of projects will the R Consortium undertake?\nThe R Consortium will coordinate and support projects that directly benefit stakeholders within the R user community, for example:\n\nImproving documentation and tools.\nSponsoring and helping execute conferences and events.\nHelping to scale and build out R infrastructure.\nMaintaining an enhanced website focused on the R user community.\nBack to Top\n\n\n\n\nWho is involved?\nR users and stakeholders as members of the consortium in addition to representatives from the R Foundation with operational support provided by The Linux Foundation.\n\nBack to Top" + "objectID": "webinars/r-insurance-series.html#speakers", + "href": "webinars/r-insurance-series.html#speakers", + "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", + "section": "Speakers", + "text": "Speakers\n\n\nGeorgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\nGeorgios’ team enables actuarial teams across the group to adopt best-practice programming and data science skills in daily work. Georgios is a Fellow of the Institute of Actuaries (IFoA) and Chair of IFoAs’ Programming for Actuarial Work Working Party.\n\n\n\nBenedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\nBenedikt recently joined the Model Development & Analytics team as a Senior Data Science Actuary. Previously, he worked for several years in Swiss Re’s Quantitative Financial Risk Management, validating financial models and risk aggregation methodologies. He supports the Atelier and R programming communities with questions surrounding infrastructure and other everyday challenges. He has an academic background in financial and actuarial mathematics." }, { - "objectID": "newsletters/newsletters.html", - "href": "newsletters/newsletters.html", - "title": "Newsletters", - "section": "", - "text": "Check out our previous Newsletters and stay tuned for future ones!" + "objectID": "webinars/r-insurance-series.html#the-r-adoption-series", + "href": "webinars/r-insurance-series.html#the-r-adoption-series", + "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", + "section": "The R Adoption Series", + "text": "The R Adoption Series\nThis is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." }, { - "objectID": "newsletters/newsletters.html#whats-happening-in-the-r-consortium", - "href": "newsletters/newsletters.html#whats-happening-in-the-r-consortium", - "title": "Newsletters", + "objectID": "webinars/tidy-finance-webinar-series.html", + "href": "webinars/tidy-finance-webinar-series.html", + "title": "Tidy Finance Webinar Series", "section": "", - "text": "Check out our previous Newsletters and stay tuned for future ones!" + "text": "Christoph Scheuch is an independent data science and business intelligence expert. He co-created and maintains the Tidy Finance project, a transparent, open source approach to research in financial economics. Alongside contributing to Tidy Finance, its maintainers have published in leading academic journals, including the Journal of Finance, Journal of Financial Economics, Review of Finance, and Journal of Econometrics. Christoph previously held the roles of Head of Artificial Intelligence, Director of Product, and Head of BI & Data Science at the social trading platform wikifolio.com. He was an external lecturer at the Vienna University of Economics and Business (WU), where he also obtained his PhD in finance as part of the Vienna Graduate School of Finance (VGSF)." }, { - "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html", - "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html", - "title": "R Consortium Q2 2024 Newsletter", - "section": "", - "text": "Hello from the R Consortium! This quarterly newsletter puts together the latest updates about our organization’s activities, the progress each working group has made, upcoming R-related events, and recordings of past events. In short, all you need to know about our work to promote the R language and how we lead community initiatives. Please share this newsletter!\nAre you a member of the R community and want to submit your content for the newsletter? Email us at info@r-consortium.org, we’d love to include you!\nYou haven’t read the previous newsletters? You can find them on the R Consortium website here.\nAny suggestions for our next newsletter? Feel free to let us know here.\nYou’d like to sign up to automatically receive the newsletter? Click here.\n\n\n\nTechnical Projects and Working Groups\nAnnual Report\nUpcoming Events\nFree R-related Technology and Industry Webinars\nR Consortium Supports R User Groups Around the World!\nBuilding Extended R Packages to Improve R Infrastructure\n\n\n\n\n\n\nThe Infrastructure Steering Committee (ISC) conducts two open grant cycles to evaluate proposals from the community for projects that the committee believes will contribute to the technical infrastructure of the R ecosystem. During the second grant cycle of 2023, the ISC funded the following seven projects with a total of $80,000:\n\nTranslating R to Nepali\nTooling for internationalization of R help pages\nRStats Mastodon Server\nTaking r-universe to the next level\nCausal Inference in a Box\nR Kafka Client\nAccessibility Enhancements for the R Journal\n\nThe first grant cycle for 2024 has recently closed, and the ISC is evaluating ten proposals which are collectively requesting more than $200,000. These proposals include translating a Public Health Model into R, adapting R-universe technology for deploying R packages, and upgrading or extending several key R packages. The ISC expects to notify the teams submitting successful proposals by May 1, 2024.\n\n\n\nIn this section, we will highlight the progress of selected R Consortium working groups. This month we look at the R Submissions working group and the Risk Assessment workstream of the R Validation hub, which have recently achieved significant milestones.\n\n\nWith the active participation of the FDA, the R Consortium R Submissions working group is developing a series of Pilot or test submissions to uncover the challenges that must be overcome in making “all R” regulatory submissions straightforward, routine, and reproducible over a minimum six-year time horizon. Each Pilot submission builds on the previous pilot and includes additional steps. The objective of Pilot 3 is to extend the work done in the Pilot 2 study, which included wrapping a Shiny application into the submissions package, to build the AdaM data set from raw data. For each submission effort, the FDA review team recreates the study from the submission package, evaluates the correctness and reproducibility of the results, and documents discrepancies from previous pilot submission packages that they may observe.\nIn the most recent Pilot 3 submission, the FDA observed a discrepancy that was due to a difference in the coding of an imputation algorithm. The Pilot 3 statisticians used a subsetting algorithm that differed from the algorithm selected by the CDISC statisticians who built the ADaM data set used in Pilot 1 and Pilot 2. This was not a statistical error, but a failure to provide documentation at a sufficient level of detail for the FDA reviewers to make the appropriate adjustment. The episode illustrates the attention to detail required to achieve a smooth handoff to the FDA.\nAs the Pilot 3 team prepares their final submission, the Pilot 4 team is nearly ready with a submission package that will include the code required to unpack the package and have it deploy within a WebAssembly browser instance.\nFor more information on the R submission working group please visit their website." + "objectID": "webinars/tidy-finance-webinar-series.html#optimize-portfolios-using-the-markowitz-model", + "href": "webinars/tidy-finance-webinar-series.html#optimize-portfolios-using-the-markowitz-model", + "title": "Tidy Finance Webinar Series", + "section": "Optimize Portfolios using the Markowitz Model", + "text": "Optimize Portfolios using the Markowitz Model\nSeptember 4th, 2024 at 12:00 pm ET\nThis webinar introduces Modern Portfolio Theory and the importance of mean-variance analysis in finance. It covers the mathematics of portfolio optimization, expected returns, variances, and covariances. Participants will learn to construct efficient frontiers and implement the Markowitz model in R, from loading return data to optimizing portfolios and interpreting risk-return trade-offs.\nAgenda:\n\nIntroduction to modern portfolio theory\nUnderstanding the mathematics of portfolio optimization\nImplementing the Markowitz model in R" }, { - "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#table-of-contents", - "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#table-of-contents", - "title": "R Consortium Q2 2024 Newsletter", - "section": "", - "text": "Technical Projects and Working Groups\nAnnual Report\nUpcoming Events\nFree R-related Technology and Industry Webinars\nR Consortium Supports R User Groups Around the World!\nBuilding Extended R Packages to Improve R Infrastructure" + "objectID": "webinars/tidy-finance-webinar-series.html#evaluate-performance-using-the-capital-asset-pricing-model", + "href": "webinars/tidy-finance-webinar-series.html#evaluate-performance-using-the-capital-asset-pricing-model", + "title": "Tidy Finance Webinar Series", + "section": "Evaluate Performance using the Capital Asset Pricing Model", + "text": "Evaluate Performance using the Capital Asset Pricing Model\nOctober 9th, 2024 at 12:00 pm ET\nThis webinar covers the Capital Asset Pricing Model (CAPM), starting with its intuitive derivation and its importance in finance. Participants will gain an understanding of Alpha and Beta and their roles in performance assessment. The webinar also includes an overview of popular CAPM extensions. Participants will learn to calculate Alpha and Beta in R with a step-by-step guide, from loading return data to estimating CAPM and interpreting the estimation results.\nAgenda:\n\nIntroduction to the CAPM\nUnderstanding Alpha and Beta\nCalculating Alpha and Beta in R" }, { - "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#technical-projects-and-working-groups", - "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#technical-projects-and-working-groups", - "title": "R Consortium Q2 2024 Newsletter", - "section": "", - "text": "The Infrastructure Steering Committee (ISC) conducts two open grant cycles to evaluate proposals from the community for projects that the committee believes will contribute to the technical infrastructure of the R ecosystem. During the second grant cycle of 2023, the ISC funded the following seven projects with a total of $80,000:\n\nTranslating R to Nepali\nTooling for internationalization of R help pages\nRStats Mastodon Server\nTaking r-universe to the next level\nCausal Inference in a Box\nR Kafka Client\nAccessibility Enhancements for the R Journal\n\nThe first grant cycle for 2024 has recently closed, and the ISC is evaluating ten proposals which are collectively requesting more than $200,000. These proposals include translating a Public Health Model into R, adapting R-universe technology for deploying R packages, and upgrading or extending several key R packages. The ISC expects to notify the teams submitting successful proposals by May 1, 2024.\n\n\n\nIn this section, we will highlight the progress of selected R Consortium working groups. This month we look at the R Submissions working group and the Risk Assessment workstream of the R Validation hub, which have recently achieved significant milestones.\n\n\nWith the active participation of the FDA, the R Consortium R Submissions working group is developing a series of Pilot or test submissions to uncover the challenges that must be overcome in making “all R” regulatory submissions straightforward, routine, and reproducible over a minimum six-year time horizon. Each Pilot submission builds on the previous pilot and includes additional steps. The objective of Pilot 3 is to extend the work done in the Pilot 2 study, which included wrapping a Shiny application into the submissions package, to build the AdaM data set from raw data. For each submission effort, the FDA review team recreates the study from the submission package, evaluates the correctness and reproducibility of the results, and documents discrepancies from previous pilot submission packages that they may observe.\nIn the most recent Pilot 3 submission, the FDA observed a discrepancy that was due to a difference in the coding of an imputation algorithm. The Pilot 3 statisticians used a subsetting algorithm that differed from the algorithm selected by the CDISC statisticians who built the ADaM data set used in Pilot 1 and Pilot 2. This was not a statistical error, but a failure to provide documentation at a sufficient level of detail for the FDA reviewers to make the appropriate adjustment. The episode illustrates the attention to detail required to achieve a smooth handoff to the FDA.\nAs the Pilot 3 team prepares their final submission, the Pilot 4 team is nearly ready with a submission package that will include the code required to unpack the package and have it deploy within a WebAssembly browser instance.\nFor more information on the R submission working group please visit their website." + "objectID": "webinars/tidy-finance-webinar-series.html#analyze-companies-using-financial-ratios", + "href": "webinars/tidy-finance-webinar-series.html#analyze-companies-using-financial-ratios", + "title": "Tidy Finance Webinar Series", + "section": "Analyze Companies using Financial Ratios", + "text": "Analyze Companies using Financial Ratios\nNovember 6th, 2024 at 12:00 pm ET\n\nRegister here: https://zoom.us/webinar/register/WN_BjhdZbAjSVuZHZEGhTZb7g\nThis webinar provides an overview of financial ratios and their importance in financial analysis. It covers categories such as liquidity, profitability, leverage, and efficiency. Participants will learn about financial statements, including the balance sheet, income statement, statement of cash flows, and statement of shareholders’ equity, with real-world examples. The webinar includes a step-by-step guide on calculating and interpreting financial ratios in R, from loading financial statement data to computing and interpreting key ratios.\nAgenda:\n\nIntroduction to financial ratios\nUnderstanding financial statements\nCalculating and interpreting financial ratios in R" }, { - "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#get-in-touch-with-the-r-consortium", - "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#get-in-touch-with-the-r-consortium", - "title": "R Consortium Q2 2024 Newsletter", - "section": "Get in Touch with the R Consortium!", - "text": "Get in Touch with the R Consortium!\nFollow us on social media or contact us here:https://www.r-consortium.org/contact" + "objectID": "webinars/tidy-finance-webinar-series.html#value-companies-using-discounted-cash-flow-analysis", + "href": "webinars/tidy-finance-webinar-series.html#value-companies-using-discounted-cash-flow-analysis", + "title": "Tidy Finance Webinar Series", + "section": "Value Companies using Discounted Cash Flow Analysis", + "text": "Value Companies using Discounted Cash Flow Analysis\nDecember 4th, 2024 at 12:00 pm ET\n\nRegister here: https://zoom.us/webinar/register/WN_IgpNWpN0TRKgAkwvVWylww\nSummary: This webinar provides an overview of company valuation methods with a focus on discounted cash flow (DFC) analysis. Participants will gain an understanding of DCF analysis and its components: forecasted cash flows, terminal value, and discount rate. The webinar includes steps to perform a DCF analysis and a guide to implementing DCF in R, from loading financial statement data to executing the analysis. The webinar concludes with interpreting the valuation results, offering practical insights into company valuation techniques.\nAgenda:\n\nIntroduction to company valuation\nUnderstanding DCF\nImplementing DCF in R" }, { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html", - "title": "R Consortium Q3 2024 Newsletter", + "objectID": "about/governance.html", + "href": "about/governance.html", + "title": "Governance", "section": "", - "text": "Welcome to the R Consortium’s Q3 2024 Newsletter!\nThis quarter has been packed with exciting updates, innovative projects, and global community initiatives that are shaping the future of R.\nBig news! The R Submissions Working Group successfully completed the “Pilot 3 Submission” which is testing the concept that an R-language based submission package for ADaMs and TLFs can meet the needs and the expectations of the FDA reviewers, including assessing code review and analyzing reproducibility. This is great progress! See the Submissions Working Group section below for more details.\nAnd there’s more! From the appointment of our new Executive Director, Terry Christiani, to the launch of our new Quarto website there’s a lot to dive into!\nWe’ve also seen impressive progress in our technical working groups, and we continue to support R User Groups across the globe.\nWhether you’re interested in the latest package developments, upcoming webinars, or community stories, there’s something here for everyone.\nLet’s explore what’s new in the R world!\n\n\n\nNew Executive Director\nNew Quarto Website\nBuilding Extended R Packages to Improve R Infrastructure\nTechnical Projects and Working Groups\nR Consortium Webinars\nEmpowering R User Groups Globally with R Consortium’s Support!\n\n\n\n\nWe are excited to announce that Terry Christiani has been appointed as the new Executive Director of the R Consortium! The board of directors affirmed Terry’s selection during our August 2024 board meeting, following a thorough process in which a dedicated selection committee interviewed candidates and provided recommendations. We look forward to Terry’s leadership in guiding the R Consortium’s initiatives and supporting the global R community.\n“I have been involved in supporting the R language and its users for many years and am so excited to have the opportunity to work with the R Consortium. The consortium is supporting important work across multiple industries. I hope to ensure that we continue to build on past successes and create more opportunities for R users to deliver valuable insights and analyses for their organizations.”\n—Terry Christiani, Executive Director, R Consortium\n\n\n\nThe R Consortium has a new website based on Quarto, the open source technical publishing system. Quarto allows easy embedding of R code examples as well as R-based interactive charts. Most of the R community already publishes documents in Quarto, making it easier to accept community contributions for blogs and technical documents.\nThe URL is the same: www.r-consortium.org. The older site is archived at archive.r-consortium.org.\n\n\n\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R ecosystem. We seek to accomplish this by funding projects that will improve the technical infrastructure of R.\nThere are two open application grant cycles each year. The latest round of the R Consortium’s Call for Proposals officially ended on October 1st, 2024.\nWe want to extend a huge thank you to everyone who submitted proposals. Each submission plays a pivotal role in strengthening the R ecosystem, and we are thrilled to see such innovative ideas pour in.\nAs we eagerly anticipate the announcement of the newly funded projects, we reflect on our mission to support and enhance the technical infrastructure behind R. Past initiatives have made significant contributions, including:\n\nTesting DBI and improving key open-source database backends\nEnhancements to critical packages such as mapview and sf\nImproving R translations to expand accessibility\nContinued infrastructure development for R on Windows and macOS\n\nStay tuned for the upcoming announcement of the new projects that will continue to drive the evolution of R’s technical foundation!\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\nSecure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database" + "text": "The primary mission of the R Consortium is to develop and implement infrastructure projects to support the R community. As a Linux Foundation Project, the R Community embraces principles of openness and collaboration as defined in the Code of Conduct." }, { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#main-sections-at-a-glance", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#main-sections-at-a-glance", - "title": "R Consortium Q3 2024 Newsletter", - "section": "", - "text": "New Executive Director\nNew Quarto Website\nBuilding Extended R Packages to Improve R Infrastructure\nTechnical Projects and Working Groups\nR Consortium Webinars\nEmpowering R User Groups Globally with R Consortium’s Support!" + "objectID": "about/governance.html#board-of-directors", + "href": "about/governance.html#board-of-directors", + "title": "Governance", + "section": "Board of Directors", + "text": "Board of Directors\nThe business of the foundation is managed by its Board of Directors, composed of appointed Platinum members of the R Consortium, annually elected Silver members of the R Consortium, and the ISC appointed director as defined in the ByLaws (PDF).\n\n\n\n\nMehar Singh\n\n\nPROCOGIA (SILVER MEMBER REPRESENTATIVE)(R CONSORTIUM CHAIR)\n\n\nMehar founded ProCogia a decade ago to offer more value and better service to clients than traditional consulting firms. Mehar has a background in Electrical Engineering and has worked primarily in consulting, technology and telecom sectors. He has held board positions at R Consortium, University of Washington, Society of Punjabi Engineers & Technologists to name a few. He is passionate about open-source technology, developing innovative products, skydiving and sea fishing.\n\n\n\n\n\n\n\n\nDavid Smith\n\n\nMICROSOFT (PLATINUM MEMBER)(R CONSORTIUM TREASURER)\n\n\nDavid Smith is a developer advocate at Microsoft, with a focus on data science and the R community. With a background in Statistics, he writes regularly about applications of R at the Revolutions blog (blog.revolutionanalytics.com), and is a co-author of “Introduction to R”, the R manual. Follow David on Twitter as @revodavid\n\n\n\n\n\n\nJames Black\n\n\nROCHE (PLATINUM MEMBER)\n\n\n\n\n\nMichael Lawrence\n\n\nR FOUNDATION (R FOUNDATION REPRESENTATIVE)\n\n\nMichael is a scientist in the Bioinformatics and Computational Biology department at Genentech Research and Early Development (gRED), based in South San Francisco, CA. There he leads the development of tools, applications and environments for analyzing genomic data using R and Bioconductor. His research interests are in visualization, software interfacing, and genomic data manipulation. Michael is a member of the Bioconductor Technical Advisory Board, the R Core team, and the R Foundation Board.\n\n \n\n\n\n\nHenrik Bengtsson\n\n\nR FOUNDATION (R FOUNDATION REPRESENTATIVE) (ISC CHAIRPERSON)\n\n\nHenrik Bengtsson is an Associated Professor at University of California, San Francisco, a member of the R Foundation, with a background in Computer Science and Mathematical Statistics. He has used R since 2000 for applied research in statistics and bioinformatics. He develops statistical methods, scientific computational software, and programming tools. His work includes R packages for science (e.g. matrixStats, and PSCBS, aroma.affymetrix) and software development (e.g. future, profmem, startup, and R.rsp).\n\n \n\n\n\n\nHadley Wickham\n\n\nPOSIT (PLATINUM MEMBER)\n\n\nHadley is Chief Scientist at RStudio, a member of the R Foundation, and Adjunct Professor at Stanford University and the University of Auckland. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (the tidyverse: including ggplot2, dplyr, tidyr, purrr, and readr) and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and speaker promoting the use of R for data science. Learn more on his website, http://hadley.nz.\n\n \n\n\n\n\nJared Lander\n\n\nLANDER ANALYTICS (SILVER MEMBER REPRESENTATIVE)\n\n\nJared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York R Conference and R in Government Conference, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. Jared is a frequent speaker at conferences, universities and meetups around the world.\n\n\n\n\n\nBenjamin Arancibia\n\n\nGSK (SILVER MEMBER REPRESENTATIVE)\n\n\nBenjamin Arancibia, Director of Data Science, focuses on enabling the use of R in GSK Biostatistics. He builds tools to make data science fun, reproducible, and helps advocate for the use of R in the department. Ben is passionate about making sure that teams have the right support when using R in production analyses and helping teams learn while delivering. He is an advocate of R and open source technologies internally at GSK and externally speaking about lived experiences at various conferences.\n\n \n\n\n\n\nMike K Smith\n\n\nPFIZER (SILVER MEMBER REPRESENTATIVE)\n\n\nMike K Smith, Lead, R Centre of Excellence and Senior Director Statistics at Pfizer. Mike is a professional geek, helping colleagues from the business lines understand the power of reproducibility, automation and writing good code and helping the IT department understand the needs of the business lines. He is passionate about driving business outcomes through primary research, data and alternative data solutions as well as statistical analysis.\n\n \n\n\n\n\nUday Preetham Palukuru\n\n\nMERCK (SILVER MEMBER REPRESENTATIVE)\n\n\nUday Preetham Palukuru is a Standards lead at Merck &Co., providing leadership to develop and maintain global standards for ADaM implementation, R package development, Open Source package qualification, Computing Platform enhancements and compliance management tools. He has contributed to various internal and external R packages and is a member of the R Validation Hub Executive committee. He actively promotes the use of open source software in clinical trial data analysis via forums and paper publications. He has a PhD in Bioengineering from Temple University.\n\n\n\n\nPhilip Brown\n\n\nBIOGEN (PLATINUM MEMBER)" }, { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-executive-director", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-executive-director", - "title": "R Consortium Q3 2024 Newsletter", - "section": "", - "text": "We are excited to announce that Terry Christiani has been appointed as the new Executive Director of the R Consortium! The board of directors affirmed Terry’s selection during our August 2024 board meeting, following a thorough process in which a dedicated selection committee interviewed candidates and provided recommendations. We look forward to Terry’s leadership in guiding the R Consortium’s initiatives and supporting the global R community.\n“I have been involved in supporting the R language and its users for many years and am so excited to have the opportunity to work with the R Consortium. The consortium is supporting important work across multiple industries. I hope to ensure that we continue to build on past successes and create more opportunities for R users to deliver valuable insights and analyses for their organizations.”\n—Terry Christiani, Executive Director, R Consortium" + "objectID": "about/governance.html#infrastructure-steering-committee", + "href": "about/governance.html#infrastructure-steering-committee", + "title": "Governance", + "section": "Infrastructure Steering Committee", + "text": "Infrastructure Steering Committee\n\nAn Infrastructure Steering Committee (ISC) is responsible for the identification, selection, and oversight of infrastructure projects, as well as directing best practices and community leadership within the R community. Voting representatives are appointed by the Platinum and Silver members of the R Consortium, as well as an elected member from the Silver membership class and the project leads for all Top Level Projects as directed in the ISC Charter (PDF)." }, { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-r-consortium-quarto-website", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-r-consortium-quarto-website", - "title": "R Consortium Q3 2024 Newsletter", - "section": "", - "text": "The R Consortium has a new website based on Quarto, the open source technical publishing system. Quarto allows easy embedding of R code examples as well as R-based interactive charts. Most of the R community already publishes documents in Quarto, making it easier to accept community contributions for blogs and technical documents.\nThe URL is the same: www.r-consortium.org. The older site is archived at archive.r-consortium.org." + "objectID": "about/governance.html#leadership", + "href": "about/governance.html#leadership", + "title": "Governance", + "section": "Leadership", + "text": "Leadership\nAs a project operating within the Linux Foundation, the project staff from the Linux Foundation focuses on project growth and health, ensuring a vendor-neutral environment for collaboration.\n\n\n\n\nTerry Christiani\n\n\nEXECUTIVE DIRECTOR\n\n\n30 years of building content strategies to help companies acquire and support customers. Successfully rebranded and created content programs to help build and sell 4 different companies. Built programs to identify and remedy content management issues affecting content performance. Managed outreach programs to open source communities through digital, hybrid, and IRL events.\n\n\n \n\n\n\n\n\nDr. Amanda Martin\n\n\nDIRECTOR OF PROGRAM MANAGEMENT\n\n\nDr. Amanda Martin is a Director of Program Management for the R Consortium. Amanda has taught and managed technical projects since 2005 with the single desire to improve the entire world." }, { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#building-extended-r-packages-to-improve-r-infrastructure", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#building-extended-r-packages-to-improve-r-infrastructure", - "title": "R Consortium Q3 2024 Newsletter", + "objectID": "about/thank-you.html", + "href": "about/thank-you.html", + "title": "Contributors to this Website", "section": "", - "text": "A major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R ecosystem. We seek to accomplish this by funding projects that will improve the technical infrastructure of R.\nThere are two open application grant cycles each year. The latest round of the R Consortium’s Call for Proposals officially ended on October 1st, 2024.\nWe want to extend a huge thank you to everyone who submitted proposals. Each submission plays a pivotal role in strengthening the R ecosystem, and we are thrilled to see such innovative ideas pour in.\nAs we eagerly anticipate the announcement of the newly funded projects, we reflect on our mission to support and enhance the technical infrastructure behind R. Past initiatives have made significant contributions, including:\n\nTesting DBI and improving key open-source database backends\nEnhancements to critical packages such as mapview and sf\nImproving R translations to expand accessibility\nContinued infrastructure development for R on Windows and macOS\n\nStay tuned for the upcoming announcement of the new projects that will continue to drive the evolution of R’s technical foundation!\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\nSecure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database" - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#submissions-working-group", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#submissions-working-group", - "title": "R Consortium Q3 2024 Newsletter", - "section": "Submissions Working Group", - "text": "Submissions Working Group\n\nPilot 3 complete!\nThe R Consortium is pleased to announce the successful completion of the Pilot 3 Submission which extended the work done in Pilots 1 and 2 by generating the ADaM datasets. The complete FDA response letter is available here.\nThe objective of the R Consortium R Submission Pilot 3 Project is to test the concept that an R-language based submission package for ADaMs and TLFs can meet the needs and the expectations of the FDA reviewers, including assessing code review and analyzing reproducibility. All submission materials and communications from this pilot are publicly available, with the aim of providing a working example for future R-language based FDA submissions. This is an FDA-industry collaboration through the non-profit organization R Consortium.\nA pilot 3 overview presentation during the 2024 R/medicine conference is available on YouTube.\n\n\nPilot 4 submission on Sept 20\nAs a next step, the R Consortium R Submission Working Group initiated submission pilot 4, to explore the use of novel technologies such as Linux containers and web assembly to bundle a Shiny application into a self-contained package, facilitating a smoother process of both transferring and executing the application.\nPilot 4 is being cited in a recent Nature paper (paywall)." - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#census-working-group", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#census-working-group", - "title": "R Consortium Q3 2024 Newsletter", - "section": "Census Working Group", - "text": "Census Working Group\nThe U.S. Census Bureau is the premier source of data about America’s people, places and economy. This makes the Bureau a natural source of information for data analysts. R programmers who start working with Census Data, however, often run into two problems:\n\nUnderstanding what data the Census Bureau publishes.\nUnderstanding what packages on CRAN are available to help with their project.\n\nThe Census working group released a second version of their guide “A Guide to Working with Census Data in R.” The guide aims to help R programmers who are confronted with these problems. Check out the full guide here: https://github.com/RConsortium/censusguide.\nKey updates include:\n\nRevamped the section on Data Dissemination to remove reference to the (now deprecated) American Fact Finder and instead point people to the (new) data.census.gov.\nNew to working with the Census API? Check out the tutorials and resources linked in the API section to learn more and get started.\nUpdated the list of R packages listed in the guide to reflect not just new download stats but also new packages published since the initial version.\nExpanded the list of programs and datasets Census provides, including links to learn more about them.\n\nOur working group welcomes feedback! We are still working on adding tutorials and other package/training related resources to the guide, so readers have more to look forward to with the next update." - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#marshaling-and-serialization-in-r", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#marshaling-and-serialization-in-r", - "title": "R Consortium Q3 2024 Newsletter", - "section": "Marshaling and Serialization in R", - "text": "Marshaling and Serialization in R\nThe R Consortium ISC Working Group on Marshaling and Serialization in R started in May 2024. This working group aims at developing standard practices for marshaling and unmarshaling of R objects.\nThis will involve identifying current problems, raising awareness, and coming up with technical solutions. This may require additions to base R. For example, one solution might be to introduce support for serialize() and unserialize() to call registered hook functions whenever certain types of objects are encountered, which then could marshall and unmarshall those objects.\nMore information can be found here: https://github.com/RConsortium/marshalling-wg" - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#multilingual-r-documentation", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#multilingual-r-documentation", - "title": "R Consortium Q3 2024 Newsletter", - "section": "Multilingual R Documentation", - "text": "Multilingual R Documentation\nThe Multilingual R Documentation working group started in June 2024. There was a virtual meeting to set the stage, and in person meetings during R Dev Day @ PLUS. Its lead presented the project at useR! 2024.\nWe have a working package and ideas for improvement. There’s a few PRs from collaborators under review and even an example of real world use of the package: a French translation of the torchvision documentation. We have this repository and a channel in the R Consortium Slack that anyone is welcome to join to participate." - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r7-package---design-refining", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r7-package---design-refining", - "title": "R Consortium Q3 2024 Newsletter", - "section": "R7 Package - Design refining", - "text": "R7 Package - Design refining\nThe Object-Oriented Programming (OOP) working group continues to refine the design and functionality of the package through active discussions within the group and the community at large.\nThe long-term goal of this project is to merge S7 in to base R. For now, you can experiment by installing it from CRAN:\ninstall.packages(\"S7\")" - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r-validation-hub", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r-validation-hub", - "title": "R Consortium Q3 2024 Newsletter", - "section": "R Validation Hub", - "text": "R Validation Hub\nThe R Validation Hub is a collaboration to support the adoption of R within a biopharmaceutical regulatory setting.\nThe R Validation Hub enhanced their website this summer to improve navigation. Please take some time to check it out and send feedback: https://www.pharmar.org/\nThe R Validation solutions for the validation of R packages quantify the “risk” of R packages with several metrics {riskmetric} and provide a user-friendly, full-fledged R Shiny app as a central hub to gauge the “risk” of packages {riskassessment}.\nFor {riskassessment} the R Validation Hub is announcing the release of two new features:\n\nAutomate “risk decisions” based on {riskmetric} quality assessment values.\nNew module called the “Function Explorer” which allows users to explore any function exported from a package in one easy-to-use interface.\n\nSpecial thanks to Glaxo-Smith Kline (GSK) contributors for donating this code!\nFor more details about our new features, read our blog post: https://www.pharmar.org/posts/news/updates-aug-2024/\nFrom the R Validation Hub:\n“Our roadmap for the app is going scoreless. Most organizations don’t really make actionable decisions from {riskmetric}’s overall package score. It can sometimes deter our attention from the more meaningful quality metrics or even lead to unnecessary confusion or bias. As such, we want Admin users to make the decision whether they want this quantitative metric to be displayed in the app at all. Stay tuned!”\n\nCollecting regulatory package lists\nWe’ve asked a few pharmaceutical organizations what R Packages have qualified for late stage analysis. We were encouraged by the transparent effort companies like Roche made: https://insightsengineering.github.io/rvalidationhub-packages/\n\n\nReg R Repo: first pilot released\nThe Regulatory R Repository working group released its first pilot this summer, a repository of R packages with pre-calculated risk metrics: https://github.com/pharmaR/pharmapkgs\nWe are working on a second release with more advanced features: risk metrics calculated on a container image and the generation of a validation report for each R package on the repository." - }, - { - "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#get-in-touch-with-the-r-consortium", - "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#get-in-touch-with-the-r-consortium", - "title": "R Consortium Q3 2024 Newsletter", - "section": "Get in Touch with the R Consortium!", - "text": "Get in Touch with the R Consortium!\nFollow us on social media or contact us here: https://r-consortium.org/about/contact.html" + "text": "The R language is open source and is supported worldwide by people who are enthusiastic to learn and improve. The R Consortium supports R infrastructure technology projects, events, webinars, R user groups, and much more. We support the R community and we benefit from it, too.\n\n\nSimisani Ndaba, R-Ladies Gaborone chapter founder and organizer\nIsabella Velásquez, Sr. Product Marketing Manager, Posit\nErik Rodriguez, San Jose State University, Information Science & Data Analytics major\nPhat Ca, University of Hawaii, Computer Science major\nPriyanka Gagneja, R-Ladies Gaborone member\nDaniel D. Sjoberg (he/him) is a Software Engineer at Genentech, contributed R plot to main homepage. Webinar talk here: https://www.r-consortium.org/r-medicine-webinar-visualizing-survival-data-with-the-ggsurvfit-r-package\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG, contributed R plot to main homepage. Previous webinar here: https://www.r-consortium.org/new-webinar-tidy-finance-and-accessing-financial-data Upcoming webinar series here: https://www.r-consortium.org/tidy-finance-webinar-series" }, { - "objectID": "newsletters/R-Consortium-Q3-2023-Newsletter.html", - "href": "newsletters/R-Consortium-Q3-2023-Newsletter.html", - "title": "R Consortium Q3 2023 Newsletter", + "objectID": "about/thank-you.html#the-following-people-have-helped-contribute-to-this-r-consortium-quarto-based-website", + "href": "about/thank-you.html#the-following-people-have-helped-contribute-to-this-r-consortium-quarto-based-website", + "title": "Contributors to this Website", "section": "", - "text": "R Consortium Q3 2023 Newsletter\n\n\nWelcome!\nHello from the R Consortium! This quarterly newsletter puts together the latest updates about our organization’s activities, the progress each working group has made, upcoming R related events, and recordings of past events. In short, all you need to know about the R Consortium! We hope you enjoy it.\nYou haven’t read the previous newsletter? You can find them on the RC website here. Any suggestions for our next newsletter? Feel free to let us know here. You’d like to sign up to automatically receive the newsletter? Click here.\n\n\n📣 New Executive Director Announcement – Welcome back, Joseph Rickert!\n\nThe R Consortium is pleased to announce that Joseph Rickert has been appointed to the position of Executive Director reporting directly to the Board of Directors.\nJoseph has been active in the R Community since he joined Revolution Analytics in 2009 and has held prominent, community-facing positions at both the R Consortium and RStudio (now renamed posit). He is deeply involved in multiple R Consortium technical working groups, is an organizer of the Bay Area useR Group (BARUG), and has been on the R/Medicine conference organizing committee since the first conference in 2018. Joseph served on the R Consortium Board of Directors from August 2016 to July 2023, serving as Chair from 2020.\nWelcome, Joseph, to your new position!\n\n\n\nFirst Publicly Available R-Based Submission Package Submitted to FDA (Pilot 3)\n\nThe R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The FDA CDER staff are now able to begin their evaluation process. All submission materials can be found at:https://github.com/RConsortium/submissions-pilot3-adam-to-fda\nRead more about this big accomplishment and work on Pilot 4 here.\n\n\n\nISC Funded Projects Improving the R Ecosystem\n\nR Consortium Funded Project Extendr Provides Rust Extensions for R\nAndy Thomason, code performance consultant and lecturer at the University of London covering programming, physics and AI courses focused on game development, created an open source project to add Rust’s performance, reliability, and productivity to R. Andy created the Extendr package, a safe and user-friendly R extension interface for using Rust. The project was supported by a grant from the R Consortium.\n\n\nR User Groups Are Active Around the World!\n\nUse of R in Non-Profit Social Policy Research in New York\n\n\n\nUse of R for Pharma in Rosario, Argentina\n\n\n\nUtilizing R for Reproducible Open Science Research in Tucson, Arizona\n\n\n\n\nISC Call for Proposals Wrap Up\n\nMain announcement: Grants For R Language Infrastructure Projects Available Now!\nThe ISC is back with its second round of proposal calls and grant awards for 2023! The main objective is to strengthen the R ecosystem’s technical infrastructure and serve the R community better. Second Grant Cycle: September 1 to October 1, acceptance by November 1, contract by December 1.\nIf you missed the cycle this time, be sure to keep an eye out for next grant cycle in 2024!\n\n\n\nWorking groups updates\nR Certification\n\n\n\nChange in Leadership and Ongoing activities In late August Joseph Korszun stepped down as Lead of R Certification Working Group. Joseph had contributed extensively in organizing and leading the efforts to compile and prepare for alpha release of Clinical Analyst examination. He had been critical in forming this working group and contributed extensively to ensure a Minimal Viable Product. Uday Preetham Palukuru has taken over the activities as lead. Joseph Rickert continues to provide guidance to the working group. Ongoing activities include:Clarification of various R Certification Exam levels expected to be part of final releaseClean-up of GitHub issues and re-prioritization of outstanding issues Completion of reviewer feedback regarding existing questionnaire pertaining to various exam levelsDiscussion with Certiverse on using .yml files for hosting draft alpha examIdentification of select candidates to preview the alpha release and gather feedback\nUday Preetham Palukurupreetham.palukuru@merck.comJoseph Rickert Joseph.Rickert@procogia.com Further information: https://github.com/RConsortium/R-Certification-WG)\n\n\n\n\n\nR Tables for Regulatory Submission (RTRS)\n\n\n\nTables in Clinical Trials with R The version 1.0, the published version of the ebook, Tables in Clinical Trials with R is available at link: https://rconsortium.github.io/rtrs-wg.In this book we present various aspects of creating tables with the R language (R Core Team 2023) to analyze and report clinical trials data.The working group will present its work in R/Pharma in October.\nGabe Becker: gabembecker@gmail.comAdrian Waddell: adrian.waddell@gene.comJoseph Rickert: joseph.rickert@rstudio.comWorking Group github repository: https://github.com/RConsortium/rtrs-wg\n\n\n\n\n\nR Validation Hub\n\n\n\nRegulatory R Repository working group In July, the working group presented its work in the Basel R conference. The recording is available here: https://youtu.be/qqfteqh9kXw?si=2sJwP079Tj0toHY4 In summary, after collecting requirements and gathering consensus on key assumptions to build on, the team is now getting ready to start its first MVP. Would you like to join? Check out our Benefits of participating PDF link\nColine Zeballos: coline.zeballos@gmail.com\n\n\n\n\n\n\nThe R Validation Hub was selected to give a talk at the upcoming R/Pharma virtual conference on October 24-26. Register here and see you there!\nColine Zeballos: coline.zeballos@gmail.com Juliane Manitz: juliane.manitz@emdserono.com\n\n\nThe slides from Doug’s Posit::conf 2023 Pharma Round Table presentation are available here: https://pharmar.github.io/events-positconf2023/#/title-slide\nDoug Kelkhoff: doug.kelkhoff@gmail.com\n\n\n\n\n\nSubmissions\n\n\n\nPilot 3 submissionThe R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The pilot 3 test submission is an example of an all R submission package following eCTD specifications. These include the installation and loading of the proprietary {pilot3} R package and other open-source R packages, R scripts for the analysis data model (ADaM) datasets from pilot 3 and tables, listings, figures (TLFs) from pilot 1, analysis data reviewer’s guide (adrg), and other required eCTD components. The working group also began working on a pilot 4 project to explore the use of novel technologies such as Linux containers and WebAssembly software to bundle a Shiny application into a self-contained package in order to facilitate a smoother process for transferring and executing the application. Stay tuned for more about pilot 4 in the future.https://www.r-consortium.org/announcement/2023/09/11/first-publicly-available-r-based-submission-package-submitted-to-fda-pilot-3\nNing Leng: lengn@genecom Joseph Rickert: joseph.rickert@gmail.comFurther information: https://github.com/RConsortium/submissions-wg\n\n\n\n\n\n\nOBJSXP Now that we have a release on CRAN, the focus has shifted to finishing and merging the OBJSXP work into base R.\nMichael Lawrence Hadley Wickham Further information:https://github.com/RConsortium/OOP-WG\n\n\n\n\n\n\nUpcoming events – R Consortium will be there, will you?\nLatinR 2023 – Taking place in Montevideo, Uruguay from October 18-20, 2023 R government – In-person and Virtual from October 19-20, 2023 R/Pharma 2023 – Virtual from October 24th to 26th with workshops the week prior\n\n\nYou’ve missed a recent event?\nR/Basel, a useR! regional Conference July 21st, 2023, Roche Basel Campus New York R Conference – Held workshops from July 11-12 and Conference from July 13-14 2023 Cascadia R Conference – Taking place in Seattle, Washington from Saturday, August 19, 2023 Joint Statistical Meetings (JSM) – August 5 – 10, 2023, in Toronto, Canada R Project Sprint August 30 – September 1, 2023, Warwick UK Posit::conf including workshop: Leveraging & Contributing to the Pharmaverse for Clinical Trial Reporting in R was held this week in Chicago with Roche folks involved – see teaser video here https://www.youtube.com/watch?v=iOOiNG2t-Dc\n\n\nFollow the R Consortium on Social Media – We need you!\nIn this section, we highlight a few opportunities for getting more involved with the R Consortium.\n\n\n\nHelp promote the R Consortium message around the globe - Follow @RConsortium on Twitter (https://twitter.com/RConsortium), @RConsortium@fosstodon.org on Mastodon, and R Consortium on LinkedIn (https://www.linkedin.com/company/r-consortium)- We’re working on updating and improving the R Consortium YouTube account (https://www.youtube.com/c/RConsortium). There’s great content there, from events, with talks and presentations covering many R topics.- Like, comment, and share/retweet R Consortium content on an ongoing basis – new content appears frequently! \nParticipate in an R Consortium working group - Example: R in Business Working Group (https://github.com/RConsortium/RBusiness), is an R Consortium working group promoting and supporting the R programming environment and the R ecosystem in business practices and business research - R Consortium Working Groups…- Help develop a community-based collaboration platform- Organize and sponsor of events -Research relevant topics in depth Develop openly available courses/tutorials- Develop and maintain R packages" + "text": "Simisani Ndaba, R-Ladies Gaborone chapter founder and organizer\nIsabella Velásquez, Sr. Product Marketing Manager, Posit\nErik Rodriguez, San Jose State University, Information Science & Data Analytics major\nPhat Ca, University of Hawaii, Computer Science major\nPriyanka Gagneja, R-Ladies Gaborone member\nDaniel D. Sjoberg (he/him) is a Software Engineer at Genentech, contributed R plot to main homepage. Webinar talk here: https://www.r-consortium.org/r-medicine-webinar-visualizing-survival-data-with-the-ggsurvfit-r-package\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG, contributed R plot to main homepage. Previous webinar here: https://www.r-consortium.org/new-webinar-tidy-finance-and-accessing-financial-data Upcoming webinar series here: https://www.r-consortium.org/tidy-finance-webinar-series" }, { "objectID": "about/privacy.html", @@ -1204,740 +1141,810 @@ "text": "This Policy is current as of the effective date set forth above. If we change our privacy policies and procedures, we will post those changes on this page and/or continue to provide access to a copy of the prior version. If we make any changes to this Privacy Policy that materially change how we treat your personal information, we will endeavor to provide you with reasonable notice of such changes, such as via prominent notice on our Sites or to your email address of record, and where required by law, we will obtain your consent or give you the opportunity to opt out of such changes." }, { - "objectID": "about/thank-you.html", - "href": "about/thank-you.html", - "title": "Contributors to this Website", + "objectID": "newsletters/R-Consortium-Q3-2023-Newsletter.html", + "href": "newsletters/R-Consortium-Q3-2023-Newsletter.html", + "title": "R Consortium Q3 2023 Newsletter", "section": "", - "text": "The R language is open source and is supported worldwide by people who are enthusiastic to learn and improve. The R Consortium supports R infrastructure technology projects, events, webinars, R user groups, and much more. We support the R community and we benefit from it, too.\n\n\nSimisani Ndaba, R-Ladies Gaborone chapter founder and organizer\nIsabella Velásquez, Sr. Product Marketing Manager, Posit\nErik Rodriguez, San Jose State University, Information Science & Data Analytics major\nPhat Ca, University of Hawaii, Computer Science major\nPriyanka Gagneja, R-Ladies Gaborone member\nDaniel D. Sjoberg (he/him) is a Software Engineer at Genentech, contributed R plot to main homepage. Webinar talk here: https://www.r-consortium.org/r-medicine-webinar-visualizing-survival-data-with-the-ggsurvfit-r-package\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG, contributed R plot to main homepage. Previous webinar here: https://www.r-consortium.org/new-webinar-tidy-finance-and-accessing-financial-data Upcoming webinar series here: https://www.r-consortium.org/tidy-finance-webinar-series" + "text": "R Consortium Q3 2023 Newsletter\n\n\nWelcome!\nHello from the R Consortium! This quarterly newsletter puts together the latest updates about our organization’s activities, the progress each working group has made, upcoming R related events, and recordings of past events. In short, all you need to know about the R Consortium! We hope you enjoy it.\nYou haven’t read the previous newsletter? You can find them on the RC website here. Any suggestions for our next newsletter? Feel free to let us know here. You’d like to sign up to automatically receive the newsletter? Click here.\n\n\n📣 New Executive Director Announcement – Welcome back, Joseph Rickert!\n\nThe R Consortium is pleased to announce that Joseph Rickert has been appointed to the position of Executive Director reporting directly to the Board of Directors.\nJoseph has been active in the R Community since he joined Revolution Analytics in 2009 and has held prominent, community-facing positions at both the R Consortium and RStudio (now renamed posit). He is deeply involved in multiple R Consortium technical working groups, is an organizer of the Bay Area useR Group (BARUG), and has been on the R/Medicine conference organizing committee since the first conference in 2018. Joseph served on the R Consortium Board of Directors from August 2016 to July 2023, serving as Chair from 2020.\nWelcome, Joseph, to your new position!\n\n\n\nFirst Publicly Available R-Based Submission Package Submitted to FDA (Pilot 3)\n\nThe R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The FDA CDER staff are now able to begin their evaluation process. All submission materials can be found at:https://github.com/RConsortium/submissions-pilot3-adam-to-fda\nRead more about this big accomplishment and work on Pilot 4 here.\n\n\n\nISC Funded Projects Improving the R Ecosystem\n\nR Consortium Funded Project Extendr Provides Rust Extensions for R\nAndy Thomason, code performance consultant and lecturer at the University of London covering programming, physics and AI courses focused on game development, created an open source project to add Rust’s performance, reliability, and productivity to R. Andy created the Extendr package, a safe and user-friendly R extension interface for using Rust. The project was supported by a grant from the R Consortium.\n\n\nR User Groups Are Active Around the World!\n\nUse of R in Non-Profit Social Policy Research in New York\n\n\n\nUse of R for Pharma in Rosario, Argentina\n\n\n\nUtilizing R for Reproducible Open Science Research in Tucson, Arizona\n\n\n\n\nISC Call for Proposals Wrap Up\n\nMain announcement: Grants For R Language Infrastructure Projects Available Now!\nThe ISC is back with its second round of proposal calls and grant awards for 2023! The main objective is to strengthen the R ecosystem’s technical infrastructure and serve the R community better. Second Grant Cycle: September 1 to October 1, acceptance by November 1, contract by December 1.\nIf you missed the cycle this time, be sure to keep an eye out for next grant cycle in 2024!\n\n\n\nWorking groups updates\nR Certification\n\n\n\nChange in Leadership and Ongoing activities In late August Joseph Korszun stepped down as Lead of R Certification Working Group. Joseph had contributed extensively in organizing and leading the efforts to compile and prepare for alpha release of Clinical Analyst examination. He had been critical in forming this working group and contributed extensively to ensure a Minimal Viable Product. Uday Preetham Palukuru has taken over the activities as lead. Joseph Rickert continues to provide guidance to the working group. Ongoing activities include:Clarification of various R Certification Exam levels expected to be part of final releaseClean-up of GitHub issues and re-prioritization of outstanding issues Completion of reviewer feedback regarding existing questionnaire pertaining to various exam levelsDiscussion with Certiverse on using .yml files for hosting draft alpha examIdentification of select candidates to preview the alpha release and gather feedback\nUday Preetham Palukurupreetham.palukuru@merck.comJoseph Rickert Joseph.Rickert@procogia.com Further information: https://github.com/RConsortium/R-Certification-WG)\n\n\n\n\n\nR Tables for Regulatory Submission (RTRS)\n\n\n\nTables in Clinical Trials with R The version 1.0, the published version of the ebook, Tables in Clinical Trials with R is available at link: https://rconsortium.github.io/rtrs-wg.In this book we present various aspects of creating tables with the R language (R Core Team 2023) to analyze and report clinical trials data.The working group will present its work in R/Pharma in October.\nGabe Becker: gabembecker@gmail.comAdrian Waddell: adrian.waddell@gene.comJoseph Rickert: joseph.rickert@rstudio.comWorking Group github repository: https://github.com/RConsortium/rtrs-wg\n\n\n\n\n\nR Validation Hub\n\n\n\nRegulatory R Repository working group In July, the working group presented its work in the Basel R conference. The recording is available here: https://youtu.be/qqfteqh9kXw?si=2sJwP079Tj0toHY4 In summary, after collecting requirements and gathering consensus on key assumptions to build on, the team is now getting ready to start its first MVP. Would you like to join? Check out our Benefits of participating PDF link\nColine Zeballos: coline.zeballos@gmail.com\n\n\n\n\n\n\nThe R Validation Hub was selected to give a talk at the upcoming R/Pharma virtual conference on October 24-26. Register here and see you there!\nColine Zeballos: coline.zeballos@gmail.com Juliane Manitz: juliane.manitz@emdserono.com\n\n\nThe slides from Doug’s Posit::conf 2023 Pharma Round Table presentation are available here: https://pharmar.github.io/events-positconf2023/#/title-slide\nDoug Kelkhoff: doug.kelkhoff@gmail.com\n\n\n\n\n\nSubmissions\n\n\n\nPilot 3 submissionThe R Consortium is pleased to announce that on August 28, 2023, the R Submissions Working Group successfully submitted an R-based test submission pilot 3 package through the FDA eCTD gateway! The pilot 3 test submission is an example of an all R submission package following eCTD specifications. These include the installation and loading of the proprietary {pilot3} R package and other open-source R packages, R scripts for the analysis data model (ADaM) datasets from pilot 3 and tables, listings, figures (TLFs) from pilot 1, analysis data reviewer’s guide (adrg), and other required eCTD components. The working group also began working on a pilot 4 project to explore the use of novel technologies such as Linux containers and WebAssembly software to bundle a Shiny application into a self-contained package in order to facilitate a smoother process for transferring and executing the application. Stay tuned for more about pilot 4 in the future.https://www.r-consortium.org/announcement/2023/09/11/first-publicly-available-r-based-submission-package-submitted-to-fda-pilot-3\nNing Leng: lengn@genecom Joseph Rickert: joseph.rickert@gmail.comFurther information: https://github.com/RConsortium/submissions-wg\n\n\n\n\n\n\nOBJSXP Now that we have a release on CRAN, the focus has shifted to finishing and merging the OBJSXP work into base R.\nMichael Lawrence Hadley Wickham Further information:https://github.com/RConsortium/OOP-WG\n\n\n\n\n\n\nUpcoming events – R Consortium will be there, will you?\nLatinR 2023 – Taking place in Montevideo, Uruguay from October 18-20, 2023 R government – In-person and Virtual from October 19-20, 2023 R/Pharma 2023 – Virtual from October 24th to 26th with workshops the week prior\n\n\nYou’ve missed a recent event?\nR/Basel, a useR! regional Conference July 21st, 2023, Roche Basel Campus New York R Conference – Held workshops from July 11-12 and Conference from July 13-14 2023 Cascadia R Conference – Taking place in Seattle, Washington from Saturday, August 19, 2023 Joint Statistical Meetings (JSM) – August 5 – 10, 2023, in Toronto, Canada R Project Sprint August 30 – September 1, 2023, Warwick UK Posit::conf including workshop: Leveraging & Contributing to the Pharmaverse for Clinical Trial Reporting in R was held this week in Chicago with Roche folks involved – see teaser video here https://www.youtube.com/watch?v=iOOiNG2t-Dc\n\n\nFollow the R Consortium on Social Media – We need you!\nIn this section, we highlight a few opportunities for getting more involved with the R Consortium.\n\n\n\nHelp promote the R Consortium message around the globe - Follow @RConsortium on Twitter (https://twitter.com/RConsortium), @RConsortium@fosstodon.org on Mastodon, and R Consortium on LinkedIn (https://www.linkedin.com/company/r-consortium)- We’re working on updating and improving the R Consortium YouTube account (https://www.youtube.com/c/RConsortium). There’s great content there, from events, with talks and presentations covering many R topics.- Like, comment, and share/retweet R Consortium content on an ongoing basis – new content appears frequently! \nParticipate in an R Consortium working group - Example: R in Business Working Group (https://github.com/RConsortium/RBusiness), is an R Consortium working group promoting and supporting the R programming environment and the R ecosystem in business practices and business research - R Consortium Working Groups…- Help develop a community-based collaboration platform- Organize and sponsor of events -Research relevant topics in depth Develop openly available courses/tutorials- Develop and maintain R packages" }, { - "objectID": "about/thank-you.html#the-following-people-have-helped-contribute-to-this-r-consortium-quarto-based-website", - "href": "about/thank-you.html#the-following-people-have-helped-contribute-to-this-r-consortium-quarto-based-website", - "title": "Contributors to this Website", + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html", + "title": "R Consortium Q3 2024 Newsletter", "section": "", - "text": "Simisani Ndaba, R-Ladies Gaborone chapter founder and organizer\nIsabella Velásquez, Sr. Product Marketing Manager, Posit\nErik Rodriguez, San Jose State University, Information Science & Data Analytics major\nPhat Ca, University of Hawaii, Computer Science major\nPriyanka Gagneja, R-Ladies Gaborone member\nDaniel D. Sjoberg (he/him) is a Software Engineer at Genentech, contributed R plot to main homepage. Webinar talk here: https://www.r-consortium.org/r-medicine-webinar-visualizing-survival-data-with-the-ggsurvfit-r-package\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG, contributed R plot to main homepage. Previous webinar here: https://www.r-consortium.org/new-webinar-tidy-finance-and-accessing-financial-data Upcoming webinar series here: https://www.r-consortium.org/tidy-finance-webinar-series" + "text": "Welcome to the R Consortium’s Q3 2024 Newsletter!\nThis quarter has been packed with exciting updates, innovative projects, and global community initiatives that are shaping the future of R.\nBig news! The R Submissions Working Group successfully completed the “Pilot 3 Submission” which is testing the concept that an R-language based submission package for ADaMs and TLFs can meet the needs and the expectations of the FDA reviewers, including assessing code review and analyzing reproducibility. This is great progress! See the Submissions Working Group section below for more details.\nAnd there’s more! From the appointment of our new Executive Director, Terry Christiani, to the launch of our new Quarto website there’s a lot to dive into!\nWe’ve also seen impressive progress in our technical working groups, and we continue to support R User Groups across the globe.\nWhether you’re interested in the latest package developments, upcoming webinars, or community stories, there’s something here for everyone.\nLet’s explore what’s new in the R world!\n\n\n\nNew Executive Director\nNew Quarto Website\nBuilding Extended R Packages to Improve R Infrastructure\nTechnical Projects and Working Groups\nR Consortium Webinars\nEmpowering R User Groups Globally with R Consortium’s Support!\n\n\n\n\nWe are excited to announce that Terry Christiani has been appointed as the new Executive Director of the R Consortium! The board of directors affirmed Terry’s selection during our August 2024 board meeting, following a thorough process in which a dedicated selection committee interviewed candidates and provided recommendations. We look forward to Terry’s leadership in guiding the R Consortium’s initiatives and supporting the global R community.\n“I have been involved in supporting the R language and its users for many years and am so excited to have the opportunity to work with the R Consortium. The consortium is supporting important work across multiple industries. I hope to ensure that we continue to build on past successes and create more opportunities for R users to deliver valuable insights and analyses for their organizations.”\n—Terry Christiani, Executive Director, R Consortium\n\n\n\nThe R Consortium has a new website based on Quarto, the open source technical publishing system. Quarto allows easy embedding of R code examples as well as R-based interactive charts. Most of the R community already publishes documents in Quarto, making it easier to accept community contributions for blogs and technical documents.\nThe URL is the same: www.r-consortium.org. The older site is archived at archive.r-consortium.org.\n\n\n\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R ecosystem. We seek to accomplish this by funding projects that will improve the technical infrastructure of R.\nThere are two open application grant cycles each year. The latest round of the R Consortium’s Call for Proposals officially ended on October 1st, 2024.\nWe want to extend a huge thank you to everyone who submitted proposals. Each submission plays a pivotal role in strengthening the R ecosystem, and we are thrilled to see such innovative ideas pour in.\nAs we eagerly anticipate the announcement of the newly funded projects, we reflect on our mission to support and enhance the technical infrastructure behind R. Past initiatives have made significant contributions, including:\n\nTesting DBI and improving key open-source database backends\nEnhancements to critical packages such as mapview and sf\nImproving R translations to expand accessibility\nContinued infrastructure development for R on Windows and macOS\n\nStay tuned for the upcoming announcement of the new projects that will continue to drive the evolution of R’s technical foundation!\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\nSecure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database" }, { - "objectID": "about/governance.html", - "href": "about/governance.html", - "title": "Governance", + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#main-sections-at-a-glance", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#main-sections-at-a-glance", + "title": "R Consortium Q3 2024 Newsletter", "section": "", - "text": "The primary mission of the R Consortium is to develop and implement infrastructure projects to support the R community. As a Linux Foundation Project, the R Community embraces principles of openness and collaboration as defined in the Code of Conduct." - }, - { - "objectID": "about/governance.html#board-of-directors", - "href": "about/governance.html#board-of-directors", - "title": "Governance", - "section": "Board of Directors", - "text": "Board of Directors\nThe business of the foundation is managed by its Board of Directors, composed of appointed Platinum members of the R Consortium, annually elected Silver members of the R Consortium, and the ISC appointed director as defined in the ByLaws (PDF).\n\n\n\n\nMehar Singh\n\n\nPROCOGIA (SILVER MEMBER REPRESENTATIVE)(R CONSORTIUM CHAIR)\n\n\nMehar founded ProCogia a decade ago to offer more value and better service to clients than traditional consulting firms. Mehar has a background in Electrical Engineering and has worked primarily in consulting, technology and telecom sectors. He has held board positions at R Consortium, University of Washington, Society of Punjabi Engineers & Technologists to name a few. He is passionate about open-source technology, developing innovative products, skydiving and sea fishing.\n\n\n\n\n\n\n\n\nDavid Smith\n\n\nMICROSOFT (PLATINUM MEMBER)(R CONSORTIUM TREASURER)\n\n\nDavid Smith is a developer advocate at Microsoft, with a focus on data science and the R community. With a background in Statistics, he writes regularly about applications of R at the Revolutions blog (blog.revolutionanalytics.com), and is a co-author of “Introduction to R”, the R manual. Follow David on Twitter as @revodavid\n\n\n\n\n\n\nJames Black\n\n\nROCHE (PLATINUM MEMBER)\n\n\n\n\n\nMichael Lawrence\n\n\nR FOUNDATION (R FOUNDATION REPRESENTATIVE)\n\n\nMichael is a scientist in the Bioinformatics and Computational Biology department at Genentech Research and Early Development (gRED), based in South San Francisco, CA. There he leads the development of tools, applications and environments for analyzing genomic data using R and Bioconductor. His research interests are in visualization, software interfacing, and genomic data manipulation. Michael is a member of the Bioconductor Technical Advisory Board, the R Core team, and the R Foundation Board.\n\n \n\n\n\n\nHenrik Bengtsson\n\n\nR FOUNDATION (R FOUNDATION REPRESENTATIVE) (ISC CHAIRPERSON)\n\n\nHenrik Bengtsson is an Associated Professor at University of California, San Francisco, a member of the R Foundation, with a background in Computer Science and Mathematical Statistics. He has used R since 2000 for applied research in statistics and bioinformatics. He develops statistical methods, scientific computational software, and programming tools. His work includes R packages for science (e.g. matrixStats, and PSCBS, aroma.affymetrix) and software development (e.g. future, profmem, startup, and R.rsp).\n\n \n\n\n\n\nHadley Wickham\n\n\nPOSIT (PLATINUM MEMBER)\n\n\nHadley is Chief Scientist at RStudio, a member of the R Foundation, and Adjunct Professor at Stanford University and the University of Auckland. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (the tidyverse: including ggplot2, dplyr, tidyr, purrr, and readr) and principled software development (roxygen2, testthat, devtools). He is also a writer, educator, and speaker promoting the use of R for data science. Learn more on his website, http://hadley.nz.\n\n \n\n\n\n\nJared Lander\n\n\nLANDER ANALYTICS (SILVER MEMBER REPRESENTATIVE)\n\n\nJared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York R Conference and R in Government Conference, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. Jared is a frequent speaker at conferences, universities and meetups around the world.\n\n\n\n\n\nBenjamin Arancibia\n\n\nGSK (SILVER MEMBER REPRESENTATIVE)\n\n\nBenjamin Arancibia, Director of Data Science, focuses on enabling the use of R in GSK Biostatistics. He builds tools to make data science fun, reproducible, and helps advocate for the use of R in the department. Ben is passionate about making sure that teams have the right support when using R in production analyses and helping teams learn while delivering. He is an advocate of R and open source technologies internally at GSK and externally speaking about lived experiences at various conferences.\n\n \n\n\n\n\nMike K Smith\n\n\nPFIZER (SILVER MEMBER REPRESENTATIVE)\n\n\nMike K Smith, Lead, R Centre of Excellence and Senior Director Statistics at Pfizer. Mike is a professional geek, helping colleagues from the business lines understand the power of reproducibility, automation and writing good code and helping the IT department understand the needs of the business lines. He is passionate about driving business outcomes through primary research, data and alternative data solutions as well as statistical analysis.\n\n \n\n\n\n\nUday Preetham Palukuru\n\n\nMERCK (SILVER MEMBER REPRESENTATIVE)\n\n\nUday Preetham Palukuru is a Standards lead at Merck &Co., providing leadership to develop and maintain global standards for ADaM implementation, R package development, Open Source package qualification, Computing Platform enhancements and compliance management tools. He has contributed to various internal and external R packages and is a member of the R Validation Hub Executive committee. He actively promotes the use of open source software in clinical trial data analysis via forums and paper publications. He has a PhD in Bioengineering from Temple University.\n\n\n\n\nPhilip Brown\n\n\nBIOGEN (PLATINUM MEMBER)" + "text": "New Executive Director\nNew Quarto Website\nBuilding Extended R Packages to Improve R Infrastructure\nTechnical Projects and Working Groups\nR Consortium Webinars\nEmpowering R User Groups Globally with R Consortium’s Support!" }, { - "objectID": "about/governance.html#infrastructure-steering-committee", - "href": "about/governance.html#infrastructure-steering-committee", - "title": "Governance", - "section": "Infrastructure Steering Committee", - "text": "Infrastructure Steering Committee\n\nAn Infrastructure Steering Committee (ISC) is responsible for the identification, selection, and oversight of infrastructure projects, as well as directing best practices and community leadership within the R community. Voting representatives are appointed by the Platinum and Silver members of the R Consortium, as well as an elected member from the Silver membership class and the project leads for all Top Level Projects as directed in the ISC Charter (PDF)." + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-executive-director", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-executive-director", + "title": "R Consortium Q3 2024 Newsletter", + "section": "", + "text": "We are excited to announce that Terry Christiani has been appointed as the new Executive Director of the R Consortium! The board of directors affirmed Terry’s selection during our August 2024 board meeting, following a thorough process in which a dedicated selection committee interviewed candidates and provided recommendations. We look forward to Terry’s leadership in guiding the R Consortium’s initiatives and supporting the global R community.\n“I have been involved in supporting the R language and its users for many years and am so excited to have the opportunity to work with the R Consortium. The consortium is supporting important work across multiple industries. I hope to ensure that we continue to build on past successes and create more opportunities for R users to deliver valuable insights and analyses for their organizations.”\n—Terry Christiani, Executive Director, R Consortium" }, { - "objectID": "about/governance.html#leadership", - "href": "about/governance.html#leadership", - "title": "Governance", - "section": "Leadership", - "text": "Leadership\nAs a project operating within the Linux Foundation, the project staff from the Linux Foundation focuses on project growth and health, ensuring a vendor-neutral environment for collaboration.\n\n\n\n\nTerry Christiani\n\n\nEXECUTIVE DIRECTOR\n\n\n30 years of building content strategies to help companies acquire and support customers. Successfully rebranded and created content programs to help build and sell 4 different companies. Built programs to identify and remedy content management issues affecting content performance. Managed outreach programs to open source communities through digital, hybrid, and IRL events.\n\n\n \n\n\n\n\n\nDr. Amanda Martin\n\n\nDIRECTOR OF PROGRAM MANAGEMENT\n\n\nDr. Amanda Martin is a Director of Program Management for the R Consortium. Amanda has taught and managed technical projects since 2005 with the single desire to improve the entire world." + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-r-consortium-quarto-website", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#new-r-consortium-quarto-website", + "title": "R Consortium Q3 2024 Newsletter", + "section": "", + "text": "The R Consortium has a new website based on Quarto, the open source technical publishing system. Quarto allows easy embedding of R code examples as well as R-based interactive charts. Most of the R community already publishes documents in Quarto, making it easier to accept community contributions for blogs and technical documents.\nThe URL is the same: www.r-consortium.org. The older site is archived at archive.r-consortium.org." }, { - "objectID": "webinars/tidy-finance-webinar-series.html", - "href": "webinars/tidy-finance-webinar-series.html", - "title": "Tidy Finance Webinar Series", + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#building-extended-r-packages-to-improve-r-infrastructure", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#building-extended-r-packages-to-improve-r-infrastructure", + "title": "R Consortium Q3 2024 Newsletter", "section": "", - "text": "Christoph Scheuch is an independent data science and business intelligence expert. He co-created and maintains the Tidy Finance project, a transparent, open source approach to research in financial economics. Alongside contributing to Tidy Finance, its maintainers have published in leading academic journals, including the Journal of Finance, Journal of Financial Economics, Review of Finance, and Journal of Econometrics. Christoph previously held the roles of Head of Artificial Intelligence, Director of Product, and Head of BI & Data Science at the social trading platform wikifolio.com. He was an external lecturer at the Vienna University of Economics and Business (WU), where he also obtained his PhD in finance as part of the Vienna Graduate School of Finance (VGSF)." + "text": "A major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R ecosystem. We seek to accomplish this by funding projects that will improve the technical infrastructure of R.\nThere are two open application grant cycles each year. The latest round of the R Consortium’s Call for Proposals officially ended on October 1st, 2024.\nWe want to extend a huge thank you to everyone who submitted proposals. Each submission plays a pivotal role in strengthening the R ecosystem, and we are thrilled to see such innovative ideas pour in.\nAs we eagerly anticipate the announcement of the newly funded projects, we reflect on our mission to support and enhance the technical infrastructure behind R. Past initiatives have made significant contributions, including:\n\nTesting DBI and improving key open-source database backends\nEnhancements to critical packages such as mapview and sf\nImproving R translations to expand accessibility\nContinued infrastructure development for R on Windows and macOS\n\nStay tuned for the upcoming announcement of the new projects that will continue to drive the evolution of R’s technical foundation!\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\nSecure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database" }, { - "objectID": "webinars/tidy-finance-webinar-series.html#optimize-portfolios-using-the-markowitz-model", - "href": "webinars/tidy-finance-webinar-series.html#optimize-portfolios-using-the-markowitz-model", - "title": "Tidy Finance Webinar Series", - "section": "Optimize Portfolios using the Markowitz Model", - "text": "Optimize Portfolios using the Markowitz Model\nSeptember 4th, 2024 at 12:00 pm ET\nThis webinar introduces Modern Portfolio Theory and the importance of mean-variance analysis in finance. It covers the mathematics of portfolio optimization, expected returns, variances, and covariances. Participants will learn to construct efficient frontiers and implement the Markowitz model in R, from loading return data to optimizing portfolios and interpreting risk-return trade-offs.\nAgenda:\n\nIntroduction to modern portfolio theory\nUnderstanding the mathematics of portfolio optimization\nImplementing the Markowitz model in R" + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#submissions-working-group", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#submissions-working-group", + "title": "R Consortium Q3 2024 Newsletter", + "section": "Submissions Working Group", + "text": "Submissions Working Group\n\nPilot 3 complete!\nThe R Consortium is pleased to announce the successful completion of the Pilot 3 Submission which extended the work done in Pilots 1 and 2 by generating the ADaM datasets. The complete FDA response letter is available here.\nThe objective of the R Consortium R Submission Pilot 3 Project is to test the concept that an R-language based submission package for ADaMs and TLFs can meet the needs and the expectations of the FDA reviewers, including assessing code review and analyzing reproducibility. All submission materials and communications from this pilot are publicly available, with the aim of providing a working example for future R-language based FDA submissions. This is an FDA-industry collaboration through the non-profit organization R Consortium.\nA pilot 3 overview presentation during the 2024 R/medicine conference is available on YouTube.\n\n\nPilot 4 submission on Sept 20\nAs a next step, the R Consortium R Submission Working Group initiated submission pilot 4, to explore the use of novel technologies such as Linux containers and web assembly to bundle a Shiny application into a self-contained package, facilitating a smoother process of both transferring and executing the application.\nPilot 4 is being cited in a recent Nature paper (paywall)." }, { - "objectID": "webinars/tidy-finance-webinar-series.html#evaluate-performance-using-the-capital-asset-pricing-model", - "href": "webinars/tidy-finance-webinar-series.html#evaluate-performance-using-the-capital-asset-pricing-model", - "title": "Tidy Finance Webinar Series", - "section": "Evaluate Performance using the Capital Asset Pricing Model", - "text": "Evaluate Performance using the Capital Asset Pricing Model\nOctober 9th, 2024 at 12:00 pm ET\nThis webinar covers the Capital Asset Pricing Model (CAPM), starting with its intuitive derivation and its importance in finance. Participants will gain an understanding of Alpha and Beta and their roles in performance assessment. The webinar also includes an overview of popular CAPM extensions. Participants will learn to calculate Alpha and Beta in R with a step-by-step guide, from loading return data to estimating CAPM and interpreting the estimation results.\nAgenda:\n\nIntroduction to the CAPM\nUnderstanding Alpha and Beta\nCalculating Alpha and Beta in R" + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#census-working-group", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#census-working-group", + "title": "R Consortium Q3 2024 Newsletter", + "section": "Census Working Group", + "text": "Census Working Group\nThe U.S. Census Bureau is the premier source of data about America’s people, places and economy. This makes the Bureau a natural source of information for data analysts. R programmers who start working with Census Data, however, often run into two problems:\n\nUnderstanding what data the Census Bureau publishes.\nUnderstanding what packages on CRAN are available to help with their project.\n\nThe Census working group released a second version of their guide “A Guide to Working with Census Data in R.” The guide aims to help R programmers who are confronted with these problems. Check out the full guide here: https://github.com/RConsortium/censusguide.\nKey updates include:\n\nRevamped the section on Data Dissemination to remove reference to the (now deprecated) American Fact Finder and instead point people to the (new) data.census.gov.\nNew to working with the Census API? Check out the tutorials and resources linked in the API section to learn more and get started.\nUpdated the list of R packages listed in the guide to reflect not just new download stats but also new packages published since the initial version.\nExpanded the list of programs and datasets Census provides, including links to learn more about them.\n\nOur working group welcomes feedback! We are still working on adding tutorials and other package/training related resources to the guide, so readers have more to look forward to with the next update." }, { - "objectID": "webinars/tidy-finance-webinar-series.html#analyze-companies-using-financial-ratios", - "href": "webinars/tidy-finance-webinar-series.html#analyze-companies-using-financial-ratios", - "title": "Tidy Finance Webinar Series", - "section": "Analyze Companies using Financial Ratios", - "text": "Analyze Companies using Financial Ratios\nNovember 6th, 2024 at 12:00 pm ET\n\nRegister here: https://zoom.us/webinar/register/WN_BjhdZbAjSVuZHZEGhTZb7g\nThis webinar provides an overview of financial ratios and their importance in financial analysis. It covers categories such as liquidity, profitability, leverage, and efficiency. Participants will learn about financial statements, including the balance sheet, income statement, statement of cash flows, and statement of shareholders’ equity, with real-world examples. The webinar includes a step-by-step guide on calculating and interpreting financial ratios in R, from loading financial statement data to computing and interpreting key ratios.\nAgenda:\n\nIntroduction to financial ratios\nUnderstanding financial statements\nCalculating and interpreting financial ratios in R" + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#marshaling-and-serialization-in-r", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#marshaling-and-serialization-in-r", + "title": "R Consortium Q3 2024 Newsletter", + "section": "Marshaling and Serialization in R", + "text": "Marshaling and Serialization in R\nThe R Consortium ISC Working Group on Marshaling and Serialization in R started in May 2024. This working group aims at developing standard practices for marshaling and unmarshaling of R objects.\nThis will involve identifying current problems, raising awareness, and coming up with technical solutions. This may require additions to base R. For example, one solution might be to introduce support for serialize() and unserialize() to call registered hook functions whenever certain types of objects are encountered, which then could marshall and unmarshall those objects.\nMore information can be found here: https://github.com/RConsortium/marshalling-wg" }, { - "objectID": "webinars/tidy-finance-webinar-series.html#value-companies-using-discounted-cash-flow-analysis", - "href": "webinars/tidy-finance-webinar-series.html#value-companies-using-discounted-cash-flow-analysis", - "title": "Tidy Finance Webinar Series", - "section": "Value Companies using Discounted Cash Flow Analysis", - "text": "Value Companies using Discounted Cash Flow Analysis\nDecember 4th, 2024 at 12:00 pm ET\n\nRegister here: https://zoom.us/webinar/register/WN_IgpNWpN0TRKgAkwvVWylww\nSummary: This webinar provides an overview of company valuation methods with a focus on discounted cash flow (DFC) analysis. Participants will gain an understanding of DCF analysis and its components: forecasted cash flows, terminal value, and discount rate. The webinar includes steps to perform a DCF analysis and a guide to implementing DCF in R, from loading financial statement data to executing the analysis. The webinar concludes with interpreting the valuation results, offering practical insights into company valuation techniques.\nAgenda:\n\nIntroduction to company valuation\nUnderstanding DCF\nImplementing DCF in R" + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#multilingual-r-documentation", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#multilingual-r-documentation", + "title": "R Consortium Q3 2024 Newsletter", + "section": "Multilingual R Documentation", + "text": "Multilingual R Documentation\nThe Multilingual R Documentation working group started in June 2024. There was a virtual meeting to set the stage, and in person meetings during R Dev Day @ PLUS. Its lead presented the project at useR! 2024.\nWe have a working package and ideas for improvement. There’s a few PRs from collaborators under review and even an example of real world use of the package: a French translation of the torchvision documentation. We have this repository and a channel in the R Consortium Slack that anyone is welcome to join to participate." }, { - "objectID": "webinars/r-insurance-series.html#summary", - "href": "webinars/r-insurance-series.html#summary", - "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", - "section": "Summary", - "text": "Summary\nThese four webinars focused on insurance and actuarial science. The webinars were led by two experts in the field, Georgios Bakoloukas, Head Model Development and Analytics at Swiss Re, and Benedikt Schamberger, Head Atelier Technology & AI Consulting at Swiss Re.\nThese sessions offered a hands-on exploration of the transition from Excel to basic R, highlighting the benefits of working with R and one possible way to straddle across Excel and R. The subsequent webinars then moved to production-level R, and ultimately to high-performance R applications.\nThe webinars were tailored to be accessible to all, requiring no previous experience with the R programming language or specialized knowledge in insurance or actuarial science. Anyone with basic spreadsheet experience or who is considering applying for a bank loan has the necessary background to benefit from these webinars.\n\nFrom Excel to Programming in R\nSpeaker: Georgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\n\n\nQuick summary:\nThis video provided an in-depth exploration into the enduring relevance of Excel in the workplace while also emphasizing the benefits of learning to code for increased flexibility and resilience. It highlighted the common working patterns shared between Excel and R, demonstrating how transitioning from traditional spreadsheet computing to best-practice programming can be highly beneficial.\nThe webinar featured a straightforward, specific example from the insurance industry to illustrate the advantages of using the R programming language. It also presented a practical approach for integrating the thought processes and methodologies of both Excel and R, showcasing how professionals can effectively straddle these two powerful tools in their work.\n\n\n\n\nFrom programming in R to putting R into production\nSpeaker: Georgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\n\n\nQuick summary:\nWe could solve problems using coding, but how could we help others solve the same problem in the future? Sharing data and solutions was critical for real-world insurance professionals and actuarial scientists.\nContinuing the example from the first webinar, Georgios illustrated ways to document and test the solution and made it available to others using R’s frameworks for packaging, Web API creation, and graphical user interface generation (Shiny).\n\n\n\n\nR performance culture\nSpeaker: Benedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\n\n\nQuick summary:\nPremature optimization was the root of all evil. But there were occasions when we needed to improve the performance of critical code. Benedikt covered how performance fit into R’s design, what tools were available to tune it, and examples of what other aspects should be considered beyond pure runtime.\n\n\n\n\nHigh performance programming in R\nSpeaker: Benedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\n\n\nQuick summary:\nIn this webinar, Benedikt discussed how comma-separated values (CSV) files were commonly used when working with data files, as they were easy to read for humans and supported by tools like Excel or R. However, these files had a downside in terms of performance and file size. To address this, the industry developed binary formats that were more efficient. Benedikt focused on the Arrow R package and the Parquet file format and how they could help save time and disk space." + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r7-package---design-refining", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r7-package---design-refining", + "title": "R Consortium Q3 2024 Newsletter", + "section": "R7 Package - Design refining", + "text": "R7 Package - Design refining\nThe Object-Oriented Programming (OOP) working group continues to refine the design and functionality of the package through active discussions within the group and the community at large.\nThe long-term goal of this project is to merge S7 in to base R. For now, you can experiment by installing it from CRAN:\ninstall.packages(\"S7\")" }, { - "objectID": "webinars/r-insurance-series.html#speakers", - "href": "webinars/r-insurance-series.html#speakers", - "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", - "section": "Speakers", - "text": "Speakers\n\n\nGeorgios Bakoloukas, Head Model Development & Analytics, Group Risk Management, Swiss Re\nGeorgios’ team enables actuarial teams across the group to adopt best-practice programming and data science skills in daily work. Georgios is a Fellow of the Institute of Actuaries (IFoA) and Chair of IFoAs’ Programming for Actuarial Work Working Party.\n\n\n\nBenedikt Schamberger, Head Atelier Technology & AI Consulting, Swiss Re\nBenedikt recently joined the Model Development & Analytics team as a Senior Data Science Actuary. Previously, he worked for several years in Swiss Re’s Quantitative Financial Risk Management, validating financial models and risk aggregation methodologies. He supports the Atelier and R programming communities with questions surrounding infrastructure and other everyday challenges. He has an academic background in financial and actuarial mathematics." + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r-validation-hub", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#r-validation-hub", + "title": "R Consortium Q3 2024 Newsletter", + "section": "R Validation Hub", + "text": "R Validation Hub\nThe R Validation Hub is a collaboration to support the adoption of R within a biopharmaceutical regulatory setting.\nThe R Validation Hub enhanced their website this summer to improve navigation. Please take some time to check it out and send feedback: https://www.pharmar.org/\nThe R Validation solutions for the validation of R packages quantify the “risk” of R packages with several metrics {riskmetric} and provide a user-friendly, full-fledged R Shiny app as a central hub to gauge the “risk” of packages {riskassessment}.\nFor {riskassessment} the R Validation Hub is announcing the release of two new features:\n\nAutomate “risk decisions” based on {riskmetric} quality assessment values.\nNew module called the “Function Explorer” which allows users to explore any function exported from a package in one easy-to-use interface.\n\nSpecial thanks to Glaxo-Smith Kline (GSK) contributors for donating this code!\nFor more details about our new features, read our blog post: https://www.pharmar.org/posts/news/updates-aug-2024/\nFrom the R Validation Hub:\n“Our roadmap for the app is going scoreless. Most organizations don’t really make actionable decisions from {riskmetric}’s overall package score. It can sometimes deter our attention from the more meaningful quality metrics or even lead to unnecessary confusion or bias. As such, we want Admin users to make the decision whether they want this quantitative metric to be displayed in the app at all. Stay tuned!”\n\nCollecting regulatory package lists\nWe’ve asked a few pharmaceutical organizations what R Packages have qualified for late stage analysis. We were encouraged by the transparent effort companies like Roche made: https://insightsengineering.github.io/rvalidationhub-packages/\n\n\nReg R Repo: first pilot released\nThe Regulatory R Repository working group released its first pilot this summer, a repository of R packages with pre-calculated risk metrics: https://github.com/pharmaR/pharmapkgs\nWe are working on a second release with more advanced features: risk metrics calculated on a container image and the generation of a validation report for each R package on the repository." }, { - "objectID": "webinars/r-insurance-series.html#the-r-adoption-series", - "href": "webinars/r-insurance-series.html#the-r-adoption-series", - "title": "R/Insurance Series: For Everyone in Insurance or Actuarial Science", - "section": "The R Adoption Series", - "text": "The R Adoption Series\nThis is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." + "objectID": "newsletters/R-Consortium-Q3-2024-Newsletter.html#get-in-touch-with-the-r-consortium", + "href": "newsletters/R-Consortium-Q3-2024-Newsletter.html#get-in-touch-with-the-r-consortium", + "title": "R Consortium Q3 2024 Newsletter", + "section": "Get in Touch with the R Consortium!", + "text": "Get in Touch with the R Consortium!\nFollow us on social media or contact us here: https://r-consortium.org/about/contact.html" }, { - "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#slide-deck-available", - "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#slide-deck-available", - "title": "Tidy Finance and Accessing Financial Data", - "section": "Slide deck available:", - "text": "Slide deck available:\nTidy Finance and Accessing Financial Data (PDF)" + "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html", + "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html", + "title": "R Consortium Q2 2024 Newsletter", + "section": "", + "text": "Hello from the R Consortium! This quarterly newsletter puts together the latest updates about our organization’s activities, the progress each working group has made, upcoming R-related events, and recordings of past events. In short, all you need to know about our work to promote the R language and how we lead community initiatives. Please share this newsletter!\nAre you a member of the R community and want to submit your content for the newsletter? Email us at info@r-consortium.org, we’d love to include you!\nYou haven’t read the previous newsletters? You can find them on the R Consortium website here.\nAny suggestions for our next newsletter? Feel free to let us know here.\nYou’d like to sign up to automatically receive the newsletter? Click here.\n\n\n\nTechnical Projects and Working Groups\nAnnual Report\nUpcoming Events\nFree R-related Technology and Industry Webinars\nR Consortium Supports R User Groups Around the World!\nBuilding Extended R Packages to Improve R Infrastructure\n\n\n\n\n\n\nThe Infrastructure Steering Committee (ISC) conducts two open grant cycles to evaluate proposals from the community for projects that the committee believes will contribute to the technical infrastructure of the R ecosystem. During the second grant cycle of 2023, the ISC funded the following seven projects with a total of $80,000:\n\nTranslating R to Nepali\nTooling for internationalization of R help pages\nRStats Mastodon Server\nTaking r-universe to the next level\nCausal Inference in a Box\nR Kafka Client\nAccessibility Enhancements for the R Journal\n\nThe first grant cycle for 2024 has recently closed, and the ISC is evaluating ten proposals which are collectively requesting more than $200,000. These proposals include translating a Public Health Model into R, adapting R-universe technology for deploying R packages, and upgrading or extending several key R packages. The ISC expects to notify the teams submitting successful proposals by May 1, 2024.\n\n\n\nIn this section, we will highlight the progress of selected R Consortium working groups. This month we look at the R Submissions working group and the Risk Assessment workstream of the R Validation hub, which have recently achieved significant milestones.\n\n\nWith the active participation of the FDA, the R Consortium R Submissions working group is developing a series of Pilot or test submissions to uncover the challenges that must be overcome in making “all R” regulatory submissions straightforward, routine, and reproducible over a minimum six-year time horizon. Each Pilot submission builds on the previous pilot and includes additional steps. The objective of Pilot 3 is to extend the work done in the Pilot 2 study, which included wrapping a Shiny application into the submissions package, to build the AdaM data set from raw data. For each submission effort, the FDA review team recreates the study from the submission package, evaluates the correctness and reproducibility of the results, and documents discrepancies from previous pilot submission packages that they may observe.\nIn the most recent Pilot 3 submission, the FDA observed a discrepancy that was due to a difference in the coding of an imputation algorithm. The Pilot 3 statisticians used a subsetting algorithm that differed from the algorithm selected by the CDISC statisticians who built the ADaM data set used in Pilot 1 and Pilot 2. This was not a statistical error, but a failure to provide documentation at a sufficient level of detail for the FDA reviewers to make the appropriate adjustment. The episode illustrates the attention to detail required to achieve a smooth handoff to the FDA.\nAs the Pilot 3 team prepares their final submission, the Pilot 4 team is nearly ready with a submission package that will include the code required to unpack the package and have it deploy within a WebAssembly browser instance.\nFor more information on the R submission working group please visit their website." }, { - "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#summary", - "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#summary", - "title": "Tidy Finance and Accessing Financial Data", - "section": "Summary", - "text": "Summary\nThis webinar focuses on Tidy Finance and accessing financial data. Tidy Finance is an opinionated approach to empirical research in financial economics. It provided a fully transparent, open source code base in R and Python. The website provides the tools for students to learn about empirical applications based on a fully transparent code base and for instructors the materials for teaching the importance of reproducible research using tidy principles.\nChristoph Scheuch introduces Tidy Finance and illustrates the underlying principles. The webinar then focuses on accessing and managing financial data using R. It shows how to import different open source and proprietary data sets and organize them in a database." + "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#table-of-contents", + "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#table-of-contents", + "title": "R Consortium Q2 2024 Newsletter", + "section": "", + "text": "Technical Projects and Working Groups\nAnnual Report\nUpcoming Events\nFree R-related Technology and Industry Webinars\nR Consortium Supports R User Groups Around the World!\nBuilding Extended R Packages to Improve R Infrastructure" }, { - "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#agenda", - "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#agenda", - "title": "Tidy Finance and Accessing Financial Data", - "section": "Agenda:", - "text": "Agenda:\n\nIntroduction to Tidy Finance\nAccessing and Managing Financial Data\nWRDS & Other Data Providers\nQ&A Session" + "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#technical-projects-and-working-groups", + "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#technical-projects-and-working-groups", + "title": "R Consortium Q2 2024 Newsletter", + "section": "", + "text": "The Infrastructure Steering Committee (ISC) conducts two open grant cycles to evaluate proposals from the community for projects that the committee believes will contribute to the technical infrastructure of the R ecosystem. During the second grant cycle of 2023, the ISC funded the following seven projects with a total of $80,000:\n\nTranslating R to Nepali\nTooling for internationalization of R help pages\nRStats Mastodon Server\nTaking r-universe to the next level\nCausal Inference in a Box\nR Kafka Client\nAccessibility Enhancements for the R Journal\n\nThe first grant cycle for 2024 has recently closed, and the ISC is evaluating ten proposals which are collectively requesting more than $200,000. These proposals include translating a Public Health Model into R, adapting R-universe technology for deploying R packages, and upgrading or extending several key R packages. The ISC expects to notify the teams submitting successful proposals by May 1, 2024.\n\n\n\nIn this section, we will highlight the progress of selected R Consortium working groups. This month we look at the R Submissions working group and the Risk Assessment workstream of the R Validation hub, which have recently achieved significant milestones.\n\n\nWith the active participation of the FDA, the R Consortium R Submissions working group is developing a series of Pilot or test submissions to uncover the challenges that must be overcome in making “all R” regulatory submissions straightforward, routine, and reproducible over a minimum six-year time horizon. Each Pilot submission builds on the previous pilot and includes additional steps. The objective of Pilot 3 is to extend the work done in the Pilot 2 study, which included wrapping a Shiny application into the submissions package, to build the AdaM data set from raw data. For each submission effort, the FDA review team recreates the study from the submission package, evaluates the correctness and reproducibility of the results, and documents discrepancies from previous pilot submission packages that they may observe.\nIn the most recent Pilot 3 submission, the FDA observed a discrepancy that was due to a difference in the coding of an imputation algorithm. The Pilot 3 statisticians used a subsetting algorithm that differed from the algorithm selected by the CDISC statisticians who built the ADaM data set used in Pilot 1 and Pilot 2. This was not a statistical error, but a failure to provide documentation at a sufficient level of detail for the FDA reviewers to make the appropriate adjustment. The episode illustrates the attention to detail required to achieve a smooth handoff to the FDA.\nAs the Pilot 3 team prepares their final submission, the Pilot 4 team is nearly ready with a submission package that will include the code required to unpack the package and have it deploy within a WebAssembly browser instance.\nFor more information on the R submission working group please visit their website." }, { - "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#speaker", - "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#speaker", - "title": "Tidy Finance and Accessing Financial Data", - "section": "Speaker", - "text": "Speaker\n\n\nChristoph Scheuch is the Head of Artificial Intelligence at the social trading platform wikifolio Financial Technologies AG. He is responsible for researching, designing, and prototyping of cutting-edge AI-driven products using R and Python. Before his focus on AI, he was responsible for product management and business intelligence at wikifolio Financial Technologies AG and an external lecturer at the Vienna University of Economics and Business, where he taught finance students how to manage empirical projects" + "objectID": "newsletters/R-Consortium-Q2-2024-Newsletter.html#get-in-touch-with-the-r-consortium", + "href": "newsletters/R-Consortium-Q2-2024-Newsletter.html#get-in-touch-with-the-r-consortium", + "title": "R Consortium Q2 2024 Newsletter", + "section": "Get in Touch with the R Consortium!", + "text": "Get in Touch with the R Consortium!\nFollow us on social media or contact us here:https://www.r-consortium.org/contact" }, { - "objectID": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#the-r-adoption-series", - "href": "webinars/new-webinar-tidy-finance-and-accessing-financial-data.html#the-r-adoption-series", - "title": "Tidy Finance and Accessing Financial Data", - "section": "The R Adoption Series", - "text": "The R Adoption Series\nThis is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." + "objectID": "newsletters/newsletters.html", + "href": "newsletters/newsletters.html", + "title": "Newsletters", + "section": "", + "text": "Check out our previous Newsletters and stay tuned for future ones!" }, { - "objectID": "webinars/webinars.html", - "href": "webinars/webinars.html", - "title": "Webinars", + "objectID": "newsletters/newsletters.html#whats-happening-in-the-r-consortium", + "href": "newsletters/newsletters.html#whats-happening-in-the-r-consortium", + "title": "Newsletters", "section": "", - "text": "This is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series.  If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org" + "text": "Check out our previous Newsletters and stay tuned for future ones!" }, { - "objectID": "webinars/webinars.html#the-r-adoption-series", - "href": "webinars/webinars.html#the-r-adoption-series", - "title": "Webinars", + "objectID": "about/faq.html", + "href": "about/faq.html", + "title": "FAQ", "section": "", - "text": "This is a series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.\nR Consortium will keep this page updated with information on future webinars in the R Adoption series.  If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org" + "text": "FAQ\n\nIs the R Consortium committed to R as an open-source project?\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nWas the R community consulted about the projects considered by the R Consortium?\nWhat kinds of projects will the R Consortium undertake?\nHow are R Consortium projects selected and managed?\nAre the leaders of the R Consortium R users?\nCan I review the governance documents for the R Consortium?\nHow is the R Consortium governed?\nAre membership dues tax-deductible?\nCan an individual become a member of the R Consortium?\nWhy the focus on organizations rather than individuals?\nWhat is the relationship between the R Consortium and the Linux Foundation?\nWhat is the relationship between the R Consortium and the R Foundation?\nWho are the members of the R Consortium?\nWhy an R Consortium?\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nCan I review the governance documents for the R Consortium?\nWhat wouldn’t the R Consortium do?\nWhat kinds of projects will the R Consortium undertake?\nWho will be involved?\n\n\n\nIs the R Consortium committed to R as an open-source project?\nDefinitely! The R Consortium’s explicit mission is to “advance the worldwide promotion of and support for the R open source language”, and all of its activities are in support of the Open Source R Project. It will support and promote the use of Open Source R in all contents, including in commercial and business settings.\nAs defined in its charter (PDF), the projects of the Infrastructure Steering Committee will focus on support of the user base, support of developers, and general advancement of Open Source R. In particular, a commercial fork of R isn’t compatible with that mission, and won’t be a project of the R Consortium.\n\nBack to Top\n\n\n\n\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nNo. The R Consortium welcomes contributions of time, effort and ideas for all passionate users and developers of the R language.\n\nBack to Top\n\n\n\n\nWas the R community consulted about the projects considered by the R Consortium?\nYes. R Consortium projects are proposed by the community to the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nWhat kinds of projects will the R Consortium undertake?\nThe R Consortium will coordinate and support projects that directly benefit stakeholders within the R user community. Here are some examples of the types of projects the R Consortium might undertake\n\nImproving documentation and tools.\nSponsoring and helping execute conferences and events.\nHelping to scale and build out R infrastructure.\nMaintaining an enhanced website focused on the R user community.\n\nThis is not an exhaustive list. Anyone may propose a project to the Infrastructure Steering Committee, which selects and executes projects.\n\nBack to Top\n\n\n\n\nHow are R Consortium projects selected and managed?\nThe technical projects undertaken by the R Consortium in support of the R Project and the R Community are overseen by the Infrastructure Steering Committee. The charter of the Infrastructure Steering Committee (ISC) describes its mission, which is to advance the worldwide promotion of and support for R, and to develop projects, technical and infrastructure collaboration initiatives, support specific initiatives related to R. The membership of the ISC is drawn from the Platinum Members, Silver Members and the R Foundation. As the ISC appoints top-level projects, it is expected that those project leads will join the ISC as voting members.\n\nBack to Top\n\n\n\n\nAre the leaders of the R Consortium R users?\nThe Board Members (including the Chairperson) are appointed or elected by members (depending on the membership class). There is always one board member representing the R Foundation, to provide guidance to the R Consortium in its mission to support the R Project. The remaining Board members are drawn from the membership, and represent the organizations that have joined the R Consortium. All of the current board members have extensive R experience.\nThe members of the Infrastructure Steering Committee are appointed by the Platinum Members, Silver Members, and the R Foundation member, and includes representatives with significant technical experience, including R package developers, community leaders, and the individuals from the R Core Group.\n\nBack to Top\n\n\n\n\nCan I review the governance documents for the R Consortium?\nYes! You can review the by-laws for the R Consortium, Inc. (PDF)and the charter for the Infrastructure Steering Committee (PDF).\n\nBack to Top\n\n\n\n\nHow is the R Consortium governed?\nThe R Consortium is governed by the R Consortium Board of Directors, which is made up of representatives determined by its members. (Members of the board are elected or appointed depending on membership levels; for details please see the by-laws.) The Board meets regularly to manage the business of the Consortium. Meetings are led by the Chairperson of the R Consortium, a rotating position held by a board member elected by the Board as a whole.\nThe technical projects undertaken by the R Consortium in support of the R Project and the R Community are overseen by the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nAre membership dues tax-deductible?\nThe R Consortium is a US-based 501(c)6 non-profit organization. Dues are not tax-deductible as charitable donations by individuals, but under US IRS rules (PDF) may be deductible as trade or business expenses.\n\nBack to Top\n\n\n\n\nCan an individual become a member of the R Consortium?\nYes, individuals may support the R Consortium by joining as a non-voting associate member. You can also support the R project by contributing to the R Foundation directly.\n\nBack to Top\n\n\n\n\nWhy the focus on organizations rather than individuals?\nHundreds of companies around the world have invested heavily in R, by building systems on the R platform and by hiring thousands of R developers. The R Consortium provides a means for those companies to invest in the R Project directly, to collaborate on projects of mutual interest to support the R Community as a whole, and to support the ongoing success of the R Project.\n\nBack to Top\n\n\n\n\nWhat is the relationship between the R Consortium and the Linux Foundation?\nThe R Consortium is an independent organization, but as Collaborative Project of the Linux Foundation, the Linux Foundation provides operational support and guidance.\n\nBack to Top\n\n\n\n\nWhat is the relationship between the R Consortium and the R Foundation?\nThe R Foundation is the leader of the R Project and the custodian of the R source code and copyright. The R Foundation determines the definition and evolution of the R language.\nThe R Consortium, as an independent entity, exists to support the R Community and the R Project as a whole — and that includes providing support to the R Foundation. That’s why the R Foundation has a guaranteed seat on the Board and the Infrastructure Steering Committee, to represent the interests of the R Foundation and to propose projects to support R itself.\n\nBack to Top\n\n\n\n\nWho are the members of the R Consortium?\nMembers of the R Consortium include the following types of organizations (PDF): any association, partnership, organization, governmental agency, company, corporation, academic entity, or non-profit entity with an interest in supporting R. (Individuals may also join as associate members.) In addition, the R Foundation is automatically a member and always has a seat on the Board and the Infrastructure Steering Committee. You can see a current list of members here.\n\nBack to Top\n\n\n\n\nWhy an R Consortium?\nThe R user community has experienced tremendous growth. With growth there is a greater need for cooperation and communication among R users and R stakeholders. R will continually benefit from improvements to its technical tools and resources. The mission of the R Consortium is to help with support and coordination of the important activities of the R Community, via projects selected and executed its Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nDo I have to be an employee of a member of the R Consortium to contribute to infrastructure projects?\nNo! The R Consortium welcomes contributions of time, effort and ideas for all passionate users and developers of the R language. After formal meetings of the Infrastructure Steering Committee have begun (which we anticipate will occur soon), we will distribute information on how project ideas can be submitted to the Infrastructure Steering Committee.\n\nBack to Top\n\n\n\n\nCan I review the governance documents for the R Consortium?\nYes! You can find copies of the by-laws (PDF) for the R Consortium, Inc. and the charter for the infrastructure steering committee.\n\nBack to Top\n\n\n\n\nWhat wouldn’t the R Consortium do?\nInterfere with the R language itself and its development.\n\nBack to Top\n\n\n\n\nWhat kinds of projects will the R Consortium undertake?\nThe R Consortium will coordinate and support projects that directly benefit stakeholders within the R user community, for example:\n\nImproving documentation and tools.\nSponsoring and helping execute conferences and events.\nHelping to scale and build out R infrastructure.\nMaintaining an enhanced website focused on the R user community.\nBack to Top\n\n\n\n\nWho is involved?\nR users and stakeholders as members of the consortium in addition to representatives from the R Foundation with operational support provided by The Linux Foundation.\n\nBack to Top" }, { - "objectID": "webinars/webinars.html#upcoming-webinars", - "href": "webinars/webinars.html#upcoming-webinars", - "title": "Webinars", - "section": "Upcoming Webinars", - "text": "Upcoming Webinars\n\nLearn more: Containerization and R for Reproducibility and More\n\nLearn more: Tidy Finance Webinar Series" + "objectID": "about/contact.html", + "href": "about/contact.html", + "title": "Contact Us", + "section": "", + "text": "Contact Us\nFor general inquiries, membership inquiries, or requests for access to collaborative infrastructure, please feel free to visit our service desk.\nYou can also send us email directly at info@r-consortium.org\nIf you would like information on becoming a member of the R Consortium, please visit the Join page." }, { - "objectID": "webinars/webinars.html#archived-webinars-full-recordings-available", - "href": "webinars/webinars.html#archived-webinars-full-recordings-available", - "title": "Webinars", - "section": "Archived Webinars – Full Recordings Available", - "text": "Archived Webinars – Full Recordings Available\n\nLearn more: Unlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar\n\nLearn more: R/Medicine: Quarto for Reproducible Medical Manuscripts\n\nLearn more: Tidy Finance and Accessing Financial Data\n\nLearn more: Escape the Data Dungeon: Unlock Scalable R Analytics and ML\n\nLearn more: From Vision to Action: The Pfizer R Center of Excellence-led journey to R Adoption\n\nLearn more: R/Insurance Series: For Everyone in Insurance or Actuarial Science\nThe R/Insurance Series is offered four webinars this January. The video recordings of the previous R/Insurance Series webinar, “From Excel to Programming in R,” “From programming in R to putting R into production,” and “R performance culture,” are now available at the link above.\n\nLearn more: R/Medicine Webinar: Visualizing Survival Data with the {ggsurvfit} R Package\n\nLearn more: R/Adoption Series: The Adoption of R in Japan’s Pharma Industry Confirmation\n\nLearn more: R/Adoption Series: R and shiny in regulatory submission\n\nLearn More: R/Adoption Series: Learnings and Reflection from R Validation Case Studies\n\nJuliane Manitz, Senior Expert Biostatistician at EMD Serono\nDoug Kelkhoff, Principal Data Scientist / Statistical Software Engineer at Roche\nUday Preetham Palukuru, Standards lead at Merck & Co.\nEric Milliman, Senior Principal Data Scientist at Biogen\n\n\n\n \n\nLearn More: Teal: An R-Shiny Framework to Unlock the Power of Interactive Data Exploration Chendi Liao, Principal Statistical Programmer Analyst, Roche Canada • Dony Unardi, Principal Data Scientist, Genentech\n\n\n\n \n\nLearn More: R Adoption Series: Introducing the Software Engineering Working Group and {mmrm} Ben Arancibia, Data Scientist – Senior Manager At GSK • Yoni Sidi, Director of Modeling and Simulation at Sage Therapeutics\n\n\n\n\n\n \n\nLearn More: R/Database: Using R at Scale on Database Data \nMark Hornick, Senior Director, Oracle Machine Learning • Sherry LaMonica, Consulting MTS, Oracle Machine Learning\n\n\n\n \n\nLearn More: Upskilling on Data Handling and Communication at Swiss Re \nClaudio T. Rebelo, Model Validation Actuary for Group Risk Management at Swiss Re • Georgios Bakoloukas, Head Model Development & Analytics, Risk Management at Swiss Re • Daniela E. Damm, Divisional Operational Officer for Group Risk Management at Swiss Re\n\n\n\n \n\nLearn More: Using Metadata for Speedy Delivery Re \nChristina Fillmore, Data Scientists and R developer at GSK • Yujie Zhao, is a Senior Scientist (Biostatistics) at Merck & Co., Inc • Keaven Anderson, Scientific Assistant VP of Methodology Research in the Biostatistics and Clinical Research Decision Sciences group at Merck\n\n\n\n \n\nLearn More: Using R in Regulatory Review \nHye Soo Cho, Statistical Analyst, FDA/CDER • Tae Hyun (Ryan) Jung, Ph.D., Senior Statistical Reviewer in FDA/CDER/OTS/OB/DBVI • Paul Schuette, Scientific Computing Coordinator, FDA • Ning Leng, Director, Product Development Data Sciences, Roche • Coline Zeballos, R Strategy Lead, Roche\n\n\n\n \n\nLearn More: Speaking Different Languages \nMichael Rimler, Head of Technical Excellence and Innovation at GlaxoSmithKline • Mike Stackhouse, Chief Innovation Officer at Atorus\n\n\n\n \n\nLearn More: Table Creation in R \nGabriel Becker, Statistical Computing Consultant\n\n\n\n \n\nLearn More: R Management at Roche \nKieran Martin, R Enablement Lead: PD Data Sciences at Roche • Tadeusz Lewandowski, Pan-Pharma collaboration product lead at Roche • Adrian Waddell, Chief Engineer NEST Project\n\n\n\n \n\nLearn More: R Training Strategies at Janssen \nPaulo R. Bargo, Ph.D., Head of R&D Data and Advanced Analytics, Ethicon • Dan Hofstaedter, is a statistical programmer within the Janssen Clinical & Statistical Programming group • Gayathri Kolandaivelu, has over 13 years of experience in the pharmaceutical industry\n\n\n\n \n\nLearn More: Scaling R at GSK \nAndy Nicholls, Head of Data Science within GSK Biostatistics" + "objectID": "about/join.html", + "href": "about/join.html", + "title": "Why Join the R Consortium?", + "section": "", + "text": "The R Consortium is the mechanism for corporate entities and other organizations to support  and engage with the R Community. Membership in the R Consortium signals community leadership, a long term viewpoint, and an appreciation for the efforts of R’s open source contributors. Membership shows commitment and a desire to contribute to the community, strengthening it for the benefit of all.\n\n\n\nHelps fund key R infrastructure such as the R-Hub build system, database interfaces, distributed computing architecture, regional conferences, local R user groups and more.\nProvides a way for companies to generate industry-wide support for projects that they see as valuable.\n\nThe bulk of the R Consortium budget goes directly to funding key community projects.\n\nThrough participation in the R Consortium Infrastructure Steering Committee (ISC), members have a voice in the process of selecting projects and the opportunity to guide their development.\nGives companies direct access to the R Foundation:\n\nBoard members interact with the R Foundation’s representative on the R Consortium Board of Directors.\nISC members:\n\nWork side-by-side with R Foundation members engaged in technical projects,\nParticipate in regular meetings with R Foundation members.\n\n\nProvides insight and access to accurate and up-to-date knowledge about important developments in the the R Community and the extended R ecosystem.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBenefits by member class\nPlatinum\nSilver\n\n\n\n\nOne seat on the Board of Directors with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nOne seat on the ISC with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nElect Silver representatives to the Board and ISC (1 Board seat per 3 Silver members, 1 ISC seat for all Silver members)\n\n\n\nXmark\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nCompany logo on R Consortium website and collateral\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nR Consortium logo on company website\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nMembership dues (annually)\nUS$100,000\n100+ FTE US $25,000 <100 FTE / non-profits, universities US $10,000\n\n\n\n\n\n\n\n\n\n\nReview the Membership Documents.\n\n\nR Consortium Membership Datasheet (PDF)\nR Consortium Bylaws (PDF)\nR Consortium Membership Agreement (PDF)\nR Consortium – Certificate of Incorporation (PDF)\n\n\nFill out our online membership application form.\nRemit the annual dues payment that is applicable for your membership level.\nBegin participating in Events, Discussions, Projects and working Groups.\n\nIf you have questions about membership or joining the R Consortium, please contact our member support desk and you will be contacted as soon as possible. Thank you." }, { - "objectID": "webinars/webinars-auto-not-being-used.html", - "href": "webinars/webinars-auto-not-being-used.html", - "title": "R Consortium", + "objectID": "about/join.html#membership-in-the-r-consortium", + "href": "about/join.html#membership-in-the-r-consortium", + "title": "Why Join the R Consortium?", "section": "", - "text": "Containerization and R for Reproducibility and More\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEscape the Data Dungeon: Unlock Scalable R Analytics and ML\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFrom Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTidy Finance and Accessing Financial Data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nR/Insurance Series: For Everyone in Insurance or Actuarial Science\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nR/Medicine: Quarto for Reproducible Medical Manuscripts\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTidy Finance Webinar Series\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nUnlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWebinars\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNo matching items" + "text": "Helps fund key R infrastructure such as the R-Hub build system, database interfaces, distributed computing architecture, regional conferences, local R user groups and more.\nProvides a way for companies to generate industry-wide support for projects that they see as valuable.\n\nThe bulk of the R Consortium budget goes directly to funding key community projects.\n\nThrough participation in the R Consortium Infrastructure Steering Committee (ISC), members have a voice in the process of selecting projects and the opportunity to guide their development.\nGives companies direct access to the R Foundation:\n\nBoard members interact with the R Foundation’s representative on the R Consortium Board of Directors.\nISC members:\n\nWork side-by-side with R Foundation members engaged in technical projects,\nParticipate in regular meetings with R Foundation members.\n\n\nProvides insight and access to accurate and up-to-date knowledge about important developments in the the R Community and the extended R ecosystem." }, { - "objectID": "blog/how_to_post.html", - "href": "blog/how_to_post.html", - "title": "R Consortium Blog", + "objectID": "about/join.html#how-r-consortium-membership-helps-support-the-r-community", + "href": "about/join.html#how-r-consortium-membership-helps-support-the-r-community", + "title": "Why Join the R Consortium?", "section": "", - "text": "Topic\n\n\n\n\nCloning the Repo\n\n\nInitial Setup\n\n\nInstall R on Linux\n\n\nR Packages Installation Method #1\n\n\nR Packages Installation Method #2\n\n\nInstall the Vscode extension “Quarto”\n\n\nRunning the Project in a Live Preview\n\n\nAdding a Blog post\n\n\nUploading your Post\n\n\n\n\n\n\nOn our GitHub repository, click “Code“ and then “Open with GitHub Desktop”.\n\nIn GitHub Desktop click “Clone”\n\n\n\n\n\nIn Github Desktop click on “Fetch origin” to get the most up to date blog on your local computer.\n\nIn Github Desktop click on “Open in Visual Studio Code” to start working on your blog\n\nIn VSCode click on “View” and then “Terminal”\n\nIn the Vscode Terminal make sure you are on a Linux terminal by switching to Ubuntu (WSL)\n\n\n\n\nInstall R using sudo apt-get install r-base and sudo apt-get install r-base-dev\n\n\n\n\nInstall R packages on Linux; type R in terminal and then install.packages(‘rmarkdown’)\nGGPLOT2 installation: install.packages(“ggplot2”)\ndygraphs installation: install.packages(“dygraphs”)\nhere installation: install.packages(“here”)\n\n\n\n\nUse RStudio Desktop on Windows then click on “install”\n\nSearch for the package you want for example “here” package and click “install”\n\n\n\n\n\n\nRecommended (optional) in the Quarto Extension settings enable the “Render on Save” option\n\n\n\n\n\n\nIn VSCode click on “View” and then “Command Palette”\n\nSearch for “Quarto: Preview” and click on that command\n\n\n\n\n\nIn Github desktop click “Branch” and then “New branch” make a new branch for example “Adding-new-elephant-post”\n\n\nIn VSCode add a new Folder in the “posts” directory and name it. My new post folder is “Slides-Post”\n\nAdd a new index.qmd file (Quarto Markdown File) into the new post folder.\n\nStart editing your new blog post!\n\n\n\nIn Github desktop commit your changes and a short message for your changes, for my example I am committing to the “Add-Slides” branch.\n\nOnce committed, push it to the remote Github Repository. On the bottom left is an indication of a successful commit.\n\nMake a pull request in Github desktop and then 1 reviewer should check the post and make sure it is looking good!\n\n\nClick on “Create pull request” on Github\n\nApproval Process and Timing\n\nEmail info@r-consortium.org" + "text": "Benefits by member class\nPlatinum\nSilver\n\n\n\n\nOne seat on the Board of Directors with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nOne seat on the ISC with full voting rights\n\n\n\nCheck\n\n\n\n\n\n\n\nXmark\n\n\n\n\n\n\nElect Silver representatives to the Board and ISC (1 Board seat per 3 Silver members, 1 ISC seat for all Silver members)\n\n\n\nXmark\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nCompany logo on R Consortium website and collateral\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nR Consortium logo on company website\n\n\n\nCheck\n\n\n\n\n\n\n\nCheck\n\n\n\n\n\n\nMembership dues (annually)\nUS$100,000\n100+ FTE US $25,000 <100 FTE / non-profits, universities US $10,000\n\n\n\n\n\n\n\n\n\n\nReview the Membership Documents.\n\n\nR Consortium Membership Datasheet (PDF)\nR Consortium Bylaws (PDF)\nR Consortium Membership Agreement (PDF)\nR Consortium – Certificate of Incorporation (PDF)\n\n\nFill out our online membership application form.\nRemit the annual dues payment that is applicable for your membership level.\nBegin participating in Events, Discussions, Projects and working Groups.\n\nIf you have questions about membership or joining the R Consortium, please contact our member support desk and you will be contacted as soon as possible. Thank you." }, { - "objectID": "blog/how_to_post.html#cloning-the-repo", - "href": "blog/how_to_post.html#cloning-the-repo", - "title": "R Consortium Blog", + "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html", + "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html", + "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", "section": "", - "text": "On our GitHub repository, click “Code“ and then “Open with GitHub Desktop”.\n\nIn GitHub Desktop click “Clone”" + "text": "Slides available here:\nQuarto Manuscript\nGithub – Quarto Manuscript\nManuscript:\nmine-cetinkaya-rundel.github.io/indo-rct\ngithub.com/mine-cetinkaya-rundel/indo-rct" }, { - "objectID": "blog/how_to_post.html#initial-setup", - "href": "blog/how_to_post.html#initial-setup", - "title": "R Consortium Blog", - "section": "", - "text": "In Github Desktop click on “Fetch origin” to get the most up to date blog on your local computer.\n\nIn Github Desktop click on “Open in Visual Studio Code” to start working on your blog\n\nIn VSCode click on “View” and then “Terminal”\n\nIn the Vscode Terminal make sure you are on a Linux terminal by switching to Ubuntu (WSL)\n\n\n\n\nInstall R using sudo apt-get install r-base and sudo apt-get install r-base-dev\n\n\n\n\nInstall R packages on Linux; type R in terminal and then install.packages(‘rmarkdown’)\nGGPLOT2 installation: install.packages(“ggplot2”)\ndygraphs installation: install.packages(“dygraphs”)\nhere installation: install.packages(“here”)\n\n\n\n\nUse RStudio Desktop on Windows then click on “install”\n\nSearch for the package you want for example “here” package and click “install”\n\n\n\n\n\n\nRecommended (optional) in the Quarto Extension settings enable the “Render on Save” option" + "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#summary", + "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#summary", + "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", + "section": "Summary ", + "text": "Summary \nIn this talk, Mine Cetinkaya-Rundel, Professor of the Practice of Statistical Science at Duke University,  presents a new capability in Quarto that provides a straightforward and user-friendly approach to creating reproducible manuscripts that are publication-ready for submission to science journals. \nThis new feature, Quarto manuscripts, includes the ability to produce a bundled output containing a standardized journal format, source documents, source computations, referenced resources, and execution information into a single bundle that be ingested into journal review and production processes. \nIn this talk, we’ll demo how Quarto manuscripts work and how you can incorporate them into your current manuscript development process as well as touch on pain points in your current workflow that Quarto manuscripts help alleviate." }, { - "objectID": "blog/how_to_post.html#running-the-project-in-a-live-preview", - "href": "blog/how_to_post.html#running-the-project-in-a-live-preview", - "title": "R Consortium Blog", - "section": "", - "text": "In VSCode click on “View” and then “Command Palette”\n\nSearch for “Quarto: Preview” and click on that command" + "objectID": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#speaker", + "href": "webinars/r-medicine-quarto-for-reproducible-medical-manuscripts.html#speaker", + "title": "R/Medicine: Quarto for Reproducible Medical Manuscripts", + "section": "Speaker", + "text": "Speaker\n\n\n\n\n\nMine Çetinkaya-Rundelis, is Professor of the Practice of Statistical Science and the Director of Undergraduate Studies in the Department of Statistical Science, as well as an affiliated faculty member in the Computational Media, Arts, and Cultures program at Duke University. Her work is dedicated to advancing innovation in statistics and data science pedagogy, focusing particularly on computing, reproducible research, student-centered learning, and open-source education. She emphasizes integrating computation into the undergraduate statistics curriculum, employing reproducible research methodologies, and analyzing real and complex datasets. In Spring 2024, she will be teaching STA 199 – Introduction to Data Science and Statistical Thinking, along with STA 313 – Advanced Data Visualization. Further details about her work can be explored below, or she can be found on Mastodon and Bluesky." }, { - "objectID": "blog/how_to_post.html#adding-a-blog-post", - "href": "blog/how_to_post.html#adding-a-blog-post", - "title": "R Consortium Blog", - "section": "", - "text": "In Github desktop click “Branch” and then “New branch” make a new branch for example “Adding-new-elephant-post”\n\n\nIn VSCode add a new Folder in the “posts” directory and name it. My new post folder is “Slides-Post”\n\nAdd a new index.qmd file (Quarto Markdown File) into the new post folder.\n\nStart editing your new blog post!\n\n\n\nIn Github desktop commit your changes and a short message for your changes, for my example I am committing to the “Add-Slides” branch.\n\nOnce committed, push it to the remote Github Repository. On the bottom left is an indication of a successful commit.\n\nMake a pull request in Github desktop and then 1 reviewer should check the post and make sure it is looking good!\n\n\nClick on “Create pull request” on Github\n\nApproval Process and Timing\n\nEmail info@r-consortium.org" + "objectID": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#summary", + "href": "webinars/from-vision-to-action-the-pfizer-r-center-of-excellence.html#summary", + "title": "From Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption", + "section": "Summary", + "text": "Summary\nThe webinar by the R consortium titled “From Vision to Action: The R Pfizer R Center of Excellence-led Journey to R Adoption” was not just a case study of Pfizer’s journey. It was a platform for sharing valuable insights and strategies applicable across industries and experience levels. Viewers can learn about the importance of an engaged R community and practical approaches to building and maintaining such a community within their organizations." }, { - "objectID": "all-projects/callforproposals.html", - "href": "all-projects/callforproposals.html", - "title": "The 2024 ISC Grant Program", - "section": "", - "text": "A major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nTechnical Infrastructure projects that have be funded include:\n\nR-hub, a centralized tool for checking R packages\nTesting DBI and improving key open source database backends.\nImprovements in packages such as mapview and sf\nImproving Translations in R\nOngoing infrastructural development for R on Windows and macOS\n\nSocial Infrastructure projects include:\n\nSatRDays, bootstrapping a system for local R conferences.\nData-Driven Discovery and Tracking of R Consortium Activities\n\nThe Infrastructure Steering Committee (ISC) projects should have a focus on technical infrastructure or involve software development to support social infrastructure. Conferences, training sessions, and user groups will be funded through the RUGS program.\nTo apply for an ISC grant please continue with the instructions below. To seek funding for a conference, training session or user group please apply through the RUGS program page.\n\n\nThe ISC is interested in projects that:\n\nAre likely to have a broad impact on the R community.\nHave a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it up into smaller chunks (a good example of this done is with the DBI/DBItest project submission, where multiple proposals came in over time to address the various needs).\nHave a low-to-medium risk with a low-to-medium reward. The ISC tends not fund high-risk, high-reward projects.\n\nWhile all projects are considered, the ISC generally does not accept projects that:\n\nImpact only a small part of the R community\nRequest conference, workshop, or meetup sponsorship. For these, you should look at our user group program or connect with the marketing committee for larger events.\nAre very exploratory. These are better to be pursued through the working group program.\n\n\n\n\nPlease provide a 2 to 5 page proposal that describes the problem you want to solve. We expect submissions to include these components:\n\nThe Problem: What problem do you want to solve? Why is it a problem? Who does it affect? What will solving the problem enable? This section should include a brief summary of existing work, such as R packages that may be relevant. If you are proposing a change to R itself, you must include a letter of support from a member of R Core.\nThe Plan: How are you going to solve the problem? Include the concrete actions you will take and an estimated timeline. What are likely failure modes and how will you recover from them?\nThe Team: Who will work on the project? Briefly describe all participants, and the skills they will bring to the project.\nProject Milestones: Outline the milestones for development and how much funding will be required for each stage (as payments will be tied to project milestone completion). Each milestone should specify the work to be done and the expected outcomes, providing enough detail for the ISC to understand the scope of the project work and assess the likelihood of success.\nHow Can The ISC Help: Please describe how you think the ISC can help. If you are looking for a cash grant include a detailed itemized budget and spending plan. We expect that most of the budget will be allocated for labor costs. We do not cover indirect costs. The ISC grants cannot cover such things as travel, lodging, food, journal publication fees, or personal hardware. Cloud services may be covered if they are specific to the project and the project period. The ISC reserves the right to vet how funds are used for each project separately. If in doubt, please reach out to us. If you are seeking to start an ISC working group, then please describe the goals of the group and provide the name of the individual who will be committed to leading and managing the group’s activities. Also, describe how you think the ISC can help promote your project.\nDissemination: How will you ensure that your work is available to the widest number of people? Please specify the open-source or creative commons license(s) you will use, how you will host your code so that others can contribute, and how you will publicize your work. We encourage you to plan content to be shared quarterly on the R Consortium blog.\n\nThe ISC has a limited grant budget, and we want to ensure that funded projects deliver the maximum benefit to the community. Successful proposals show well-defined milestones, with initial work completed to minimize delivery risk, e.g., upfront research and well-defined action plans.\nIf you would like a template to help you structure your proposal, we encourage you to use one contributed by Steph Locke at https://github.com/RConsortium/isc-proposal.\nWe encourage you to seek feedback from the community before formally submitting your proposal. You are welcome to email individual committee members who might be particularly interested in your proposal to get their informal opinion, and you may want to publicize it more widely to get feedback from the broader R community.\n\n\n\nOnce you have completed your proposal, create a self-contained PDF and complete this form (requires signing in via a Google Account). When you submit the form, you should see a response page saying “Thank you for your proposal!” Soon thereafter, you will receive an email from forms-receipts-noreply@google.com with all the details of your submission. If you do not receive that email, please be sure to check your spam folder. If you do not see it, reach out to us as soon as possible.\nPlease note that the R Consortium utilizes a standard agreement for all funded projects selected in an effort to streamline the award process and to fund the greatest amount of projects as possible. The standard agreement is available for review in advance: Individual Consultant Agreement for R Consortium ISC Projects – 20170622.\nIf you have any questions please email proposal@r-consortium.org.\n\n\n\n\n\n\nMarch 1, 2024 – Grant Application period opens\nApril 1, 2024 – Grant Application period closes, 11:59pm US ET\nMay 1, 2024 – All accepted grantees are contacted by the ISC\nJune 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nSeptember 1, 2024 – Grant Application period opens\nOctober 1, 2024 – Grant Application period close, 11:59pm US ET\nNovember 1, 2024 – All accepted grantees are contacted by the ISC\nDecember 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nAll proposals will be read and reviewed by the Chair of the ISC and assigned to a committee member for detailed review. Proposals will be reviewed as a group, and you will be notified of the decision by the dates listed above.\n50% of the grant will be paid out when the contract is signed and 50% upon completion.\nAll accepted projects will be published on the R Consortium blog.\nWe review this process yearly to ensure that the process is as smooth as possible, and to incorporate the knowledge gained from putting it into practice. 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Watch our in-depth Oracle Machine Learning for R (OML4R) webinar to learn more!\nKey topics included:\n\nSeamless In-Database Access: Jump straight into your data without the drag of extractions.\nScalable High-Performance Data Processing: Handle huge datasets effortlessly.\nIntegrated In-Database ML: Develop and deploy potent models right within your database.\nEffortless Production Deployment: Streamline your R scripts from development to production.\n\nFound out more about OML4R through practical examples in product bundling, demand forecasting, and customer churn prediction. Escape the data grind and transformed your R experience." + }, + { + "objectID": "webinars/escape-the-data-dungeon.html#speaker", + "href": "webinars/escape-the-data-dungeon.html#speaker", + "title": "Escape the Data Dungeon: Unlock Scalable R Analytics and ML", + "section": "Speaker", + "text": "Speaker\n\n\nMark Hornick, Senior Director, Oracle Machine Learning\nMark Hornick is senior director of product management for Oracle Machine Learning. Mark has more than 20 years of experience integrating and leveraging machine learning with Oracle software as well as working with internal and external customers to apply Oracle’s machine learning technologies. He has been involved with R technology for the past 15 years.  Mark is Oracle’s representative to the R Consortium and is an Oracle Adviser of the Analytics and Data Oracle User Community. He has been issued seven US patents. Mark holds a bachelor’s degree from Rutgers University and a master’s degree from Brown University, both in computer science. Follow him on Twitter @MarkHornick and connect on LinkedIn.\n\n\n\nSherry LaMonica, Consulting MTS, Oracle Machine Learning\nSherry is a member of the Oracle Machine Learning Product Management team. She has 20 years of software experience focused on enabling the commercial use of the open-source data analysis software systems with R and Python for data science and machine learning projects. 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If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at info@r-consortium.org." + }, + { + "objectID": "webinars/containerization-and-r-for-reproducibility.html#abstract", + "href": "webinars/containerization-and-r-for-reproducibility.html#abstract", + "title": "Containerization and R for Reproducibility and More", + "section": "Abstract", + "text": "Abstract\nContainerization has become a dominant computing paradigm for computing in the past decade due to its many advantages: isolation and security, scalability and efficiency with lightweight containers sharing an operating kernel and resources, and portability across cloud computing providers. For the researcher, analyst, or R user, containers have applications ranging from reproducible analytical environments to packaging statistical code to use in web applications. I will discuss how biomedical researchers can make use of containerization technology, particularly the tools provided by the Rocker Project, which publishes powerful standardized containers for the R language.\n\nRegister here: https://zoom.us/webinar/register/WN_aWMKlQngTUqgp4G_qkkD_g" + }, + { + "objectID": "webinars/containerization-and-r-for-reproducibility.html#speaker", + "href": "webinars/containerization-and-r-for-reproducibility.html#speaker", + "title": "Containerization and R for Reproducibility and More", + "section": "Speaker", + "text": "Speaker\n\nNoam Ross is a computational disease ecologist and Executive Director of rOpenSci, a nonprofit dedicated to promoting open science and validating data science and computational methods. He is a core member of the Rocker Project, which maintains standardized containers for the R computer language. Noam’s work includes spearheading rOpenSci’s work in software peer review, developing a widely emulated system for leveraging the academic peer-review process coupled with state-of-the art automated code analysis to improve code quality in the scientific software in ecosystem, as well as using review as a mechanism for community building and training. His research interests and contributions span a wide range of topics, including disease ecology, zoonotic spillover, mechanistic modeling of disease dynamics, and non-parametric data science methods. His applied work includes creating early outbreak assessment models for the U.S. Defense Threat Reduction Agency, and modeling and forecasting for New York State’s COVID-19 emergency response. Noam holds a Ph.D. in theoretical ecology from the University of California-Davis and a B.Sc. from Brown University." + }, + { + "objectID": "webinars/unlocking-insights-from-latinr.html#date-and-time-october-22-2024-9am-pacific-time", + "href": "webinars/unlocking-insights-from-latinr.html#date-and-time-october-22-2024-9am-pacific-time", + "title": "Unlocking Insights from LatinR: Collaboration and Innovation in Data Science Webinar", + "section": "Date and time: October 22, 2024, 9am Pacific time", + "text": "Date and time: October 22, 2024, 9am Pacific time\nJoin us for an exciting webinar featuring the co-founders and co-chair of LatinR, as they share insights into the vibrant R community in Latin America and the evolution of the LatinR conference over its past six editions. Discover the impact this conference has had on the regional and global R community, learn about the unique aspects of R usage in Latin America, and get a sneak peek into what to expect at the upcoming LatinR 2024 edition. 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She is one of the co-founders and chairs of LatinR. She is also the rOpenSci Community Manager and part of the R-Ladies Leadership Team. She has 30 years of experience in education and 24 years as a researcher.\n\n\nNatalia Da Silva\n\nNatalia is an Assistant Professor of Statistics at Universidad de la República in Montevideo, Uruguay, with a Ph.D. in Statistics from Iowa State University, whose research focuses on supervised learning, exploratory data analysis, statistical graphics, and reproducible research, and who co-founded LatinR, R-Ladies Montevideo, and the Montevideo R User Group (GURU), while also serving as an Associate Editor for Reproducibility at the Journal of the American Statistical Association.\n\n\nRiva Quiroga\n\nRiva Quiroga is a Linguist based in Valparaíso, Chile. 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Briefly describe all participants, and the skills they will bring to the project.\nProject Milestones: Outline the milestones for development and how much funding will be required for each stage (as payments will be tied to project milestone completion). Each milestone should specify the work to be done and the expected outcomes, providing enough detail for the ISC to understand the scope of the project work and assess the likelihood of success.\nHow Can The ISC Help: Please describe how you think the ISC can help. If you are looking for a cash grant include a detailed itemized budget and spending plan. We expect that most of the budget will be allocated for labor costs. We do not cover indirect costs. The ISC grants cannot cover such things as travel, lodging, food, journal publication fees, or personal hardware. Cloud services may be covered if they are specific to the project and the project period. The ISC reserves the right to vet how funds are used for each project separately. If in doubt, please reach out to us. If you are seeking to start an ISC working group, then please describe the goals of the group and provide the name of the individual who will be committed to leading and managing the group’s activities. Also, describe how you think the ISC can help promote your project.\nDissemination: How will you ensure that your work is available to the widest number of people? Please specify the open-source or creative commons license(s) you will use, how you will host your code so that others can contribute, and how you will publicize your work. We encourage you to plan content to be shared quarterly on the R Consortium blog.\n\nThe ISC has a limited grant budget, and we want to ensure that funded projects deliver the maximum benefit to the community. Successful proposals show well-defined milestones, with initial work completed to minimize delivery risk, e.g., upfront research and well-defined action plans.\nIf you would like a template to help you structure your proposal, we encourage you to use one contributed by Steph Locke at https://github.com/RConsortium/isc-proposal.\nWe encourage you to seek feedback from the community before formally submitting your proposal. You are welcome to email individual committee members who might be particularly interested in your proposal to get their informal opinion, and you may want to publicize it more widely to get feedback from the broader R community." + "text": "The R Consortium blog will serve as a channel for the members, ISC grant recipients and the community at large to broadcast to a wide audience how their work and engagement is growing opportunities for the R language for data science and statistical computing.\nThis may include summaries of how leading institutions, companies and developers are using, developing and advancing R.\nThose involved with developing, maintaining, distributing, and using R software are encouraged to contribute to the blog.\nGuest posts from the R Consortium community at large or projects funded by the ISC that enhance R and support users are welcomed. Updates about R-related conferences (including useR!), meetings (including SatRDays and RLadies), local user groups worldwide, new working groups or programs for R language certification and training are of interest. Other topics would certainly be considered, but it should be something of interest to the broader R community.\nAccepted blog posts are at the sole discretion of the R Consortium." }, { - "objectID": "all-projects/callforproposals.html#how-to-apply", - "href": "all-projects/callforproposals.html#how-to-apply", - "title": "The 2024 ISC Grant Program", + "objectID": "blog/guidelines.html#r-consortium-blog-overview", + "href": "blog/guidelines.html#r-consortium-blog-overview", + "title": "Blog Guidelines", "section": "", - "text": "Once you have completed your proposal, create a self-contained PDF and complete this form (requires signing in via a Google Account). When you submit the form, you should see a response page saying “Thank you for your proposal!” Soon thereafter, you will receive an email from forms-receipts-noreply@google.com with all the details of your submission. If you do not receive that email, please be sure to check your spam folder. If you do not see it, reach out to us as soon as possible.\nPlease note that the R Consortium utilizes a standard agreement for all funded projects selected in an effort to streamline the award process and to fund the greatest amount of projects as possible. The standard agreement is available for review in advance: Individual Consultant Agreement for R Consortium ISC Projects – 20170622.\nIf you have any questions please email proposal@r-consortium.org." + "text": "The R Consortium blog will serve as a channel for the members, ISC grant recipients and the community at large to broadcast to a wide audience how their work and engagement is growing opportunities for the R language for data science and statistical computing.\nThis may include summaries of how leading institutions, companies and developers are using, developing and advancing R.\nThose involved with developing, maintaining, distributing, and using R software are encouraged to contribute to the blog.\nGuest posts from the R Consortium community at large or projects funded by the ISC that enhance R and support users are welcomed. Updates about R-related conferences (including useR!), meetings (including SatRDays and RLadies), local user groups worldwide, new working groups or programs for R language certification and training are of interest. Other topics would certainly be considered, but it should be something of interest to the broader R community.\nAccepted blog posts are at the sole discretion of the R Consortium." }, { - "objectID": "all-projects/callforproposals.html#proposal-dates-for-2024", - "href": "all-projects/callforproposals.html#proposal-dates-for-2024", - "title": "The 2024 ISC Grant Program", + "objectID": "blog/guidelines.html#quality", + "href": "blog/guidelines.html#quality", + "title": "Blog Guidelines", + "section": "Quality", + "text": "Quality\nWe are looking for posts that teach and give value to our community. Blogs should include the meta-narrative that “R is a fast-growing language for statistical computing and graphics” and “the R Consoritum supports the worldwide community of users, maintainers and developers of R software.”\nGuest posts must be vendor neutral, though it may mention vendors involved in specific deployment or adoption paths, or their hosting of an in-person event or speaking at an event, or other indications of meaningful participation in the community. It shouldn’t feel like an advertisement for your product, services or company though. Your post must be your content, but can be published elsewhere on the Internet with permission from that website. All content should have a byline (preferably by a company engineer) and be published under Creative Commons with Attribution, so you’re welcome to re-publish on your own blog.\nThe most interesting posts are those that teach or show how to do something in a way maybe others haven’t thought of. Good blog posts show hurdles that were encountered and explain how they were overcome (not that everything is rainbows and unicorns). When showing upstreaming of a patch fixing an issue for others, link back to the Github issue, so readers can follow along. We don’t avoid critical commentary or broad issues, but approach them with sensitivity, professionalism and tact in a way that is beneficial and positive for the community. It would be helpful to the R Consortium to discuss how to choose between different technologies and how to accommodate different legacy issues and cloud platforms.\nBe interesting and inspiring!" + }, + { + "objectID": "blog/guidelines.html#promotion", + "href": "blog/guidelines.html#promotion", + "title": "Blog Guidelines", + "section": "Promotion", + "text": "Promotion\nYour blog will be shared on R Consortium’s Twitter channel. Please feel free to retweet or share. Don’t forget to share your work on your own social channels and favorite news aggregator sites. Suggested sites: Twitter, LinkedIn, Reddit, Hacker News, DZone, TechBeacon. Plus industry sites like: https://www.r-bloggers.com/about/, rweekly.org and reddit.com/r/rstats." + }, + { + "objectID": "blog/guidelines.html#how-to-submit-for-consideration", + "href": "blog/guidelines.html#how-to-submit-for-consideration", + "title": "Blog Guidelines", + "section": "How to submit for consideration", + "text": "How to submit for consideration\nPlease submit the blog post or a brief summary and the topic of the post to r-marketing@lists.r-consortium.org (with the Subject line: “Proposed Blog: BLOG TITLE”) for consideration. The PR team will review your submission in a timely manner and provide the green light to draft the entire article or provide feedback on next steps. If you are submitting an article or presentation that already exists, please send it in its entirety with a note on the expressed permission from the owner of content. Once your submission has been approved, it will be added to our blog publishing calendar and a publish date will be provided, so you may plan to promote accordingly through your personal and company social media channels. Blog posts should be no longer than 1,000 words and no shorter than 300 words. Diagrams, code examples or photos are strongly encouraged.\nThis document last updated July 17, 2024" + }, + { + "objectID": "blog/index.html", + "href": "blog/index.html", + "title": "R Consortium", "section": "", - "text": "March 1, 2024 – Grant Application period opens\nApril 1, 2024 – Grant Application period closes, 11:59pm US ET\nMay 1, 2024 – All accepted grantees are contacted by the ISC\nJune 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\n\n\n\n\nSeptember 1, 2024 – Grant Application period opens\nOctober 1, 2024 – Grant Application period close, 11:59pm US ET\nNovember 1, 2024 – All accepted grantees are contacted by the ISC\nDecember 1, 2024 – Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter." + "text": "Want to contribute to the R Consortium blog? Please review our Blog Post Guidelines.\nR Consortium blog archive (2015-2024)\n\n\n\n\n\n\n \n \n \n Order By\n Default\n \n Date - Oldest\n \n \n Date - Newest\n \n \n Title\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n\nDate\n\n\nTitle\n\n\nAuthor\n\n\n\n\n\n\nNov 1, 2024\n\n\nReviving Sheffield R User Group and Building Tools for Thyroid Cancer Prediction\n\n\nR Consortium\n\n\n\n\nOct 30, 2024\n\n\nStreamlining API Integration: Jon Harmon’s Journey with the api2r Package\n\n\nR Consortium\n\n\n\n\nOct 23, 2024\n\n\nConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers\n\n\nR Consortium\n\n\n\n\nOct 18, 2024\n\n\nEndophytes, Oaks, and R: How R-Ladies Morelia is Cultivating Science and Community in Morelia, Mexico\n\n\nR Consortium\n\n\n\n\nOct 16, 2024\n\n\nThe U.S. Federal Reserve quarterly model in R\n\n\nGuest Blog Post\n\n\n\n\nOct 15, 2024\n\n\nEmpowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative\n\n\nR Consortium\n\n\n\n\nOct 14, 2024\n\n\nR/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track\n\n\nR Consortium\n\n\n\n\nOct 9, 2024\n\n\nUsing R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research\n\n\nR Consortium\n\n\n\n\nOct 8, 2024\n\n\nCakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group\n\n\nR Consortium\n\n\n\n\nOct 1, 2024\n\n\nAnnouncing the Health Technology Assessment (HTA) Working Group\n\n\nR Consortium\n\n\n\n\nSep 23, 2024\n\n\nUnlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research\n\n\nR Consortium\n\n\n\n\nSep 20, 2024\n\n\nFree Boba Tea and Technical R Topics Lure Young Learners to New Brunei R User Group\n\n\nR Consortium\n\n\n\n\nSep 12, 2024\n\n\nEmpowering Data Science: How R is Transforming Research in Cameroon\n\n\nR Consortium\n\n\n\n\nSep 10, 2024\n\n\nThank You, Joseph Rickert: A Legacy of Leadership and Innovation in the R Community\n\n\nR Consortium\n\n\n\n\nSep 6, 2024\n\n\nR-Ladies Bariloche in Argentina: Fostering a Different Approach to Leadership\n\n\nR Consortium\n\n\n\n\nAug 30, 2024\n\n\nThe 2024 ISC Grant Program will begin Accepting Applications Soon!\n\n\nR Consortium\n\n\n\n\nAug 27, 2024\n\n\nR4SocialScience: Empowering Social Science Research with R in India\n\n\nR Consortium\n\n\n\n\nAug 26, 2024\n\n\nNews from R Submissions Working Group – Pilot 3 Successfully Reviewed by FDA\n\n\nR Consortium\n\n\n\n\nAug 20, 2024\n\n\nBuilding Bridges in Haifa, Israel: How the New R User Group in Haifa is Establishing a Diverse R Community\n\n\nR Consortium\n\n\n\n\nAug 12, 2024\n\n\nA New R Community in Ahmedabad, India, focused on Clinical Research and Pharmaceutical Industries\n\n\nR Consortium\n\n\n\n\nAug 2, 2024\n\n\nR Consortium Grants Committee Announces New Chair\n\n\nR Consortium\n\n\n\n\nAug 1, 2024\n\n\nPharma RUG: The Rise of R in China’s Pharmaceutical Industry\n\n\nR Consortium\n\n\n\n\nJul 26, 2024\n\n\nR-Ladies Rome: Empowering Women in Data Science Through Collaboration and Innovation\n\n\nR Consortium\n\n\n\n\nJul 22, 2024\n\n\nEmpowering the R Community: Insights from Myles Mitchell of the Leeds Data Science Group\n\n\nR Consortium\n\n\n\n\nJul 12, 2024\n\n\nKolkata R User Group: A Rich History with Statistics\n\n\nR Consortium\n\n\n\n\nJul 3, 2024\n\n\nDiving into R with Isabella Velasquez: Perspectives from R-Ladies Seattle\n\n\nR Consortium\n\n\n\n\nJul 2, 2024\n\n\nR Consortium’s Submission Working Group: Advancing R for Regulatory Success at PharmaSUG 2024\n\n\nR Consortium\n\n\n\n\nJun 25, 2024\n\n\nR Addicts Paris: Promoting Diversity in R\n\n\nR Consortium\n\n\n\n\nJun 24, 2024\n\n\nThe Crucial Role of Release Control in R for Healthcare Organizations\n\n\nGuest Blog Post\n\n\n\n\nJun 17, 2024\n\n\nBridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students\n\n\nR Consortium\n\n\n\n\nJun 11, 2024\n\n\nKeith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R\n\n\nR Consortium\n\n\n\n\nJun 4, 2024\n\n\nFull-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks\n\n\nR Consortium\n\n\n\n\nMay 30, 2024\n\n\nR4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions\n\n\nR Consortium\n\n\n\n\nMay 29, 2024\n\n\nEnhancing Clinical Trial Data Sharing with R Consortium’s R Submissions Working Group\n\n\nR Consortium\n\n\n\n\nMay 29, 2024\n\n\nOne More Step Forward: The R Consortium Submission Working Group’s Presentation to Swissmedic on Regulatory Submission using R and Shiny\n\n\nGuest Authors\n\n\n\n\nMay 24, 2024\n\n\nCollaborative Growth: The Botswana R User Group and Regional Partnerships\n\n\nR Consortium\n\n\n\n\nMay 16, 2024\n\n\nGergely Daróczi’s Journey: Empowering R Users in Hungary\n\n\nR Consortium\n\n\n\n\nMay 15, 2024\n\n\nEnhancing R: The Vision and Impact of Jan Vitek’s MaintainR Initiative\n\n\nR Consortium\n\n\n\n\nMay 14, 2024\n\n\nTackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research\n\n\nR Consortium\n\n\n\n\nMay 13, 2024\n\n\nThe Evolution of Melbourne’s Business Analytics and R Business User Group\n\n\nR Consortium\n\n\n\n\nApr 30, 2024\n\n\nR/Medicine is coming June 10-14, 2024 – See Top Five R Medicine Talks from Previous Years\n\n\nR Consortium\n\n\n\n\nApr 26, 2024\n\n\nBridging Gaps: Tunis R User Group’s Journey in Democratizing R in Bioinformatics\n\n\nR Consortium\n\n\n\n\nApr 19, 2024\n\n\nNavigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors\n\n\nR Consortium\n\n\n\n\nApr 18, 2024\n\n\nBuilding Data Highways: Kirill Müller’s Journey in Enhancing R’s Database\n\n\nR Consortium\n\n\n\n\nApr 15, 2024\n\n\nDecade of Data: Celebrating 10 Years of Innovation at the New York R Conference\n\n\nR Consortium\n\n\n\n\nApr 10, 2024\n\n\nThe Impact of R on Academic Excellence in Manchester, UK\n\n\nR Consortium\n\n\n\n\nApr 8, 2024\n\n\nEARL Early Bird Tickets Are Now Available!\n\n\nR Consortium\n\n\n\n\nApr 5, 2024\n\n\nR/Medicine Coming June 10-14, 2024 – Call for Abstracts Open – Keynotes Announced\n\n\nR Consortium\n\n\n\n\nApr 4, 2024\n\n\nUnlocking Financial Insights: Join Us at the R Finance Conference\n\n\nR Consortium\n\n\n\n\nMar 28, 2024\n\n\nEmpowering R Enthusiasts: SatRDays London 2024 Unveiled\n\n\nR Consortium\n\n\n\n\nMar 27, 2024\n\n\nAligning Beliefs and Profession: Using R in Protecting the Penobscot Nation’s Traditional Lifeways\n\n\nR Consortium\n\n\n\n\nMar 26, 2024\n\n\nElevate Your R Community with the 2024 RUGS Grant Program\n\n\nR Consortium\n\n\n\n\nMar 19, 2024\n\n\nOffa R Users Group: Empowering Data-Driven Education in Nigeria\n\n\nR Consortium\n\n\n\n\nMar 13, 2024\n\n\nR-Ladies Goiânia: Promoting Diversity and Inclusion in Local R Community\n\n\nR Consortium\n\n\n\n\nMar 12, 2024\n\n\nISC-funded Grant: Secure TLS Connections in {nanonext} and {mirai} Facilitating High-Performance Computing in the Life Sciences\n\n\nR Consortium\n\n\n\n\nMar 7, 2024\n\n\nThe Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics\n\n\nR Consortium\n\n\n\n\nMar 1, 2024\n\n\nApply Now! R Consortium Infrastructure Steering Committee (ISC) Grant Program Open for Proposals!\n\n\nR Consortium\n\n\n\n\nFeb 28, 2024\n\n\nThe R Consortium 2023: A Year of Growth and Innovation\n\n\nR Consortium\n\n\n\n\nFeb 27, 2024\n\n\nMoffitt Cancer Center Bio-Data Club’s New Chapter in Spatial Data Analysis and Enhanced Hackathon Collaboration\n\n\nR Consortium\n\n\n\n\nFeb 23, 2024\n\n\nRecap: R Validation Hub Community Meeting\n\n\nR Consortium\n\n\n\n\nFeb 21, 2024\n\n\nJoin our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts\n\n\nR Consortium\n\n\n\n\nFeb 20, 2024\n\n\nR-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women\n\n\nR Consortium\n\n\n\n\nFeb 14, 2024\n\n\nUnlocking the Power of R for Insurance and Actuarial Science: Webinar Series Recap\n\n\nR Consortium\n\n\n\n\nFeb 13, 2024\n\n\nAnn Arbor R User Group: Harnessing the Power of R and GitHub\n\n\nR Consortium\n\n\n\n\nFeb 12, 2024\n\n\nUnraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024\n\n\nR Consortium\n\n\n\n\nFeb 8, 2024\n\n\nR Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!\n\n\nR Consortium\n\n\n\n\nFeb 7, 2024\n\n\nImproving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade\n\n\nR Consortium\n\n\n\n\nFeb 6, 2024\n\n\nJoin Our Upcoming Webinar: Master Tidy Finance & Access Financial Data with Expert Christoph Scheuch\n\n\nR Consortium\n\n\n\n\nFeb 2, 2024\n\n\nNatalia Andriychuk on RUGs, Pfizer R Center of Excellence, and Open Source Projects: Fostering R Communities Inside and Out\n\n\nR Consortium\n\n\n\n\n\nNo matching items" }, { - "objectID": "all-projects/callforproposals.html#the-process", - "href": "all-projects/callforproposals.html#the-process", - "title": "The 2024 ISC Grant Program", + "objectID": "all-projects/2021-group-2.html", + "href": "all-projects/2021-group-2.html", + "title": "R Consortium", "section": "", - "text": "All proposals will be read and reviewed by the Chair of the ISC and assigned to a committee member for detailed review. Proposals will be reviewed as a group, and you will be notified of the decision by the dates listed above.\n50% of the grant will be paid out when the contract is signed and 50% upon completion.\nAll accepted projects will be published on the R Consortium blog.\nWe review this process yearly to ensure that the process is as smooth as possible, and to incorporate the knowledge gained from putting it into practice. All decisions to accept or reject proposals will be made by R Consortium in its sole discretion and shall be final.\nIf you have any questions about the proposals or submission process write to proposal@r-consortium.org." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n\n\n\nFunded:\n$17,000\nProposed by:\nEdzer Pebesma\nSummary:\nThe retirement of rgdal, rgeos, and maptools presents a significant impact on the CRAN community, these packages are scheduled for retirement by the end of 2023. In response, a proposal for an ISC Funded project has been put forward to tackle this challenge. Preparing CRAN for the Retirement of rgdal, rgeos and maptools focuses on finding suitable alternatives for the functionalities offered by the retiring packages and providing guidance to package maintainers on necessary adjustments and migration steps. By doing so, it aims to minimize disruption to CRAN packages and existing R scripts, ensuring the overall stability and robustness of the CRAN ecosystem. The retirement process will simplify the maintenance of the “R Spatial stack” and contribute to the long-term health of the CRAN ecosystem.\n\n\n\nFunded:\n$4,840\nProposed by:\nLampros Mouselimis\nSummary:\nR Package for the ICESat-2 Altimeter Data aims to create an R package specifically designed for accessing ICESat-2 satellite data through the OpenAltimetry API. Addressing the lack of existing R packages for downloading geospatial data in specific formats, the package will enable R users to download ICESat-2 data, list available data based on a bounding box or named location, create simple feature objects using the sf package, and visualize the output data using popular geospatial R packages such as leaflet or mapview. The proposed ISC-funded project will enhance the capabilities of R users working with geospatial datasets, facilitating data exploration, analysis, and visualization within the R environment for improved geospatial research and applications.\n\n\n\nFunded:\n$17,000\nProposed by:\nKirill Müller\nSummary:\nThe Future of DBI focuses on the advancements achieved with support from the ISC, including bringing the existing DBI backend, RSQLite, up to specification and implementing two new compliant backends, RMariaDB and RPostgres. This project mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Ensuring compatibility with evolving elements such as OS, databases, R, and other packages is vital for long-term success. The proposal also includes modules for redesigning the database interface, efficient storage, and arithmetic for big integers, decimals with fixed width and precision, investigating Apache Arrow as an interface, and relational data models with R, with the option to adjust the scope as needed.\n\n\n\nFunded:\n$5,200\nProposed by:\nTimothy A. Ogunleye\nSummary:\nWe want to conduct training workshops on data science and machine learning with R. Out of nearly 60 countries that form the continent, we carefully selected four countries – one from each of the North, South, West, and East Africa. Nigeria is considered for the West Africa, Kenya is chosen from the East Africa, Sudan from the North Africa, while Zimbabwe is selected from the South African countries. We have 2 volunteers each, who are experts in the field of data science and machine learning with R, from the selected countries. We have also recruited 2 tutors for each country, making a total of 8. These tutors would serve as training assistants to the coordinators. Training materials are to be prepared by the coordinators. Therefore, the coordinators are expected to teach the contents of the training materials." }, { - "objectID": "all-projects/isc-working-groups.html", - "href": "all-projects/isc-working-groups.html", - "title": "ISC Working Groups", + "objectID": "all-projects/2021-group-2.html#funded-isc-grants-2021-2", + "href": "all-projects/2021-group-2.html#funded-isc-grants-2021-2", + "title": "R Consortium", "section": "", - "text": "ISC working groups provide the mechanism through which the ISC can explore, fund, and manage large collaborative projects. There are primary two modes of collaboration that may make a proposal well suited to be a WG:\n\nThe advice or collaboration of subject matter experts is required to decide the merit or feasibility of a project.\nThe work required for the project requires the skills not possessed by a single individual, or the amount of work required is more than can be accomplished by a single person in a reasonable amount of time.\n\n\n\nYour project will be:\n\nVetted by the relevant experts\nSanctioned by the R Consortium\nReceive the attention of the R Foundation\nBecome visible to the greater R Community\nAdministrative support from the R Consortium\n\n\n\n\nMany working groups are open for anyone. Please see the R Consortium Public Calendar for the next WG meeting you might want to attend.\n\n\n\nCensus: Is developing package recommendations, and other materials for working with census data.\nHealth Technology Assessment (HTA): To cultivate a more collaborative and unified approach to Health Technology Assessment (HTA) analytics work that leverages the power of R to enhance transparency, efficiency, and consistency, accelerating the delivery of innovative treatments to patients.\nMarshaling and Serialization in R: Developing standard practices for marshalling and unmarshalling of R objects. Involve identifying current problems, raising awareness, coming up with technical solutions, which might require additions to base R.\nMultilingual R Documentation: Support multilingual documentation in R.\nR7 Package: Object-Oriented Programming. The R7 package is a new OOP system designed to be a successor to S3 and S4. It has been designed and implemented collaboratively by the R Consortium Object-Oriented Programming Working Group, which includes representatives from R-Core, BioConductor, RStudio/tidyverse, and the wider R community.\nR Certification: Is working to establish a common certification program for proficiency in R.\nR Repositories: Collaboratively exploring how to support, maintain, and improve the tooling for R package distribution.\nR Tables for Regulatory Submission (RTRS): Develop standards for creating tables that meet the requirements of FDA submission documents.\nR Validation Hub: Working to devise a standard for validating packages for the regulated Pharmaceutical industry and create a online repository that will be free to use.\nSubmissions: Focus on IT and platform challenges that must be addressed in order to make “all R” regulatory submissions.\n\n\nActive working groups have public mailing lists to facilitate discussions.\n\n\n\n\nhistoRicalg: This project aims to document and test older Fortran and C and other code that is still essential to the R ecosystem, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future.\nFuture-proof native APIs for R: Is working to assess current native API usage, gather community input, and work towards an easy-to-understand, consistent and verifiable API that will drive R language adoption.\nR IDEA: Now a Top Level Project. R Community Diversity and Inclusion is a group broadly considering how the R Consortium can best encourage and support diversity and inclusion in the R Community.\nUnified Framework for Distributed Computing in R: Exploring the feasibility of developing a common framework to standardize the programming of distributed applications in R.\nDistributed Computing: Endorse the design of a common abstraction for distributed data structures in R.\n\n\n\nR / Business: R users from different areas of business and financial services collaborating on events and advocacy of R.\nCode Coverage: Develop a tool that addresses feature and platform limitations of existing tools. Helping to improve R software quality through the development of a code coverage tool and promoting the use of code coverage more systematically within the R ecosystem.\n\n\n\n\n\nThe purpose of ISC working groups is to organize collaborative projects under governance of the ISC. Membership in ISC working groups is in principle open to anyone from the R Community who desires to participate. There is no requirement that membership in working groups be restricted to individuals who are employed by R Consortium member companies. Working groups are expected to undertake projects that will bring benefits to the R Community.\n\n\n\nR Consortium Working Groups are authorized by the Infrastructure Steering Committee and operate in accordance with the R Consortium By-Laws and the Charter of the ISC.\nThe ISC may disband a working group at any time at its sole discretion.\n\n\n\nWorking groups may or may not receive funding from the ISC according to the needs of the working group and the budget of the ISC. Budgeting periods are aligned with the R Consortium budgeting year, from January 1 to December 31.\nIf a working group receives funding from the ISC members can manage this budget and dispose of available funds for purposes and projects that have been previously determined by the ISC to be in the scope of the working group’s charter. Spending that represents a significant part of the working group’s budget must be approved by the Executive Director.\nWorking groups may not solicit funds from outside sources without permission of the ISC or the R Consortium’s Executive Director. This includes applying for grants organizations outside of the R Consortium.\nWorking groups may supplement their budgets with income from conferences or other activities. Working groups may not spend in excess of their R Consortium budget grant plus income collected to date without authorization in the form of an additional budget grant from the R Consortium.\nAny income generated by working groups from conferences or activities in excess of the amount to cover the working group’s expenses will be returned to the R Consortium’s general fund at the end of the budgeting period. It is expected that working groups will request a budget each year that is commensurate with the expected income earned and the activities planned for that year.\n\n\n\nWorking group members are expected to represent the best interests of the R Consortium at all times, being cognizant that their activities and behavior reflect directly on the reputation of the R Consortium.\nNo member of a working group, including its leader, may enter into any financial relationship, or legal contract that pertains to their role as a working group member.\nWhen speaking at conferences or other venues about work accomplished by a working group, working group members must properly attribute the work to the working group and promote the R Consortium and working group brand when appropriate.\n\n\n\nWorking groups are required to operate transparently in full public view to the greatest extent possible. This does not preclude holding smaller invitation-only working sessions or “executive” when privacy is warranted.\nWorking groups must keep minutes for all substantial meetings and place the meeting minutes in an appropriate folder of the GitHub repository allocated to the working group. Exceptions to this practice require the approval of the ISC or the Executive Director.\nAll working group activities must be in accordance with city, state and federal laws. Working group members should be regularly reminded that their activities must:\n\ncomply with United States Antitrust laws\nbe conducted according to the R Consortium Code of Conduct\ncomply with appropriate international regulations such as the GDPR regulations of the European Union" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n\n\n\nFunded:\n$17,000\nProposed by:\nEdzer Pebesma\nSummary:\nThe retirement of rgdal, rgeos, and maptools presents a significant impact on the CRAN community, these packages are scheduled for retirement by the end of 2023. In response, a proposal for an ISC Funded project has been put forward to tackle this challenge. Preparing CRAN for the Retirement of rgdal, rgeos and maptools focuses on finding suitable alternatives for the functionalities offered by the retiring packages and providing guidance to package maintainers on necessary adjustments and migration steps. By doing so, it aims to minimize disruption to CRAN packages and existing R scripts, ensuring the overall stability and robustness of the CRAN ecosystem. The retirement process will simplify the maintenance of the “R Spatial stack” and contribute to the long-term health of the CRAN ecosystem.\n\n\n\nFunded:\n$4,840\nProposed by:\nLampros Mouselimis\nSummary:\nR Package for the ICESat-2 Altimeter Data aims to create an R package specifically designed for accessing ICESat-2 satellite data through the OpenAltimetry API. Addressing the lack of existing R packages for downloading geospatial data in specific formats, the package will enable R users to download ICESat-2 data, list available data based on a bounding box or named location, create simple feature objects using the sf package, and visualize the output data using popular geospatial R packages such as leaflet or mapview. The proposed ISC-funded project will enhance the capabilities of R users working with geospatial datasets, facilitating data exploration, analysis, and visualization within the R environment for improved geospatial research and applications.\n\n\n\nFunded:\n$17,000\nProposed by:\nKirill Müller\nSummary:\nThe Future of DBI focuses on the advancements achieved with support from the ISC, including bringing the existing DBI backend, RSQLite, up to specification and implementing two new compliant backends, RMariaDB and RPostgres. This project mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Ensuring compatibility with evolving elements such as OS, databases, R, and other packages is vital for long-term success. The proposal also includes modules for redesigning the database interface, efficient storage, and arithmetic for big integers, decimals with fixed width and precision, investigating Apache Arrow as an interface, and relational data models with R, with the option to adjust the scope as needed.\n\n\n\nFunded:\n$5,200\nProposed by:\nTimothy A. Ogunleye\nSummary:\nWe want to conduct training workshops on data science and machine learning with R. Out of nearly 60 countries that form the continent, we carefully selected four countries – one from each of the North, South, West, and East Africa. Nigeria is considered for the West Africa, Kenya is chosen from the East Africa, Sudan from the North Africa, while Zimbabwe is selected from the South African countries. We have 2 volunteers each, who are experts in the field of data science and machine learning with R, from the selected countries. We have also recruited 2 tutors for each country, making a total of 8. These tutors would serve as training assistants to the coordinators. Training materials are to be prepared by the coordinators. Therefore, the coordinators are expected to teach the contents of the training materials." }, { - "objectID": "all-projects/isc-working-groups.html#benefits-of-forming-an-isc-working-group", - "href": "all-projects/isc-working-groups.html#benefits-of-forming-an-isc-working-group", - "title": "ISC Working Groups", + "objectID": "all-projects/2022-group-2.html", + "href": "all-projects/2022-group-2.html", + "title": "R Consortium", "section": "", - "text": "Your project will be:\n\nVetted by the relevant experts\nSanctioned by the R Consortium\nReceive the attention of the R Foundation\nBecome visible to the greater R Community\nAdministrative support from the R Consortium" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n\n\n\nFunded:\n$8,000\nProposed by:\nMauricio “Pacho” Vargas Sepulveda\nSummary:\nThe D3po: R Package for Easy Interactive D3 Visualization With Shiny project plans to finish a new version of d3po and include maps and other plot types available in highcharts. This project aims to provide out-of-the-box high-quality visualizations with minimum time and coding effort.\nThe ultimate aim of the project is to produce a package that:\n\nOffers integration with Shiny\nEnables downloading the charts in different image formats (png, jpeg, svg)\nEnables downloading the data in different formats (json, csv, xlsx)\nCan produce high-quality results with a minimal number of lines of code\n\n“I figured out that d3po sounded like c3po from Star Wars, also a Chilean will read it as “dee three POH”, and “poh” is Chilean slang that reflects the “necessity is the mother of invention” spirit that Chileans have.” - Mauricio “Pacho” Vargas Sepulveda\n\n\n\nFunded:\n$8,000\nProposed by:\nMaëlle Salmon\nSummary:\nTooling and Guidance for Translations of Markdown-Based R Content (Quarto, R Markdown) focuses on the achievement of a first version of translated material, both technically (tooling to create an automatically translated document) and linguistically (glossary). With this proposal, the project will aim to share the rOpenSci workflow with others via the creation of an R package including extensive documentation.\n\n\n\nFunded:\n$22,000\nProposed by:\nSimon Urbanek\nSummary:\nThe Online Submission and Review Infrastructure for the R Journal ISC-funded project aims to address problems with the current all-manual revision infrastructure for submissions in the R Journal. The project proposes the development and deployment of an online, web-based system that ties into the existing status management infrastructure but allows for reviews and submission management to be performed online. The ISC funds will be used to assist with the development of an online front-end for the management of articles for the R Journal, including submission, checking, and peer-review tracking of articles. The system will leverage the existing rj and rjtools packages which provide the back-end, but will add a web interface to the process from submission to reviews and article management.\n\n\n\nFunded:\n$6,000\nProposed by:\nBen Ubah\nSummary:\nThe Upgrading SatRdays Website Template project addresses the SatRdays event website templates, which are used by the R community looking to run a SatRday event. The goal of this project is to upgrade the SatRdays website template with a view to make it easy for R community organizers to spin up their own SatRday website without deep knowledge of technologies like Hugo (upon which the current template is based using an R package like blogdown. There will also be documentation of this development with easy-to-follow instructions that are beginner-friendly.\n\n\n\nFunded:\n$25,000\nProposed by:\nOrhun Aydin\nSummary:\nThe Building the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure project proposes to deliver a set of self-contained online training modules on spatial and spatiotemporal data science with R. The modules will consist of focus-areas pertinent to topics frequently requested by the spatial R community using a large number of packages from CRAN Spatial Task View and Spatiotemporal Task View. The deliverable will provide the R Consortium and community with the materials needed to solicit more lessons from the community while ensuring uniformity across lessons." }, { - "objectID": "all-projects/isc-working-groups.html#join-a-working-group", - "href": "all-projects/isc-working-groups.html#join-a-working-group", - "title": "ISC Working Groups", + "objectID": "all-projects/2022-group-2.html#funded-isc-grants-2022-2", + "href": "all-projects/2022-group-2.html#funded-isc-grants-2022-2", + "title": "R Consortium", "section": "", - "text": "Many working groups are open for anyone. Please see the R Consortium Public Calendar for the next WG meeting you might want to attend." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n\n\n\nFunded:\n$8,000\nProposed by:\nMauricio “Pacho” Vargas Sepulveda\nSummary:\nThe D3po: R Package for Easy Interactive D3 Visualization With Shiny project plans to finish a new version of d3po and include maps and other plot types available in highcharts. This project aims to provide out-of-the-box high-quality visualizations with minimum time and coding effort.\nThe ultimate aim of the project is to produce a package that:\n\nOffers integration with Shiny\nEnables downloading the charts in different image formats (png, jpeg, svg)\nEnables downloading the data in different formats (json, csv, xlsx)\nCan produce high-quality results with a minimal number of lines of code\n\n“I figured out that d3po sounded like c3po from Star Wars, also a Chilean will read it as “dee three POH”, and “poh” is Chilean slang that reflects the “necessity is the mother of invention” spirit that Chileans have.” - Mauricio “Pacho” Vargas Sepulveda\n\n\n\nFunded:\n$8,000\nProposed by:\nMaëlle Salmon\nSummary:\nTooling and Guidance for Translations of Markdown-Based R Content (Quarto, R Markdown) focuses on the achievement of a first version of translated material, both technically (tooling to create an automatically translated document) and linguistically (glossary). With this proposal, the project will aim to share the rOpenSci workflow with others via the creation of an R package including extensive documentation.\n\n\n\nFunded:\n$22,000\nProposed by:\nSimon Urbanek\nSummary:\nThe Online Submission and Review Infrastructure for the R Journal ISC-funded project aims to address problems with the current all-manual revision infrastructure for submissions in the R Journal. The project proposes the development and deployment of an online, web-based system that ties into the existing status management infrastructure but allows for reviews and submission management to be performed online. The ISC funds will be used to assist with the development of an online front-end for the management of articles for the R Journal, including submission, checking, and peer-review tracking of articles. The system will leverage the existing rj and rjtools packages which provide the back-end, but will add a web interface to the process from submission to reviews and article management.\n\n\n\nFunded:\n$6,000\nProposed by:\nBen Ubah\nSummary:\nThe Upgrading SatRdays Website Template project addresses the SatRdays event website templates, which are used by the R community looking to run a SatRday event. The goal of this project is to upgrade the SatRdays website template with a view to make it easy for R community organizers to spin up their own SatRday website without deep knowledge of technologies like Hugo (upon which the current template is based using an R package like blogdown. There will also be documentation of this development with easy-to-follow instructions that are beginner-friendly.\n\n\n\nFunded:\n$25,000\nProposed by:\nOrhun Aydin\nSummary:\nThe Building the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure project proposes to deliver a set of self-contained online training modules on spatial and spatiotemporal data science with R. The modules will consist of focus-areas pertinent to topics frequently requested by the spatial R community using a large number of packages from CRAN Spatial Task View and Spatiotemporal Task View. The deliverable will provide the R Consortium and community with the materials needed to solicit more lessons from the community while ensuring uniformity across lessons." }, { - "objectID": "all-projects/isc-working-groups.html#active-working-groups", - "href": "all-projects/isc-working-groups.html#active-working-groups", - "title": "ISC Working Groups", + "objectID": "all-projects/2017-group-2.html", + "href": "all-projects/2017-group-2.html", + "title": "R Consortium", "section": "", - "text": "Census: Is developing package recommendations, and other materials for working with census data.\nHealth Technology Assessment (HTA): To cultivate a more collaborative and unified approach to Health Technology Assessment (HTA) analytics work that leverages the power of R to enhance transparency, efficiency, and consistency, accelerating the delivery of innovative treatments to patients.\nMarshaling and Serialization in R: Developing standard practices for marshalling and unmarshalling of R objects. Involve identifying current problems, raising awareness, coming up with technical solutions, which might require additions to base R.\nMultilingual R Documentation: Support multilingual documentation in R.\nR7 Package: Object-Oriented Programming. The R7 package is a new OOP system designed to be a successor to S3 and S4. It has been designed and implemented collaboratively by the R Consortium Object-Oriented Programming Working Group, which includes representatives from R-Core, BioConductor, RStudio/tidyverse, and the wider R community.\nR Certification: Is working to establish a common certification program for proficiency in R.\nR Repositories: Collaboratively exploring how to support, maintain, and improve the tooling for R package distribution.\nR Tables for Regulatory Submission (RTRS): Develop standards for creating tables that meet the requirements of FDA submission documents.\nR Validation Hub: Working to devise a standard for validating packages for the regulated Pharmaceutical industry and create a online repository that will be free to use.\nSubmissions: Focus on IT and platform challenges that must be addressed in order to make “all R” regulatory submissions.\n\n\nActive working groups have public mailing lists to facilitate discussions." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n\n\n\nFunded:\n$5,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://r-spatial.github.io/stars/\nSummary:\nThe stars project enables the processing Earth imagery data that is held on servers, without the need to download it to local hard driver. This project will (i) create software to run a back-end, (ii) develop scripts and tutorials that explain how such a data server and processing backend can be set up, and (iii) create an instance of such a backend in the AWS cloud that can be used for testing and evaluation purposes.\n\n\n\nFunded:\n$10,000\nProposed by:\nHenrik Bengtsson\nWebsite:\nhttps://github.com/HenrikBengtsson/\nSummary:\nThe objective of the Future Framework implemented in the future package is to simplify how parallel and distributed processing is conducted in R. This project aims to provide a formal Future API specification and provide a test framework for validating the conformance of existing (e.g. future.batchtools and future.callr) and to-come third-party parallel backends to the Future framework.\n\n\n\nFunded:\n$10,000\nProposed by:\nInaki Ucar\nWebsite:\nhttps://github.com/r-quantities/quantities and https://www.r-spatial.org/r/2018/08/31/quantities-final.html\nSummary:\nThe ‘units’ package has become the reference for quantity calculus in R, with a wide and welcoming response from the R community. Along the same lines, the ‘errors’ package integrates and automatises error propagation and printing for R vectors. A significant fraction of R users, both practitioners and researchers, use R to analyse measurements, and would benefit from a joint processing of quantity values with errors.\nThis project not only aims at orchestrating units and errors in a new data type, but will also extend the existing frameworks (compatibility with base R as well as other frameworks such as the tidyverse) and standardise how to import/export data with units and errors.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Beare\nWebsite:\nhttps://github.com/richardbeare/RConsortiumSwig\nSummary:\nThe Simplified Wrapper and Interface Generator (SWIG) is a tool for automatically generating interface code between interpreters, including R, and a C or C++ library. The R module needs to be updated to support modern developments in R and the rest of SWIG. This project aims to make the R module conform to the recommended SWIG standards and thus ensure that there is support for R in the future. We hope that this project will be the first step in allowing SWIG generated R code using reference classes." }, { - "objectID": "all-projects/isc-working-groups.html#completed-working-groups", - "href": "all-projects/isc-working-groups.html#completed-working-groups", - "title": "ISC Working Groups", + "objectID": "all-projects/2017-group-2.html#funded-isc-grants-2017-2", + "href": "all-projects/2017-group-2.html#funded-isc-grants-2017-2", + "title": "R Consortium", "section": "", - "text": "histoRicalg: This project aims to document and test older Fortran and C and other code that is still essential to the R ecosystem, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future.\nFuture-proof native APIs for R: Is working to assess current native API usage, gather community input, and work towards an easy-to-understand, consistent and verifiable API that will drive R language adoption.\nR IDEA: Now a Top Level Project. R Community Diversity and Inclusion is a group broadly considering how the R Consortium can best encourage and support diversity and inclusion in the R Community.\nUnified Framework for Distributed Computing in R: Exploring the feasibility of developing a common framework to standardize the programming of distributed applications in R.\nDistributed Computing: Endorse the design of a common abstraction for distributed data structures in R." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n\n\n\nFunded:\n$5,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://r-spatial.github.io/stars/\nSummary:\nThe stars project enables the processing Earth imagery data that is held on servers, without the need to download it to local hard driver. This project will (i) create software to run a back-end, (ii) develop scripts and tutorials that explain how such a data server and processing backend can be set up, and (iii) create an instance of such a backend in the AWS cloud that can be used for testing and evaluation purposes.\n\n\n\nFunded:\n$10,000\nProposed by:\nHenrik Bengtsson\nWebsite:\nhttps://github.com/HenrikBengtsson/\nSummary:\nThe objective of the Future Framework implemented in the future package is to simplify how parallel and distributed processing is conducted in R. This project aims to provide a formal Future API specification and provide a test framework for validating the conformance of existing (e.g. future.batchtools and future.callr) and to-come third-party parallel backends to the Future framework.\n\n\n\nFunded:\n$10,000\nProposed by:\nInaki Ucar\nWebsite:\nhttps://github.com/r-quantities/quantities and https://www.r-spatial.org/r/2018/08/31/quantities-final.html\nSummary:\nThe ‘units’ package has become the reference for quantity calculus in R, with a wide and welcoming response from the R community. Along the same lines, the ‘errors’ package integrates and automatises error propagation and printing for R vectors. A significant fraction of R users, both practitioners and researchers, use R to analyse measurements, and would benefit from a joint processing of quantity values with errors.\nThis project not only aims at orchestrating units and errors in a new data type, but will also extend the existing frameworks (compatibility with base R as well as other frameworks such as the tidyverse) and standardise how to import/export data with units and errors.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Beare\nWebsite:\nhttps://github.com/richardbeare/RConsortiumSwig\nSummary:\nThe Simplified Wrapper and Interface Generator (SWIG) is a tool for automatically generating interface code between interpreters, including R, and a C or C++ library. The R module needs to be updated to support modern developments in R and the rest of SWIG. This project aims to make the R module conform to the recommended SWIG standards and thus ensure that there is support for R in the future. We hope that this project will be the first step in allowing SWIG generated R code using reference classes." }, { - "objectID": "all-projects/isc-working-groups.html#inactive-working-groups", - "href": "all-projects/isc-working-groups.html#inactive-working-groups", - "title": "ISC Working Groups", + "objectID": "all-projects/rugsprogram.html", + "href": "all-projects/rugsprogram.html", + "title": "R User Groups, Conferences, and Special Project Grants", "section": "", - "text": "R / Business: R users from different areas of business and financial services collaborating on events and advocacy of R.\nCode Coverage: Develop a tool that addresses feature and platform limitations of existing tools. Helping to improve R software quality through the development of a code coverage tool and promoting the use of code coverage more systematically within the R ecosystem." + "text": "R User Groups, Conferences, and Special Project Grants\nThis page describes how to apply for grants to support R user groups, conferences featuring R, and R Special Projects.\nFor any problems or information, please email operations@r-consortium.org\n\n\n2024 RUGS Program\nThe RUGS mission is to facilitate the person-to-person exchange of knowledge in small group settings on a global scale. We continue to believe that the most effective way for people to learn from and about each other, and to set and accomplish common goals is to meet face-to-face on a regular basis. Nevertheless, occasional virtual meetings are acceptable.\nRUGS grants are intended to help people form enduring R user group communities. Active user groups may apply for grants once every calendar year.\nThe R Consortium RUGS Program has grown from being a relatively modest R user group support program to being the primary vehicle for the R Consortium to award Social Infrastructure Grants. Social Infrastructure includes meetings, events, conferences, and other activities to strengthen the R Community.\nThese grants do not include support for software development or technical projects. Grants to support the R ecosystem’s technical infrastructure are awarded and administered through the ISC Grant Program, which issues a call for proposals two times each year.\n\n📌 Find your local R User Group here\n\n\n\n\nStructure\nIn 2024, there will be three categories of RUGS Program grants that are described in detail below:\n\nUser Group Grants\nConference Grants\nSpecial Projects Grants\n\n\nDuration of the 2024 RUGS Program\nThe 2024 RUGS Program will open on January 8, 2024, and close at midnight PST on September 30, 2024. We reserve the right to close the grant window earlier than anticipated based on the number of applications.\n\n\nHow to apply for a RUGS Program Grant\nTo apply for a grant fill out this form. Be sure to select the correct box to indicate whether you are applying for a use group, conference, or special projects grant.\n\n\n\nUser Group Grants\n\nRequirements\nTo be eligible for a RUGS grant, a user group must:\n\nGroup Organizer must have at least five people in the R User Group\nHave R as a primary focus\nAdhere to the Code of Conduct published on the R Consortium website\nAgree to participate in the RUGS meetup.com Pro program and use their meetup.com site to announce and track meetings\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on the group’s website\nAgree to write at least two blog posts per year about their group’s activities for possible publication on the R Consortium Blog\nComply with the instructions by completing a W9 Form (US-based groups only) or Wire Transfer form (Groups based outside of the US)\nAgree to the above in a grant agreement via DocuSign\n\n\n\nStructure\nR user groups grants under the RUGS 2024 program come in two parts:\n\nR user groups that are not already participating in the RUGS meetup.com Pro account will be enrolled into this program. The R Consortium will pay the group’s meetup.com fees for twelve months after acceptance into the program. Thereafter, the R Consortium will continue to pay meetup.com dues for participating groups as long as the groups comply with the requirements above, remain active, continue to meet at least once every three months, and use meetup.com to schedule and announce meetings. User group organizers do not need to re-apply for meetup.com Pro account participation if the group’s meetup.com account remains active.\nCash grants typically vary between $200 and $1,000 and depend on group size and special needs.\n\n\n\n\nGeneral Requirements\n\nMust agree to write 2 blog posts a year\nPost photos of their meetings onto Meetup.com as appropriate\nUpload available material to the R Consortium GitHub Repository\n\n\n\nRUGs Grant Amounts and Groups’ Responsibilities\nBrand new R User Group\n\nThe group receives a grant of $250 and membership in Meetup pro\nThe group must show 5 people committed to the group\nR Consortium will provide the blog link and best practice guide\nThe group must agree to write two blog posts per year\n\nTo get a grant of up to $500, all of the above plus:\n\nThe group must meet at least 1 time every 3 months\nThe group must have more than 25 people at the meeting\nThe group must have photos of the meeting\nThe group must show R Consortium Sponsorship\n\nTo get a grant of up to $1,000, all of the above plus:\n\nThe group must meet at least twice every 3 months\nThe group must have more than 50 people at the meeting\nThe group should provide presentations available for others (The R Consortium will host on GitHub)\n\n\nNotes\n\nR-Ladies maintains a separate meetup.com Pro account. R-Ladies groups must apply directly to R-Ladies for acceptance into their program. They will not be automatically entered into the RUGS meetup.com Pro account.\nThe R Consortium maintains the right to terminate the RUG’s Pro program at any time. Additionally, The R Consortium has the right to terminate a group’s participation in the meetup.com Pro program if they do not comply with the requirements specified in the Code of Conduct.\n\n\n\n\n2024 Conference Grants\nTo qualify for a RUGS program conference grant, an event must be focused on the R language, offer at least one full day of technical talks and presentations, and aim to attract participants with diverse backgrounds. RUGS conference grants are for conferences organized by non-profit or volunteer groups. If you seek a sponsorship for your professional event, please contact sponsorship@r-consortium.org.\nFor good examples of conferences, please see Bioconductor, Rencontres, and LatinR.\n\n\nRequirements\n\nTo be eligible for consideration, a conference must:\n\nBe organized around the R Language or demonstrate that there will be significant R content.\nThese are NOT workshops.\nHave a web page that provides basic typical information such as:\n\nThe theme or purpose of the conference\nThe date, time and location of the conference\nRegistration fees listed for classes of attendees (e.g. corporate, student etc.) and mechanism for people to register\nSponsorship details (R Consortium logo should not be posted until grant is approved and contract is signed) along with details on classes of sponsorship and any associated benefits\nA list of sponsors or alternate sources of funding\nA section on how to submit talks and a mechanism for people to submit talks\nA list of keynote speakers (if any)\nA schedule of talks and events\nA list of confirmed speakers\nInformation about travel and housing\nA code of conduct that uses or is compatible with the R Consortium’s Code of Conduct that provides information about how conference participants can report violations or seek help\n\n\n\n\nAfter Receiving a Grant\n\nApplicants must submit billing documentation (W9 or wire transfer form) within one week of contract signature.\nConference organizers must:\n\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on the conference website.\nProvide at least one full admission ticket for an R Consortium member.\nWrite a short report after the conference summarizing what happened, describing highlights, and providing key metrics for the conference, including demographics for the attendees, in a way that would be suitable for publication as an R Consortium blog post.\nOffer the R Consortium the same benefits that the conference offers to other sponsors at the same level of support.\nComply with local Covid-19 public health protocols.\n\n\nNote\nAny grant relating to a specific activity will be canceled if (a) the activity to which it relates is canceled without rescheduling or (b) the activity has otherwise not occurred within 365 days of the grant date.\n\n\n\nSpecial Projects Grants\nWe do not believe that these kinds of events comprise everything that can be done to support the R Community. With our Special Projects Grants categories, we hope to stimulate the imagination of local R community builders.\n\n\nRequirements\n\nA request for a special purpose grant must take the form of a formal proposal and include:\n\nA business case for the project\nThese are NOT workshops\nA description of how it will benefit the R Community\nA description of who will participate\nThe cost to participate\nExplaining how it will happen\nListing the work products that might result\nDetailing when and where the project will happen\nListing who will manage and produce the project\nDetailing how much it will cost\nInclude a detailed breakdown of how grant money will be spent\nHave a Code of Conduct\n\n\n\nAfter Receiving a Grant\n\nApplicants must submit billing documentation (W9 or wire transfer form) within one week of contract signature\nAcknowledge the R Consortium as a sponsor and display the R Consortium logo on any associated online websites or promotional material\nApplicant billing information must match applicant contact information\nParticipants must:\n\nEvent participants must adhere to the Code of Conduct\nComply with local COVID-19 public health protocols\n\n\n\n\nAlso, note that any training materials developed with R Consortium funds must be made publically available with an open source license.\n\n\nHow to Apply for a RUGS, Conference, or Special Projects Grant\nApply for a grant by filling out this form. Be sure to select the correct box on the form that indicates whether you are applying for a RUGS grant, a conference grant, or a special projects grant" }, { - "objectID": "all-projects/isc-working-groups.html#isc-regulations-and-guidelines", - "href": "all-projects/isc-working-groups.html#isc-regulations-and-guidelines", - "title": "ISC Working Groups", + "objectID": "all-projects/2023-group-1.html", + "href": "all-projects/2023-group-1.html", + "title": "R Consortium", "section": "", - "text": "The purpose of ISC working groups is to organize collaborative projects under governance of the ISC. Membership in ISC working groups is in principle open to anyone from the R Community who desires to participate. There is no requirement that membership in working groups be restricted to individuals who are employed by R Consortium member companies. Working groups are expected to undertake projects that will bring benefits to the R Community.\n\n\n\nR Consortium Working Groups are authorized by the Infrastructure Steering Committee and operate in accordance with the R Consortium By-Laws and the Charter of the ISC.\nThe ISC may disband a working group at any time at its sole discretion.\n\n\n\nWorking groups may or may not receive funding from the ISC according to the needs of the working group and the budget of the ISC. Budgeting periods are aligned with the R Consortium budgeting year, from January 1 to December 31.\nIf a working group receives funding from the ISC members can manage this budget and dispose of available funds for purposes and projects that have been previously determined by the ISC to be in the scope of the working group’s charter. Spending that represents a significant part of the working group’s budget must be approved by the Executive Director.\nWorking groups may not solicit funds from outside sources without permission of the ISC or the R Consortium’s Executive Director. This includes applying for grants organizations outside of the R Consortium.\nWorking groups may supplement their budgets with income from conferences or other activities. Working groups may not spend in excess of their R Consortium budget grant plus income collected to date without authorization in the form of an additional budget grant from the R Consortium.\nAny income generated by working groups from conferences or activities in excess of the amount to cover the working group’s expenses will be returned to the R Consortium’s general fund at the end of the budgeting period. It is expected that working groups will request a budget each year that is commensurate with the expected income earned and the activities planned for that year.\n\n\n\nWorking group members are expected to represent the best interests of the R Consortium at all times, being cognizant that their activities and behavior reflect directly on the reputation of the R Consortium.\nNo member of a working group, including its leader, may enter into any financial relationship, or legal contract that pertains to their role as a working group member.\nWhen speaking at conferences or other venues about work accomplished by a working group, working group members must properly attribute the work to the working group and promote the R Consortium and working group brand when appropriate.\n\n\n\nWorking groups are required to operate transparently in full public view to the greatest extent possible. This does not preclude holding smaller invitation-only working sessions or “executive” when privacy is warranted.\nWorking groups must keep minutes for all substantial meetings and place the meeting minutes in an appropriate folder of the GitHub repository allocated to the working group. Exceptions to this practice require the approval of the ISC or the Executive Director.\nAll working group activities must be in accordance with city, state and federal laws. Working group members should be regularly reminded that their activities must:\n\ncomply with United States Antitrust laws\nbe conducted according to the R Consortium Code of Conduct\ncomply with appropriate international regulations such as the GDPR regulations of the European Union" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n\n\n\nFunded:\n$10,000\nProposed by:\nKirill Müller\nSummary:\nThis proposal mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Keeping compatibility with the evolving ecosystem (OS, databases, R itself, other packages) is vital for the long-term success of the project.\n\n\n\nFunded:\n$10,000\nProposed by:\nCharlie Gao\nSummary:\nThe project aims to implement secure connections with a TLS layer for encrypted communications in distributed systems used by statisticians and data scientists. The current lack of secure communication tools restricts the use of existing R packages for long-running tasks to trusted local networks, posing security risks in compromised or untrusted environments. The proposed solution addresses this gap by providing encryption and authentication of endpoints, ensuring data security in line with industry standards.\n\n\n\nFunded:\n$12,265\nProposed by:\nKristina Riemer\nSummary:\nThis ISC funded project focuses on the development of the volcalc R package, which automates the estimation of compound volatility based on their chemical structure. The package streamlines the process by downloading chemical structure data, parsing it to identify functional groups, and utilizing the SIMPOL.1 algorithm to predict volatility using functional groups and molecular weight. The compounds are then assigned volatility categories based on a reference environment. This project aims to enhance the package by expanding its compatibility to work with any chemical compound with structural information from various databases. Additionally, improvements in testing and documentation will be implemented to enhance the reliability of the package.\n\n\n\nFunded:\n$3,000\nProposed by:\nMark Padgham\nSummary:\nThe project aims to develop an R package to automate property-based testing procedures in R, building upon the existing “typetracer” package. The new package will utilize “typetracer” to infer properties of function parameters and systematically mutate or randomize these properties to facilitate automated testing. The package will inherit the GPL-3 license from its predecessor and will be submitted to CRAN for wider dissemination. This initiative aligns with the goal of promoting efficient and reliable testing practices within the R community.\n\n\n\nFunded:\n$15,750\nProposed by:\nJon Harmon\nSummary:\nThis project aims to develop an R package called api2r, which will automate the creation of R package structures for APIs that adhere to the OpenAPI Specification (OAS). By leveraging the OAS as a foundation, api2r will significantly reduce the time and effort required to build API clients in R. This initiative hopes to have a widespread impact within the R community, benefiting data scientists, researchers, and developers who regularly interact with diverse APIs. To ensure its functionality and effectiveness, the development process will involve generating packages based on at least three authentic OpenAPI specifications." }, { - "objectID": "all-projects/2016-group-2.html", - "href": "all-projects/2016-group-2.html", + "objectID": "all-projects/2023-group-1.html#funded-isc-grants-2023-1", + "href": "all-projects/2023-group-1.html#funded-isc-grants-2023-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n\n\n\nFunded:\n$9,100\nProposed by:\nTim Appelhans\nWebsite:\nhttps://github.com/environmentalinformatics-marburg/mapview_toolchain and https://cran.r-project.org/package=mapview\nSummary:\nThe ISC awarded $9,100 to Tim Appelhans, Florian Detsch and Christoph Reudenbach the authors of the Interactive data manipulation in mapview project which aims to extend the capabilities of R for visualizing geospatial data by implementing a two-way data exchange mechanism between R and JavaScript. The central idea is to extend the capabilities of existing tools to enhance the user experience of interactively working with geospatial data by implementing mechanisms for two way data transfer. For example, although htmlwidgets has proven itself to be a powerful framework for enabling interactive, JavaScript based data visualizations, data flow from R to Javascript runs on a one-way street. There is currently no way to pass manipulated data back into the user’s R environment. This project aims to first develop a general framework to provide a bridge between htmlwidgets and R to enable a workflow of R -> htmlwidgets -> R and then to use this framework to implement standard interactive spatial data manipulation tools for packages mapview and leaflet. The plan section of the project proposal provides considerable detail on the steps required to achieve the project’s goals.\n\n\n\nFunded:\n$10,000\nProposed by:\nAndrew Redd\nWebsite:\nhttps://github.com/RDocTaskForce/documentation\nSummary:\nAndrew Redd received $10,000 to lead a new ISC working group, The R Documentation Task Force, which has a mission to design and build the next generation R documentation system. The task force will identify issues with documentation that currently exist, abstract the current Rd system into an R compatible structure, and extend this structure to include new considerations that were not concerns when the Rd system was first implemented. The goal of the project is to create a system that allows for documentation to exist as objects that can be manipulated inside R. This will make the process of creating R documentation much more flexible enabling new capabilities such as porting documentation from other languages or creating inline comments. The new capabilities will add rigor to the documentation process and enable the the system to operate more efficiently than any current methods allow." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n\n\n\nFunded:\n$10,000\nProposed by:\nKirill Müller\nSummary:\nThis proposal mostly focuses on the maintenance and support for {DBI}, the {DBItest} test suite, and the three backends to open-source databases ({RSQLite}, {RMariaDB} and {RPostgres}). Keeping compatibility with the evolving ecosystem (OS, databases, R itself, other packages) is vital for the long-term success of the project.\n\n\n\nFunded:\n$10,000\nProposed by:\nCharlie Gao\nSummary:\nThe project aims to implement secure connections with a TLS layer for encrypted communications in distributed systems used by statisticians and data scientists. The current lack of secure communication tools restricts the use of existing R packages for long-running tasks to trusted local networks, posing security risks in compromised or untrusted environments. The proposed solution addresses this gap by providing encryption and authentication of endpoints, ensuring data security in line with industry standards.\n\n\n\nFunded:\n$12,265\nProposed by:\nKristina Riemer\nSummary:\nThis ISC funded project focuses on the development of the volcalc R package, which automates the estimation of compound volatility based on their chemical structure. The package streamlines the process by downloading chemical structure data, parsing it to identify functional groups, and utilizing the SIMPOL.1 algorithm to predict volatility using functional groups and molecular weight. The compounds are then assigned volatility categories based on a reference environment. This project aims to enhance the package by expanding its compatibility to work with any chemical compound with structural information from various databases. Additionally, improvements in testing and documentation will be implemented to enhance the reliability of the package.\n\n\n\nFunded:\n$3,000\nProposed by:\nMark Padgham\nSummary:\nThe project aims to develop an R package to automate property-based testing procedures in R, building upon the existing “typetracer” package. The new package will utilize “typetracer” to infer properties of function parameters and systematically mutate or randomize these properties to facilitate automated testing. The package will inherit the GPL-3 license from its predecessor and will be submitted to CRAN for wider dissemination. This initiative aligns with the goal of promoting efficient and reliable testing practices within the R community.\n\n\n\nFunded:\n$15,750\nProposed by:\nJon Harmon\nSummary:\nThis project aims to develop an R package called api2r, which will automate the creation of R package structures for APIs that adhere to the OpenAPI Specification (OAS). By leveraging the OAS as a foundation, api2r will significantly reduce the time and effort required to build API clients in R. This initiative hopes to have a widespread impact within the R community, benefiting data scientists, researchers, and developers who regularly interact with diverse APIs. To ensure its functionality and effectiveness, the development process will involve generating packages based on at least three authentic OpenAPI specifications." }, { - "objectID": "all-projects/2016-group-2.html#funded-isc-grants-2016-2", - "href": "all-projects/2016-group-2.html#funded-isc-grants-2016-2", + "objectID": "all-projects/2024-group-1.html", + "href": "all-projects/2024-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n\n\n\nFunded:\n$9,100\nProposed by:\nTim Appelhans\nWebsite:\nhttps://github.com/environmentalinformatics-marburg/mapview_toolchain and https://cran.r-project.org/package=mapview\nSummary:\nThe ISC awarded $9,100 to Tim Appelhans, Florian Detsch and Christoph Reudenbach the authors of the Interactive data manipulation in mapview project which aims to extend the capabilities of R for visualizing geospatial data by implementing a two-way data exchange mechanism between R and JavaScript. The central idea is to extend the capabilities of existing tools to enhance the user experience of interactively working with geospatial data by implementing mechanisms for two way data transfer. For example, although htmlwidgets has proven itself to be a powerful framework for enabling interactive, JavaScript based data visualizations, data flow from R to Javascript runs on a one-way street. There is currently no way to pass manipulated data back into the user’s R environment. This project aims to first develop a general framework to provide a bridge between htmlwidgets and R to enable a workflow of R -> htmlwidgets -> R and then to use this framework to implement standard interactive spatial data manipulation tools for packages mapview and leaflet. The plan section of the project proposal provides considerable detail on the steps required to achieve the project’s goals.\n\n\n\nFunded:\n$10,000\nProposed by:\nAndrew Redd\nWebsite:\nhttps://github.com/RDocTaskForce/documentation\nSummary:\nAndrew Redd received $10,000 to lead a new ISC working group, The R Documentation Task Force, which has a mission to design and build the next generation R documentation system. The task force will identify issues with documentation that currently exist, abstract the current Rd system into an R compatible structure, and extend this structure to include new considerations that were not concerns when the Rd system was first implemented. The goal of the project is to create a system that allows for documentation to exist as objects that can be manipulated inside R. This will make the process of creating R documentation much more flexible enabling new capabilities such as porting documentation from other languages or creating inline comments. The new capabilities will add rigor to the documentation process and enable the the system to operate more efficiently than any current methods allow." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n\n\n\nFunded:\n$18,000\nProposed by:\nCory Brunson and Aymeric Stamm\nSummary:\nThe goal of this project is to seamlessly integrate popular techniques from topological data analysis (TDA) into common statistical workflows in R. The expected benefit is that these extensions will be more widely used by non-specialist researchers and analysts, which will create sufficient awareness and interest in the community to extend the individual packages and the collection.\n\n\n\nFunded:\n$13,750\nProposed by:\nEmmanuel Blondel\nSummary:\nThe present project enhances the geometa package for handling the new ISO 19115-3 geographic information standard as part of its object-oriented data model developed with R6. The user community, especially data managers working in research national institutes and international organizations, will take advantage of the features to start adopting the new standard for managing their geographic metadata, progressively promoted in Geographic information management web platforms, especially those from the OpenSource Geospatial Foundation (OSGeo) such as GeoNetwork, PyCSW or GeoNode.\n\n\n\nFunded:\n$20,000\nProposed by:\nWill Landau\nSummary:\nThe implementation of R-multiverse to date has been both straightforward and achievable. It builds directly upon the proven technologies of R-universe and GitHub Actions. By the end of the milestones, the entire project will be in a ready state to be launched to the public as a production solution for non-CRAN non-Bioconductor packages.\n\n\n\nFunded:\n$8,000\nProposed by:\nAidan Lakshman, University of Pittsburgh\nSummary:\nBiostrings is a core Bioconductor package providing efficient containers for storing, manipulating, and analyzing biological sequences. Biostrings is the method to access biological sequence data in R; nearly every analysis working with genomic data depends on the Biostrings package to handle sequencing data.\nThis project proposes to clear out accumulated technical debt by addressing open issues, implementing robust tests for long-term sustainability, improving user experience, and adding features that will keep Biostrings relevant for modern sequencing technologies. For end-users, this will result in numerous bugfixes, a host of new features to support genomic analyses, and a variety of performance improvements to bolster R as one of the top programming languages for bioinformatics. For developers, this will make the Biostrings package more sustainable, allowing for more community contribution and faster bug resolution in the future.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon, cynkra\nSummary:\nThis project is aimed at improving the quality of igraph codebase itself and of the user interface (messages including error messages, documentation indicating the status of exported functions). It has the goal of improving the user-friendliness of the installation from source.\n\n\n\nFunded:\n$15,912\nProposed by:\nEric Scott, University of Arizona\nSummary:\nThe goal of this project is to create a package that makes using targets for geospatial analysis in R as seamless as possible. To that end, geotargets will provide custom functions for defining geospatial targets that take care of translating and saving R objects for the user. In addition, the project will provide vignettes demonstrating how to use various geospatial R packages with targets. Where appropriate, the project will identify contributions to existing R packages to make them easier to use with targets and geotargets." }, { - "objectID": "all-projects/2018-group-2.html", - "href": "all-projects/2018-group-2.html", + "objectID": "all-projects/2024-group-1.html#funded-isc-grants-2024-1", + "href": "all-projects/2024-group-1.html#funded-isc-grants-2024-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n\n\n\nFunded:\n$46,050\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://blog.r-hub.io\nSummary:\nAfter the continuing technical progress of R-hub over the last two years, this project aims at catalizing its adoption by R package developers of all levels through developer advocacy. Indeed, R-hub is currently a successful and very valuable project, but it is not documented thoroughly, which hinders its wider adoption by package developers. This project shall answer this concern by three main actions: improving R-hub documentation, making R-hub better known in the community and making the R-hub web site more attractive to, and easier to use by, R developers and users via the ingestion of METACRAN services and the creation of a R-hub blog.\n\n\n\nFunded:\n$5,250\nProposed by:\nBenaiah Chibuokem Ubah\nWebsite:\nhttps://benubah.github.io/r-community-explorer/rugs.html\nSummary:\nThis project proposes an infrastructure that provides a data-driven approach to render the yearly activities of the R Consortium, by deploying web pages for discovering and tracking ISC Funded Projects, RUGS and Marketing activities. These pages are planned to appear like dashboards summarizing activities in interactive tables and charts, presenting several views, trends and insights to what R Consortium has achieved over time. The project hopes that presenting these achievements in a data-driven manner to the R community, the data science community and prospective R Consortium members will promote greater transparency, productivity and community inclusiveness around R Consortium activities.\n\n\n\nFunded:\n$50,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://rjpilot.netlify.app/\nSummary:\nThis project supports the operation of the R Journal. There are two aspects, one is to fund an editorial assistant to send reminders about reviews, and assist with typesetting and copyediting issues. The second part is to explore updating the technical operations of the journal production.\n\n\n\nFunded:\n$6,000\nProposed by:\nColin Fay\nWebsite:\nhttps://github.com/ThinkR-open/isc-proposal-licence/ and https://thinkr-open.github.io/licensing-r/intro.html#getting-a-more-global-idea and https://github.com/ThinkR-open/isc-proposal-licence/blob/master/proposal_licence.md\nSummary:\nLicensing is a vital part of Open Source. It provides guidelines for interacting with a program, and for making code accessible and reusable (or not). It provides a way to make code open source, in a way one wants to share it, protecting how it will be used and reused. Licensing is also challenging and complex: there are a lot of available licenses, and the choice is influenced by how you import and interact with elements from other packages and/or programs.\nWith this project, we propose to explore and document the current state of open source licenses in R, and to decipher compatibility and incompatibly elements inside these licenses, to help developers chose the best suited licence for their project.\n\n\n\nFunded:\n$25,000\nProposed by:\nClaus Wilke\nWebsite:\nhttps://wilkelab.org/gridtext/\nSummary:\nText is a key component of any data visualization. We need to label axes and legends, we need to annotate or highlight specific data points, and we need to provide plot titles and captions. The R graphics package ggplot2 provides numerous features to customize the labeling and annotation of plots, but ultimately it is limited by the current capabilities of the underlying graphics libary it uses, grid. Grid can draw simple text strings or mathematical expressions (via plotmath) in different colors, sizes, and fonts. However, it lacks functionality for changing formatting within a string (e.g., draw a single word in italics or in a different color), and it also cannot draw text boxes, where the text is enclosed in a box with defined margins, padding, or background color. This project will support the development of a new package, gridtext, that will alleviate these text formatting limitations. The project will also support efforts to make these new capabilities available from within ggplot2.\n\n\n\nFunded:\n$20,000\nProposed by:\nEmmanuel Blondel\nWebsite:\nSummary:\nThe project aims to strengthen the role of R in support of Spatial Data Infrastructures (SDI) management, through major enhancements of the geometa R package which offers tools for reading and writing ISO/OGC geographic metadata, including ISO 19115, 19110, and 19119 through the ISO 19139 XML format. This also extends to the Geographic Markup Language (GML - ISO 19136) used for describing geographic data. The use of geometa in combination with publication tools such as ows4R ( https://cran.r-project.org/package=ows4R ) and geosapi (https://cran.r-project.org/package=geosapi) fosters the use of R software to ease the management and publication of metadata documents and related datasets in web catalogues, and then allows to move forward with a real R implementation of spatial data management plans based on FAIR (Findable, Accessible Interoperable and Reusable) principles.\nThe workplan includes several activities such as working on the completeness of the ISO 19115 (ISO 19115-1 and 19115-2) data model in geometa, functions to read/write multilingual metadata documents, and an increased metadata validation capability with a validator targeting the EU INSPIRE directive. Finally, functions will be made available to convert between geometa ISO/OGC metadata objects and other known metadata objects such as NetCDF-CF and EML (Ecological Metadata Language) to foster metadata interoperability. By providing these R tools, we seek to facilitate the work of spatial data (GIS) managers, but also data scientists, whatever the thematic domain, whose daily tasks consist in handling data, describing them with metadata and publishing datasets.\n\n\n\nFunded:\n$6,000\nProposed by:\nEmi Tanaka\nWebsite:\nSummary:\nSymbolic model formulae define the structural component of a statistical model in an easier and often more accessible terms for practitioners. The earlier instance of symbolic model formulae for linear models was applied in Genstat with further generalisation by Wilkinson and Rogers (1973). Chambers and Hastie (1993) describe the symbolic model formulae implementation for linear models in the S language which remains much the same in the R language (Venables et al. 2018).\nLinear mixed models (LMMs) are widely used across many disciplines (e.g. ecology, psychology, agriculture, finance etc) due to its flexibility to model complex, correlated structures in the data. While the symbolic formula of linear models generally have a consistent representation and evaluation rule as implemented in stats::formula, this is not the case for LMMs. The inconsistency of symbolic formulae arises mainly in the representation of random effects, with the additional need to specify the variance-covariance structure of the random effects as well as structure of the associated model matrix that governs how the random effects are mapped to (groups of) the observational units. The differences give rise to confusion of equivalent model specification in different R-packages.\nThe lack of consistency in symbolic formula and model representation across mixed model software motivates the need to formulate a unified symbolic model formulae for LMMs with: (1) extension of the evaluation rules described in Wilkinson and Rogers (1973); and (2) ease of comprehension of the specified model for the user. This symbolic model formulae can be a basis for creating a common API to mixed models with wrappers to popular mixed model R-packages, thereby achieving a similar feat to parsnip R-package (Kuhn 2018) which implements a tidy unified interface to many predictive modelling functions (e.g. random forest, logistic regression, survival models etc).\nWe would like to find out what are your experiences with fitting linear mixed model in R! Please fill out the survey below to help us understand your problems: https://docs.google.com/forms/d/e/1FAIpQLSeblEoPtDmPS-dH2dmsHjLxLuKl19UY1JdmTrZux-AUSq3N7Q/viewform?usp=sf_link\n\n\n\nFunded:\n$10,000\nProposed by:\nChristoph Bodner, Florian Schwendinger, Thomas Laber\nWebsite:\nhttps://github.com/harlecin/serverless\nSummary:\nR is a great language for rapid prototyping and experimentation, but putting an R model in production is still more complex and time-consuming than it needs to be. With the growing popularity of serverless computing frameworks such as AWS Lambda and Azure Functions we see a a huge chance to allow R developers to more easily deploy their code into production. We want to build an R package called ‘serverless’ to allow R users to easily deploy scripts and custom R packages to AWS Lambda and in a second step to Azure Functions. Our main goal is to build a user-friendly cloud agnostic wrapper that can be extended to include additional cloud providers later on. We want to build on the work already done for deploying R functions to AWS Lambda by Philipp Schirmer and on the work already done by Neal Fultz and Gergely Daróczi on a gRPC client/server for R, which is necessary for Azure Functions. If you like our idea and want to help us, feel free to reach out to us on Github at https://github.com/harlecin/serverless\nBest,\nChristoph, Florian and Thomas" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n\n\n\nFunded:\n$18,000\nProposed by:\nCory Brunson and Aymeric Stamm\nSummary:\nThe goal of this project is to seamlessly integrate popular techniques from topological data analysis (TDA) into common statistical workflows in R. The expected benefit is that these extensions will be more widely used by non-specialist researchers and analysts, which will create sufficient awareness and interest in the community to extend the individual packages and the collection.\n\n\n\nFunded:\n$13,750\nProposed by:\nEmmanuel Blondel\nSummary:\nThe present project enhances the geometa package for handling the new ISO 19115-3 geographic information standard as part of its object-oriented data model developed with R6. The user community, especially data managers working in research national institutes and international organizations, will take advantage of the features to start adopting the new standard for managing their geographic metadata, progressively promoted in Geographic information management web platforms, especially those from the OpenSource Geospatial Foundation (OSGeo) such as GeoNetwork, PyCSW or GeoNode.\n\n\n\nFunded:\n$20,000\nProposed by:\nWill Landau\nSummary:\nThe implementation of R-multiverse to date has been both straightforward and achievable. It builds directly upon the proven technologies of R-universe and GitHub Actions. By the end of the milestones, the entire project will be in a ready state to be launched to the public as a production solution for non-CRAN non-Bioconductor packages.\n\n\n\nFunded:\n$8,000\nProposed by:\nAidan Lakshman, University of Pittsburgh\nSummary:\nBiostrings is a core Bioconductor package providing efficient containers for storing, manipulating, and analyzing biological sequences. Biostrings is the method to access biological sequence data in R; nearly every analysis working with genomic data depends on the Biostrings package to handle sequencing data.\nThis project proposes to clear out accumulated technical debt by addressing open issues, implementing robust tests for long-term sustainability, improving user experience, and adding features that will keep Biostrings relevant for modern sequencing technologies. For end-users, this will result in numerous bugfixes, a host of new features to support genomic analyses, and a variety of performance improvements to bolster R as one of the top programming languages for bioinformatics. For developers, this will make the Biostrings package more sustainable, allowing for more community contribution and faster bug resolution in the future.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon, cynkra\nSummary:\nThis project is aimed at improving the quality of igraph codebase itself and of the user interface (messages including error messages, documentation indicating the status of exported functions). It has the goal of improving the user-friendliness of the installation from source.\n\n\n\nFunded:\n$15,912\nProposed by:\nEric Scott, University of Arizona\nSummary:\nThe goal of this project is to create a package that makes using targets for geospatial analysis in R as seamless as possible. To that end, geotargets will provide custom functions for defining geospatial targets that take care of translating and saving R objects for the user. In addition, the project will provide vignettes demonstrating how to use various geospatial R packages with targets. Where appropriate, the project will identify contributions to existing R packages to make them easier to use with targets and geotargets." }, { - "objectID": "all-projects/2018-group-2.html#funded-isc-grants-2018-2", - "href": "all-projects/2018-group-2.html#funded-isc-grants-2018-2", + "objectID": "all-projects/2019-group-1.html", + "href": "all-projects/2019-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n\n\n\nFunded:\n$46,050\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://blog.r-hub.io\nSummary:\nAfter the continuing technical progress of R-hub over the last two years, this project aims at catalizing its adoption by R package developers of all levels through developer advocacy. Indeed, R-hub is currently a successful and very valuable project, but it is not documented thoroughly, which hinders its wider adoption by package developers. This project shall answer this concern by three main actions: improving R-hub documentation, making R-hub better known in the community and making the R-hub web site more attractive to, and easier to use by, R developers and users via the ingestion of METACRAN services and the creation of a R-hub blog.\n\n\n\nFunded:\n$5,250\nProposed by:\nBenaiah Chibuokem Ubah\nWebsite:\nhttps://benubah.github.io/r-community-explorer/rugs.html\nSummary:\nThis project proposes an infrastructure that provides a data-driven approach to render the yearly activities of the R Consortium, by deploying web pages for discovering and tracking ISC Funded Projects, RUGS and Marketing activities. These pages are planned to appear like dashboards summarizing activities in interactive tables and charts, presenting several views, trends and insights to what R Consortium has achieved over time. The project hopes that presenting these achievements in a data-driven manner to the R community, the data science community and prospective R Consortium members will promote greater transparency, productivity and community inclusiveness around R Consortium activities.\n\n\n\nFunded:\n$50,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://rjpilot.netlify.app/\nSummary:\nThis project supports the operation of the R Journal. There are two aspects, one is to fund an editorial assistant to send reminders about reviews, and assist with typesetting and copyediting issues. The second part is to explore updating the technical operations of the journal production.\n\n\n\nFunded:\n$6,000\nProposed by:\nColin Fay\nWebsite:\nhttps://github.com/ThinkR-open/isc-proposal-licence/ and https://thinkr-open.github.io/licensing-r/intro.html#getting-a-more-global-idea and https://github.com/ThinkR-open/isc-proposal-licence/blob/master/proposal_licence.md\nSummary:\nLicensing is a vital part of Open Source. It provides guidelines for interacting with a program, and for making code accessible and reusable (or not). It provides a way to make code open source, in a way one wants to share it, protecting how it will be used and reused. Licensing is also challenging and complex: there are a lot of available licenses, and the choice is influenced by how you import and interact with elements from other packages and/or programs.\nWith this project, we propose to explore and document the current state of open source licenses in R, and to decipher compatibility and incompatibly elements inside these licenses, to help developers chose the best suited licence for their project.\n\n\n\nFunded:\n$25,000\nProposed by:\nClaus Wilke\nWebsite:\nhttps://wilkelab.org/gridtext/\nSummary:\nText is a key component of any data visualization. We need to label axes and legends, we need to annotate or highlight specific data points, and we need to provide plot titles and captions. The R graphics package ggplot2 provides numerous features to customize the labeling and annotation of plots, but ultimately it is limited by the current capabilities of the underlying graphics libary it uses, grid. Grid can draw simple text strings or mathematical expressions (via plotmath) in different colors, sizes, and fonts. However, it lacks functionality for changing formatting within a string (e.g., draw a single word in italics or in a different color), and it also cannot draw text boxes, where the text is enclosed in a box with defined margins, padding, or background color. This project will support the development of a new package, gridtext, that will alleviate these text formatting limitations. The project will also support efforts to make these new capabilities available from within ggplot2.\n\n\n\nFunded:\n$20,000\nProposed by:\nEmmanuel Blondel\nWebsite:\nSummary:\nThe project aims to strengthen the role of R in support of Spatial Data Infrastructures (SDI) management, through major enhancements of the geometa R package which offers tools for reading and writing ISO/OGC geographic metadata, including ISO 19115, 19110, and 19119 through the ISO 19139 XML format. This also extends to the Geographic Markup Language (GML - ISO 19136) used for describing geographic data. The use of geometa in combination with publication tools such as ows4R ( https://cran.r-project.org/package=ows4R ) and geosapi (https://cran.r-project.org/package=geosapi) fosters the use of R software to ease the management and publication of metadata documents and related datasets in web catalogues, and then allows to move forward with a real R implementation of spatial data management plans based on FAIR (Findable, Accessible Interoperable and Reusable) principles.\nThe workplan includes several activities such as working on the completeness of the ISO 19115 (ISO 19115-1 and 19115-2) data model in geometa, functions to read/write multilingual metadata documents, and an increased metadata validation capability with a validator targeting the EU INSPIRE directive. Finally, functions will be made available to convert between geometa ISO/OGC metadata objects and other known metadata objects such as NetCDF-CF and EML (Ecological Metadata Language) to foster metadata interoperability. By providing these R tools, we seek to facilitate the work of spatial data (GIS) managers, but also data scientists, whatever the thematic domain, whose daily tasks consist in handling data, describing them with metadata and publishing datasets.\n\n\n\nFunded:\n$6,000\nProposed by:\nEmi Tanaka\nWebsite:\nSummary:\nSymbolic model formulae define the structural component of a statistical model in an easier and often more accessible terms for practitioners. The earlier instance of symbolic model formulae for linear models was applied in Genstat with further generalisation by Wilkinson and Rogers (1973). Chambers and Hastie (1993) describe the symbolic model formulae implementation for linear models in the S language which remains much the same in the R language (Venables et al. 2018).\nLinear mixed models (LMMs) are widely used across many disciplines (e.g. ecology, psychology, agriculture, finance etc) due to its flexibility to model complex, correlated structures in the data. While the symbolic formula of linear models generally have a consistent representation and evaluation rule as implemented in stats::formula, this is not the case for LMMs. The inconsistency of symbolic formulae arises mainly in the representation of random effects, with the additional need to specify the variance-covariance structure of the random effects as well as structure of the associated model matrix that governs how the random effects are mapped to (groups of) the observational units. The differences give rise to confusion of equivalent model specification in different R-packages.\nThe lack of consistency in symbolic formula and model representation across mixed model software motivates the need to formulate a unified symbolic model formulae for LMMs with: (1) extension of the evaluation rules described in Wilkinson and Rogers (1973); and (2) ease of comprehension of the specified model for the user. This symbolic model formulae can be a basis for creating a common API to mixed models with wrappers to popular mixed model R-packages, thereby achieving a similar feat to parsnip R-package (Kuhn 2018) which implements a tidy unified interface to many predictive modelling functions (e.g. random forest, logistic regression, survival models etc).\nWe would like to find out what are your experiences with fitting linear mixed model in R! Please fill out the survey below to help us understand your problems: https://docs.google.com/forms/d/e/1FAIpQLSeblEoPtDmPS-dH2dmsHjLxLuKl19UY1JdmTrZux-AUSq3N7Q/viewform?usp=sf_link\n\n\n\nFunded:\n$10,000\nProposed by:\nChristoph Bodner, Florian Schwendinger, Thomas Laber\nWebsite:\nhttps://github.com/harlecin/serverless\nSummary:\nR is a great language for rapid prototyping and experimentation, but putting an R model in production is still more complex and time-consuming than it needs to be. With the growing popularity of serverless computing frameworks such as AWS Lambda and Azure Functions we see a a huge chance to allow R developers to more easily deploy their code into production. We want to build an R package called ‘serverless’ to allow R users to easily deploy scripts and custom R packages to AWS Lambda and in a second step to Azure Functions. Our main goal is to build a user-friendly cloud agnostic wrapper that can be extended to include additional cloud providers later on. We want to build on the work already done for deploying R functions to AWS Lambda by Philipp Schirmer and on the work already done by Neal Fultz and Gergely Daróczi on a gRPC client/server for R, which is necessary for Azure Functions. If you like our idea and want to help us, feel free to reach out to us on Github at https://github.com/harlecin/serverless\nBest,\nChristoph, Florian and Thomas" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n\n\n\nFunded:\n$13,912\nProposed by:\nRichard Webster\nWebsite:\nhttps://cheori.org/samplesize/\nSummary:\nSample size calculation and power analysis are fundamental for study design, yet they are challenging to do in the R programming language due to limited inter-package documentation. It is difficult to find the required functionality within the sea of open source packages. Indeed, there is no systematic R resource that allows users to search for whether a particular study design and corresponding statistical test has a power analysis implemented in R.\nOur aims are to improve usability of power analyses performed in R, to facilitate proper design and analysis of data, and promote reproducible research.\nOur duel approach is to create a Task View page for sample size calculations & power analyses, as well as a series of tutorials to reduce the R users’ learning curve. Addressing the usability of sample size calculation / power analyses will benefit a broad spectrum of R users, as this is a vital component for study design, result interpretability and reproducibility.\n\n\n\nFunded:\n$20,171\nProposed by:\nMartin Westgate\nWebsite:\nhttps://rmetaverse.github.io\nSummary:\nEvidence synthesis is the process of identifying, collating and summarizing primary scientific research to provide reliable, transparent summaries such as systematic reviews and meta-analyses. Despite their importance for linking research with policy, however, evidence synthesis projects are often time-consuming, expensive, and difficult to update. Open and reproducible workflows would help address these problems, but these workflows are poorly supported by the current package environment, preventing access by new users and hindering uptake of the well-developed suite of statistical tools for meta-analysis in R. The metaverse project will integrate and expand tools to support evidence synthesis and meta-research in R; suggest flexible workflows to complete these projects in a straightforward and open manner; and provide a collector package allowing easy access to these developments for new and experienced users.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttp://s2geometry.io/\nSummary:\nCurrently, a number of R spatial functions assume that coordinates are two-dimensional, taken from a “flat” space, and may or may not work for geographical (long/lat) coordinates, depicting points on a globe. This project will try to make such functions more robust and helpful for the the case of geographical coordinates. It will reconsider the concept of a bounding box, and build an interface to the S2 geometry library (http://s2geometry.io/), which powers several modern systems that assume geographic coordinates.\n\n\n\nFunded:\n$10,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftraj\nSummary:\nMovement defined broadly plays a central and growing role in fields as diverse as transportation, sport, ecology, music, medicine, and data science. Sampling movements results in tracking data, in the form of geographic (x,y,z) and temporal coordinates (t). Despite this common nature, there is a critical lack of standard infrastructure to deal with movement. With a sharp increase of the use of R for movement studies (more than 70 % of movement studies used R in 2018), the Movement community in R is at the same time very dynamic and very fragmented; in 2018 there was 57 packages that process, visualize and analyze tracking data, one third of which worked in isolation, not being linked to any other tracking package. We aim to develop a central trajectory class to support all stages of movement studies (pre-processing, post-processing and analysis).\nWe propose a sftraj package offering a generic and flexible approach. The only aim of the package will be to present a central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R. The first stage of the work will specifically involve the Movement community in R. During this stage, we will open contributions of use cases for the package (using GitHub’s issue system), which set practical goals for the development of the package. Use cases describe the workflow that is expected from both users’ and developers’ perspectives, and thus the capabilities that a trajectory package needs to offer. The package specifications and development will aim at addressing all use cases described, to make sure the solution provided is relevant for a wide array of users and package developers." }, { - "objectID": "all-projects/2020-group-1.html", - "href": "all-projects/2020-group-1.html", + "objectID": "all-projects/2019-group-1.html#funded-isc-grants-2019-1", + "href": "all-projects/2019-group-1.html#funded-isc-grants-2019-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n\n\n\nFunded:\n$4,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/rladies/starter-kit\nSummary:\nR-Ladies Global is a successful, growing organization aiming at increasing gender diversity in the R community. R-Ladies Global is a Top-Level Project of the ISC. R-Ladies Global guidance for starting and running a chapter, as well as overseeing chapters around the world, and for the rotating curator account, grew organically. The information is fragmented and exists in different formats: several Markdown and PDF Documents and wiki entries in a GitHub repository. This impedes the optimal finding of resources by those who need them, and also impedes contributions. This project aims to consolidate existing R-Ladies Global guidance into a well-structured and continuously deployed online book, with its source open on GitHub, as ( R ) Markdown documents woven together, and whose maintenance will be an R-Ladies major priority task.\nThe project will create a web based manuscript containing all the necessary information to understand what the R-Ladies organization is about, its structure and how to contribute to its mission. Information will be collated and organized leveraging the experience of R-Ladies organizers and volunteers that, over the past 4 years, contributed to the establishment and growth of one of the most active and successful communities in the data science realm. This book will be a crucial resource for R-Ladies and other organizations that are looking to consolidate or create their own guidance.\n\n\n\nFunded:\n$6,000\nProposed by:\nEtienne Racine\nWebsite:\nhttps://github.com/r-spatial/sfdbi\nSummary:\nManipulating spatial data in R sometimes requires interaction with a spatial database: the data doesn’t fit in memory, or simply because this is where the data is. The `sf` package already supports the PostGIS spatial database, but this project will extend the compatibility and make it easier to integrate in the `dplyr` workflow (with `dbplyr`). We also want to make it easier to add support for new database backends. We’ll create a new `sfdbi` package to centralize the interface between `sf` and databases and remove dependencies in `sf`. If you want to contribute, or if you’d like to suggest a database, make sure to join the `sfdbi` repo.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/ropensci-books/http-testing\nSummary:\nMore and more R packages access resources on the web, and play crucial roles in workflows: data access and updates for CRM reports (Hubspot APIs), for scientific publications (scientific web APIs, Open Science Framework). Like for all other packages, appropriate unit testing can make them more robust. Their unit testing brings special challenges: dependence of tests on a good internet connection, testing in the absence of authentication secrets, etc. Having tests fail due to resources being down or slow, during development or on CRAN, means a time loss for everyone involved (slower development, messages from CRAN). Although many packages accessing remote resources are well tested, there is a lack of resources around best practices for HTTP testing in packages using httr, crul, or curl. The best guidance to date about HTTP testing for R packages to our knowledge is a forum entry that pre-dates the development of relatively new packages for HTTP testing that have now been released on CRAN: vcr and webmockr by Scott Chamberlain, httptest by Neal Richardson, presser by Gábor Csárdi. This project aims at curating a free, central reference for developers of R packages accessing web resources, to help them have a faster and more robust development. We shall develop an useful guidance, in the form of a open-source web-based book.\n\n\n\nFunded:\n$35,000\nProposed by:\nOlga Vitek\nWebsite:\nhttps://github.com/kuwisdelu/matter\nSummary:\nThe project develops the MATTER 2.0 package for computing with larger-than-memory data in R. It extends the functionality of the existing MATTER package to any disk data format and in-memory layout. It also extends MATTER’s implementation with ALTREP to provide seamless interoperation with existing code, and various performance improvements critical for rapid prototyping of new statistical methods.\n\n\n\nFunded:\n$10,000\nProposed by:\nBenedikt Gräler\nWebsite:\nhttps://github.com/BenGraeler/STDataAndAnalytics/\nSummary:\nMany data sets are recorded irregular in space and time. Movement of people driving the spread of an disease, or the distribution of current and future cases are per se irregular spatiotemporal data and only two of many examples. Being able to easily visualise, aggregate and model irregular spatiotemporal data will help to better understand and forecast underlying processes. Filling the gap for irregular spatiotemporal data and providing direct interaction with analytical tools will ease the analysis for researchers. We will develop the sftime package to a mature state so that the suite of modern spatial and spatiotemporal data representations in R includes irregular spatiotemporal data. After doing this, we will modify the geostatistical modelling package gstat and the spatial copula modelling package spcopula to support the new data representation classes of sf, stars and sftime.\n\n\n\nFunded:\n$23,300\nProposed by:\nThibaut Jombart\nWebsite:\nhttps://www.repidemicsconsortium.org/2020-06-09-covid-challenge/\nSummary:\nThe RECON COVID-19 challenge aims to bring together the infectious disease modelling, epidemiology and R communities to improve analytics resources for the COVID-19 response via a website which will provide a platform to centralise, curate and update R development tasks relevant to the COVID-19 response. Similar to the Open Street Map Tasking Manager (tasks.hotosm.org), this platform will allow potential contributors to quickly identify outstanding tasks submitted by groups involved in the response to COVID-19 and ensure that developments follow the highest scientific and technical standards.\nWhile this project is aimed at leveraging R tools for helping to respond to COVID-19, we expect that it will lead to long-lasting developments of partnerships between the R and epidemiological communities, and that the resources developed will become key assets for supporting outbreak responses well beyond this pandemic.\n\n\n\nFunded:\n$5,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftrack\nSummary:\nsftrack’ is a modern approach for tracking data in R. In response to the large diversity of ad-hoc solutions, in part outdated, we propose a generic and flexible approach that support all stages of movement studies (pre-processing, post-processing and analysis). ‘sftrack’ provides two central classes for tracking data (points) and movement data (steps), and basic functions to build, handle, summarize and plot them. Version 1.0 of ‘sftrack’ will be finalized and submitted to CRAN, and will already incorporate converters from/to classes of major existing tracking packages. We will further work with all tracking package developers willing to fully integrate the solution offered by ‘sftrack’ into their package data flow." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n\n\n\nFunded:\n$13,912\nProposed by:\nRichard Webster\nWebsite:\nhttps://cheori.org/samplesize/\nSummary:\nSample size calculation and power analysis are fundamental for study design, yet they are challenging to do in the R programming language due to limited inter-package documentation. It is difficult to find the required functionality within the sea of open source packages. Indeed, there is no systematic R resource that allows users to search for whether a particular study design and corresponding statistical test has a power analysis implemented in R.\nOur aims are to improve usability of power analyses performed in R, to facilitate proper design and analysis of data, and promote reproducible research.\nOur duel approach is to create a Task View page for sample size calculations & power analyses, as well as a series of tutorials to reduce the R users’ learning curve. Addressing the usability of sample size calculation / power analyses will benefit a broad spectrum of R users, as this is a vital component for study design, result interpretability and reproducibility.\n\n\n\nFunded:\n$20,171\nProposed by:\nMartin Westgate\nWebsite:\nhttps://rmetaverse.github.io\nSummary:\nEvidence synthesis is the process of identifying, collating and summarizing primary scientific research to provide reliable, transparent summaries such as systematic reviews and meta-analyses. Despite their importance for linking research with policy, however, evidence synthesis projects are often time-consuming, expensive, and difficult to update. Open and reproducible workflows would help address these problems, but these workflows are poorly supported by the current package environment, preventing access by new users and hindering uptake of the well-developed suite of statistical tools for meta-analysis in R. The metaverse project will integrate and expand tools to support evidence synthesis and meta-research in R; suggest flexible workflows to complete these projects in a straightforward and open manner; and provide a collector package allowing easy access to these developments for new and experienced users.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttp://s2geometry.io/\nSummary:\nCurrently, a number of R spatial functions assume that coordinates are two-dimensional, taken from a “flat” space, and may or may not work for geographical (long/lat) coordinates, depicting points on a globe. This project will try to make such functions more robust and helpful for the the case of geographical coordinates. It will reconsider the concept of a bounding box, and build an interface to the S2 geometry library (http://s2geometry.io/), which powers several modern systems that assume geographic coordinates.\n\n\n\nFunded:\n$10,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftraj\nSummary:\nMovement defined broadly plays a central and growing role in fields as diverse as transportation, sport, ecology, music, medicine, and data science. Sampling movements results in tracking data, in the form of geographic (x,y,z) and temporal coordinates (t). Despite this common nature, there is a critical lack of standard infrastructure to deal with movement. With a sharp increase of the use of R for movement studies (more than 70 % of movement studies used R in 2018), the Movement community in R is at the same time very dynamic and very fragmented; in 2018 there was 57 packages that process, visualize and analyze tracking data, one third of which worked in isolation, not being linked to any other tracking package. We aim to develop a central trajectory class to support all stages of movement studies (pre-processing, post-processing and analysis).\nWe propose a sftraj package offering a generic and flexible approach. The only aim of the package will be to present a central class and basic functions to build, handle, summarize and plot movement data. Our project relies on three complementary pillars: a broad involvement of the movement community, a robust conceptual data model, and a sf-based implementation in R. The first stage of the work will specifically involve the Movement community in R. During this stage, we will open contributions of use cases for the package (using GitHub’s issue system), which set practical goals for the development of the package. Use cases describe the workflow that is expected from both users’ and developers’ perspectives, and thus the capabilities that a trajectory package needs to offer. The package specifications and development will aim at addressing all use cases described, to make sure the solution provided is relevant for a wide array of users and package developers." }, { - "objectID": "all-projects/2020-group-1.html#funded-isc-grants-2020-1", - "href": "all-projects/2020-group-1.html#funded-isc-grants-2020-1", + "objectID": "all-projects/2020-group-2.html", + "href": "all-projects/2020-group-2.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n\n\n\nFunded:\n$4,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/rladies/starter-kit\nSummary:\nR-Ladies Global is a successful, growing organization aiming at increasing gender diversity in the R community. R-Ladies Global is a Top-Level Project of the ISC. R-Ladies Global guidance for starting and running a chapter, as well as overseeing chapters around the world, and for the rotating curator account, grew organically. The information is fragmented and exists in different formats: several Markdown and PDF Documents and wiki entries in a GitHub repository. This impedes the optimal finding of resources by those who need them, and also impedes contributions. This project aims to consolidate existing R-Ladies Global guidance into a well-structured and continuously deployed online book, with its source open on GitHub, as ( R ) Markdown documents woven together, and whose maintenance will be an R-Ladies major priority task.\nThe project will create a web based manuscript containing all the necessary information to understand what the R-Ladies organization is about, its structure and how to contribute to its mission. Information will be collated and organized leveraging the experience of R-Ladies organizers and volunteers that, over the past 4 years, contributed to the establishment and growth of one of the most active and successful communities in the data science realm. This book will be a crucial resource for R-Ladies and other organizations that are looking to consolidate or create their own guidance.\n\n\n\nFunded:\n$6,000\nProposed by:\nEtienne Racine\nWebsite:\nhttps://github.com/r-spatial/sfdbi\nSummary:\nManipulating spatial data in R sometimes requires interaction with a spatial database: the data doesn’t fit in memory, or simply because this is where the data is. The `sf` package already supports the PostGIS spatial database, but this project will extend the compatibility and make it easier to integrate in the `dplyr` workflow (with `dbplyr`). We also want to make it easier to add support for new database backends. We’ll create a new `sfdbi` package to centralize the interface between `sf` and databases and remove dependencies in `sf`. If you want to contribute, or if you’d like to suggest a database, make sure to join the `sfdbi` repo.\n\n\n\nFunded:\n$16,000\nProposed by:\nMaëlle Salmon\nWebsite:\nhttps://github.com/ropensci-books/http-testing\nSummary:\nMore and more R packages access resources on the web, and play crucial roles in workflows: data access and updates for CRM reports (Hubspot APIs), for scientific publications (scientific web APIs, Open Science Framework). Like for all other packages, appropriate unit testing can make them more robust. Their unit testing brings special challenges: dependence of tests on a good internet connection, testing in the absence of authentication secrets, etc. Having tests fail due to resources being down or slow, during development or on CRAN, means a time loss for everyone involved (slower development, messages from CRAN). Although many packages accessing remote resources are well tested, there is a lack of resources around best practices for HTTP testing in packages using httr, crul, or curl. The best guidance to date about HTTP testing for R packages to our knowledge is a forum entry that pre-dates the development of relatively new packages for HTTP testing that have now been released on CRAN: vcr and webmockr by Scott Chamberlain, httptest by Neal Richardson, presser by Gábor Csárdi. This project aims at curating a free, central reference for developers of R packages accessing web resources, to help them have a faster and more robust development. We shall develop an useful guidance, in the form of a open-source web-based book.\n\n\n\nFunded:\n$35,000\nProposed by:\nOlga Vitek\nWebsite:\nhttps://github.com/kuwisdelu/matter\nSummary:\nThe project develops the MATTER 2.0 package for computing with larger-than-memory data in R. It extends the functionality of the existing MATTER package to any disk data format and in-memory layout. It also extends MATTER’s implementation with ALTREP to provide seamless interoperation with existing code, and various performance improvements critical for rapid prototyping of new statistical methods.\n\n\n\nFunded:\n$10,000\nProposed by:\nBenedikt Gräler\nWebsite:\nhttps://github.com/BenGraeler/STDataAndAnalytics/\nSummary:\nMany data sets are recorded irregular in space and time. Movement of people driving the spread of an disease, or the distribution of current and future cases are per se irregular spatiotemporal data and only two of many examples. Being able to easily visualise, aggregate and model irregular spatiotemporal data will help to better understand and forecast underlying processes. Filling the gap for irregular spatiotemporal data and providing direct interaction with analytical tools will ease the analysis for researchers. We will develop the sftime package to a mature state so that the suite of modern spatial and spatiotemporal data representations in R includes irregular spatiotemporal data. After doing this, we will modify the geostatistical modelling package gstat and the spatial copula modelling package spcopula to support the new data representation classes of sf, stars and sftime.\n\n\n\nFunded:\n$23,300\nProposed by:\nThibaut Jombart\nWebsite:\nhttps://www.repidemicsconsortium.org/2020-06-09-covid-challenge/\nSummary:\nThe RECON COVID-19 challenge aims to bring together the infectious disease modelling, epidemiology and R communities to improve analytics resources for the COVID-19 response via a website which will provide a platform to centralise, curate and update R development tasks relevant to the COVID-19 response. Similar to the Open Street Map Tasking Manager (tasks.hotosm.org), this platform will allow potential contributors to quickly identify outstanding tasks submitted by groups involved in the response to COVID-19 and ensure that developments follow the highest scientific and technical standards.\nWhile this project is aimed at leveraging R tools for helping to respond to COVID-19, we expect that it will lead to long-lasting developments of partnerships between the R and epidemiological communities, and that the resources developed will become key assets for supporting outbreak responses well beyond this pandemic.\n\n\n\nFunded:\n$5,000\nProposed by:\nMathieu Basille\nWebsite:\nhttps://github.com/mablab/sftrack\nSummary:\nsftrack’ is a modern approach for tracking data in R. In response to the large diversity of ad-hoc solutions, in part outdated, we propose a generic and flexible approach that support all stages of movement studies (pre-processing, post-processing and analysis). ‘sftrack’ provides two central classes for tracking data (points) and movement data (steps), and basic functions to build, handle, summarize and plot them. Version 1.0 of ‘sftrack’ will be finalized and submitted to CRAN, and will already incorporate converters from/to classes of major existing tracking packages. We will further work with all tracking package developers willing to fully integrate the solution offered by ‘sftrack’ into their package data flow." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n\n\n\nFunded:\n$46,800\nProposed by:\nJeroen Ooms\nSummary:\nAs of R 4.0.0 (released April 2020), R for Windows uses a brand new toolchain bundle called rtools40. This version upgrades the mingw-gcc toolchains to version 8.3.0, and introduces a powerful new build system based on the widely used msys2 platform, which makes it easier to maintain R itself, as well as system libraries needed for developing R and R-packages.\nThe current project seeks to build out this system to improve tooling for building and debugging on Windows, and move towards a scalable build infrastructure, which is transparent, extensible, and fully automated. Thereby we can empower development on Windows, and support further growth of the R ecosystem while relieving work for CRAN and R-core members.\n\n\n\nFunded:\n$9,688\nProposed by:\nChun Fung Kwok\nWebsite:\nhttps://github.com/kcf-jackson/sketch and https://cran.r-project.org/package=sketch\nSummary:\nThis project aims to make creating flexible interactive visualisation accessible to a wider R community. By implementing an R-to-JavaScript transpiler, i.e. a program that translates R code into JavaScript code, it lets R users develop JavaScript(JS) applications using solely the R syntax. This eliminates the need to pick up an entire new language, makes it easy for R users to learn and experiment with JS technologies and gives direct and full access to all existing JS libraries. The transpiler is distributed as a regular R package, and it can be used standalone or to complement existing packages, including Rmarkdown, shiny and V8." }, { - "objectID": "all-projects/funded-projects.html", - "href": "all-projects/funded-projects.html", - "title": "Recipients of ISC Grants", + "objectID": "all-projects/2020-group-2.html#funded-isc-grants-2020-2", + "href": "all-projects/2020-group-2.html#funded-isc-grants-2020-2", + "title": "R Consortium", "section": "", - "text": "Recipients of ISC Grants\n2024 (group 1)\n\nModular, interoperable, and extensible topological data analysis in R\nISO 19115-3 standard implementation in geometa R package\nR-multiverse for production\nCritical Updates to Biostrings\nSetting up igraph for success in the next decade\n{geotargets}: Enabling geospatial workflow management with {targets}\n\n2023 (group 2)\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nCausal Inference in a Box\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n2023 (group 1)\n\nThe future of DBI (extension 1)\nSecure TLS Communications for R\nvolcalc: Calculate predicted volatility of chemical compounds\nautotest: Automated testing of R packages\napi2r: An R Package for Auto-Generating R API Clients\n\n2022 (group 2)\n\nD3po: R Package for Easy Interactive D3 Visualization With Shiny\nTooling and Guidance for Translations of Markdown-Based R Content  Quarto, R Markdown\nOnline Submission and Review Infrastructure for the R Journal\nUpgrading SatRdays Website Template\nBuilding the “Spatial Data Science With R” Educational Materials and Pedagogical Infrastructure\n\n2022 (group 1)\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n2021 (group 2)\n\nPreparing CRAN for the Retirement of rgdal, rgeos and maptools\nR Package for the ICESat-2 Altimeter Data\nThe Future of DBI\nData Science and Machine Learning Training Workshop Using R Programming Language\n\n2021 (group 1)\n\nAccounting/Auditing Gap-Analysis\nExtendr - Rust extensions for R.\nGoogle Earth Engine with R\nImproving Translations in R\nMinimizing wastage of blood products\nR for Engineering Applications\nSetting up an R-Girls-Schools Network\ndeposits: Deposit Research Data Anywhere\n\n2020 (group 2)\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n2020 (group 1)\n\nConsolidating R-Ladies Global organisational guidance and wisdom\nDatabase interoperability for spatial objects in R\nHTTP testing in R Book\nMATTER 2.0: larger-than-memory data for R\nSpatiotemporal Data and Analytics\nThe RECON COVID-19 challenge: leveraging the R community to improve COVID-19 analytics resources\nsftrack v1.0: Stable API for a broad adoption\n\n2019 (group 2)\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n2019 (group 1)\n\nEnhancing usability of sample size calculations and power analyses in R with a Task View page and accompanying tutorials\nExpanding the ‘metaverse’; an R ecosystem for meta-research\nR-global: analysing spatial data globally\nsftraj: A central class for tracking and movement data\n\n2018 (group 2)\n\nCatalyzing R-hub adoption through R package developer advocacy\nData-Driven Discovery and Tracking of R Consortium Activities\nEditorial assistance for the R Journal\nLicensing R - Guidelines and tools\nNext-generation text layout in grid and ggplot2\nStrengthening of R in support of spatial data infrastructures management : geometa and ows4R R packages\nSymbolic Formulae for Linear Mixed Models\nserveRless\n\n2018 (group 1)\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n2017 (group 2)\n\nAn Earth data processing backend for testing and evaluating stars\nFuture Minimal API: Specification with Backend Conformance Test Suite\nQuantities for R\nRefactoring and updating the SWIG R module\n\n2017 (group 1)\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n2016 (group 2)\n\nInteractive data manipulation in mapview\nR Documentation Task Force\n\n2016 (group 1)\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nDevelopment and maintenance of the Windows build infrastructure (Top level project proposal)\nInteractive visualisations in R via R-to-JavaScript-transpilation\n\n\n\n\nFunded:\n$46,800\nProposed by:\nJeroen Ooms\nSummary:\nAs of R 4.0.0 (released April 2020), R for Windows uses a brand new toolchain bundle called rtools40. This version upgrades the mingw-gcc toolchains to version 8.3.0, and introduces a powerful new build system based on the widely used msys2 platform, which makes it easier to maintain R itself, as well as system libraries needed for developing R and R-packages.\nThe current project seeks to build out this system to improve tooling for building and debugging on Windows, and move towards a scalable build infrastructure, which is transparent, extensible, and fully automated. Thereby we can empower development on Windows, and support further growth of the R ecosystem while relieving work for CRAN and R-core members.\n\n\n\nFunded:\n$9,688\nProposed by:\nChun Fung Kwok\nWebsite:\nhttps://github.com/kcf-jackson/sketch and https://cran.r-project.org/package=sketch\nSummary:\nThis project aims to make creating flexible interactive visualisation accessible to a wider R community. By implementing an R-to-JavaScript transpiler, i.e. a program that translates R code into JavaScript code, it lets R users develop JavaScript(JS) applications using solely the R syntax. This eliminates the need to pick up an entire new language, makes it easy for R users to learn and experiment with JS technologies and gives direct and full access to all existing JS libraries. The transpiler is distributed as a regular R package, and it can be used standalone or to complement existing packages, including Rmarkdown, shiny and V8." }, { - "objectID": "all-projects/2017-group-1.html", - "href": "all-projects/2017-group-1.html", + "objectID": "all-projects/2023-group-2.html", + "href": "all-projects/2023-group-2.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n\n\n\nFunded:\n$15,000\nProposed by:\nDirk Eddelbuettel\nSummary:\nThis project proposes to take the creation of binary Linux packages to the next level by providing R-Hub and eventually CRAN with the ability to deliver directly installable binary packages with properly-resolved dependencies. This will allow large-scale automated use of CRAN packages anywhere: laptops, desktops, servers, cluster farms and cloud-based deployments. The project would like to hear from anyone who could possibly host a dedicated server in a rack for long term use.\n\n\n\nFunded:\n$12,000\nProposed by:\nJeroen Ooms\nSummary:\nWhen installing CRAN packages, Windows and MacOS users often rely on binary packages that contain precompiled source code and any required external C/C++ libraries. By eliminating the need to setup a full compiler environment or manage external libraries this tremendously improves the usability of R on these platforms. Our project will improve the system by adapting the popular homebrew system to facilitate static linking of external libraries\n\n\n\nFunded:\n$32,000\nProposed by:\nHeather Turner\nWebsite:\nhttps://github.com/satrdays\nSummary:\nThis project will evaluate a number of open source conference management systems to assess their suitability for use with useR! and satRdays. Test versions of these systems will be set up to test their functionality and ease of use for all roles (systems administrator, local organizer, program chair, reviewer, conference participant). A system will be selected and a production system set up, with a view to be ready for useR! 2018 and future satRdays events.\n\n\n\nFunded:\n$15,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://wiki.r-consortium.org/view/Distributed_Computing_Working_Group and https://github.com/vertica/ddR/wiki/Design\nSummary:\nThe ISC’s Distributed Computing Working Group explores ways of enabling distributed computing in R. One of its outputs, the CRAN package ddR, defines an idiomatic API that abstracts different distributed computing engines, such as DistributedR and potentially Spark and TensorFlow. The goal of the project is to enable R users to interact with familiar data structures and write code that is portable across distributed systems. The working group will use this R Consortium grant to fund an internship to help improve ddR and implement support for one or more additional backends. Please contact Michael Lawrence to apply or request additional information.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nGetting data in and out of R is an important part of a statistician’s or data scientist’s work. If the data reside in a database, this is best done with a backend to DBI, R’s native DataBase Interface. The ongoing “Improving DBI” project supports the specification of DBI, both in prose and as an automated test, and also the adaptation of the `RSQLite` package to these specs. This follow-up project aims at implementing modern, fully spec-compliant DBI backends to two major open-source RDBMS, MySQL/MariaDB and PostgreSQL.\n\n\n\nFunded:\n$25,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://forwards.github.io/edu/workshops/\nSummary:\nThe proportion of female package authors and maintainers has remained persistently low, at best at 15%, despite 20 years of the R project’s existence. This project will conduct a grassroots effort to increase the participation of women in the R community. One day package development workshops for women engaged in research will be held in Melbourne, Australia and Auckland, New Zealand in 2017, and at locations yet to be determined in the USA and Europe in 2018. Additionally, one day workshops for teenage girls focused on building Shiny apps will be developed to encourage an interest in programming. These will be rolled out in the same locations as the women’s workshops. All materials developed will be made available under a Creative Commons share-alike license on the Forwards website (http://forwards.github.io).\n\n\n\nFunded:\n$11,000\nProposed by:\nKirill Müller\nWebsite:\nhttps://github.com/krlmlr/profile and https://cran.r-project.org/web/packages/profile/index.html\nSummary:\nR has excellent facilities for profiling R code: the main entry point is the [`Rprof()`](https://www.rdocumentation.org/packages/utils/versions/3.3.2/topics/Rprof) function that starts an execution mode where the R call stack is sampled periodically, optionally at source line level, and written to a file. Profiling results can be analyzed with `summaryRprof()`, or visualized using the `profvis`, `aprof`, or `GUIProfiler` packages. However, the execution time of native code is only available in bulk, without detailed source information. This project aims at bridging this gap with a drop-in replacement to `Rprof()` that records call stacks and memory usage information at both R and native levels, and later commingles them to present a unified view to the user.\n\n\n\nFunded:\n$11,200\nProposed by:\nHeidi Seibold\nSummary:\nSchool of Data is a network of data literacy practitioners, both organizations and individuals, implementing training and other data literacy activities in their respective countries and regions. Members of School of Data work to empower civil society organizations (CSOs), journalists, civil servants and citizens with the skills they need to use data effectively in their efforts to create better, more equitable and more sustainable societies Our R consortium will develop learning materials about R for journalists, with a focus on making them accessible and relevant to journalists from various countries. As a consequence, our content will use country-relevant examples and will be translated in several languages (English, French, Spanish, German).\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://cran.r-project.org/web/packages/stars/index.html\nSummary:\nSpatiotemporal and raster data often come as dense, two-dimensional arrays while remote sensing and climate model data are often presented as higher dimensional arrays. Data sets of this kind often do not fit in main memory. This project will make it easier to handle such data with R by using dplyr-style, pipe-based workflows, and also consider the case where the data reside remotely, in a cloud environment. Questions and offers to support are welcome through issues at: https://github.com/edzer/stars" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n\n\n\nFunded:\n$1,000\nProposed by:\nBinod Jung Bogati, R User Group Nepal\nSummary:\nThis project aims to bridge language gaps within the R community by translating essential R resources into Nepali. This inclusivity will attract diverse talents and perspectives, fostering innovation and growth within the community. We are working with the R User Group Nepal community for a series of Translation hackathons and follow-up meetings. This initiative started before the R Project Sprint 2023 with the assistance of the R User Group Nepal.\n\n\n\nFunded:\n$1,306.80\nProposed by:\nDan Wilson, The Data Collective Consulting Pty Ltd\nSummary:\nTo help create a place for social connection to the broad R community that isn’t focussed on any specific subgroup of r users, we’d like funding to help establish an RStats Mastodon server. The goal would be to be funded for the first year with a grant from the R Consortium and develop a pathway for user funding like other Mastodon servers.\n\n\n\nFunded:\n$20,800\nProposed by:\nElio Campitelli\nSummary:\nWe propose a system in which either package maintainers or community members could create translation modules of specific packages. Users would then be able to install those translation modules and browse their documentation. By default, help() would display the documentation in the user’s preferred language if available, and fall-back to the canonical documentation otherwise. It would also include a link to the canonical documentation and warnings if translations are not up to date.\n\n\n\nFunded:\n$5,000\nProposed by:\nMalcolm Barrett\nSummary:\nIn response to a growing demand for accessible and comprehensive educational resources in causal inference within the R community, we propose the development of a Causal Inference In a Box course. Leveraging a “teach the teacher” model and building on the successful Data Science in a Box template, we will provide instructional materials, including slide decks, lab exercises, and assessments, all meticulously designed to facilitate effective learning. Additionally, we are committed to ensuring inclusivity by offering alternative formats for diverse learning preferences. This comprehensive course, supported by dedicated pedagogical software tools, will revolutionize how practitioners approach causal inference in the R environment, ultimately enhancing the quality and reliability of their research and analyses.\n\n\n\nFunded:\n$4,000\nProposed by:\nDianne Cook\nSummary:\nThe plan for the use of this funding is to check and enhance the accessibility of published R Journal articles, and to develop tools to help authors and editors ensure that new R Journal articles are at the cutting edge of accessibility. Checking the published articles will involve manual work to read each article and add meaningful alt text to each image. Screen reader accessibility will be checked using available screen readers, with advice from team member Jonathan Godfrey. Jonathan has already used the screen reader JAWS to read a sample of articles converted from the legacy format and confirms that he can now access 90% of the R Journal content as opposed to 10% previously! We will also work closely with the current editors of the R Journal to assist with checking new submissions, especially those produced with the legacy template. This will also help ensure that new articles have accessible content, with appropriate alt text.\n\n\n\nFunded:\n$40,000\nProposed by:\nJeroen Ooms, rOpenSci\nSummary:\nWe are interested to collaborate with the R consortium to make R-universe a top-level ISC in order to get a variety of stakeholders involved, grow adoption and community ownership, and to be able to guarantee the continued availability of the service to the R community. R-universe has the potential to become the central place where one can find everything the R community has to offer, complementing CRAN with open infrastructure that can continuously be adapted to new needs. Moreover, existing r-hub containers for extra checks can be integrated to make these tools more accessible. We hope to become a flagship project for the consortium, and an example of a mutually beneficial collaboration between its members and the R community.\n\n\n\nFunded:\n$24,000\nProposed by:\nAndreas Neudecker, INWT Statistics GmbH\nSummary:\nThe goal of this project is to create a robust and efficient Kafka client library for R that supports essential functionalities to communicate with a Kafka cluster. The proposed Kafka client for R will be built by creating a wrapper around the C++ librdkafka library, which is maintained and developed by Confluent which was founded by the original developers of Kafka. This approach is already common and produces reliable and stable releases in multiple other programming languages (Python, Rust, Go, …). There are packages for the major linux package managers (Debian, RPM, Gentoo) and it also runs on MacOS X and Windows." }, { - "objectID": "all-projects/2017-group-1.html#funded-isc-grants-2017-1", - "href": "all-projects/2017-group-1.html#funded-isc-grants-2017-1", + "objectID": "all-projects/2023-group-2.html#funded-isc-grants-2023-2", + "href": "all-projects/2023-group-2.html#funded-isc-grants-2023-2", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAdding Linux Binary Builders to CRAN\nAn infrastructure for building R packages on MacOS Abstract with homebrew\nConference Management System for R Consortium Supported Conferences\nContinued Development of the R API for Distributed Computing\nEstablishing DBI\nForwards Workshops for Women and Girls\nJoint profiling of native and R code\nSchool of Data Material Development\nstars: Scalable, spatiotemporal tidy arrays for R\n\n\n\n\nFunded:\n$15,000\nProposed by:\nDirk Eddelbuettel\nSummary:\nThis project proposes to take the creation of binary Linux packages to the next level by providing R-Hub and eventually CRAN with the ability to deliver directly installable binary packages with properly-resolved dependencies. This will allow large-scale automated use of CRAN packages anywhere: laptops, desktops, servers, cluster farms and cloud-based deployments. The project would like to hear from anyone who could possibly host a dedicated server in a rack for long term use.\n\n\n\nFunded:\n$12,000\nProposed by:\nJeroen Ooms\nSummary:\nWhen installing CRAN packages, Windows and MacOS users often rely on binary packages that contain precompiled source code and any required external C/C++ libraries. By eliminating the need to setup a full compiler environment or manage external libraries this tremendously improves the usability of R on these platforms. Our project will improve the system by adapting the popular homebrew system to facilitate static linking of external libraries\n\n\n\nFunded:\n$32,000\nProposed by:\nHeather Turner\nWebsite:\nhttps://github.com/satrdays\nSummary:\nThis project will evaluate a number of open source conference management systems to assess their suitability for use with useR! and satRdays. Test versions of these systems will be set up to test their functionality and ease of use for all roles (systems administrator, local organizer, program chair, reviewer, conference participant). A system will be selected and a production system set up, with a view to be ready for useR! 2018 and future satRdays events.\n\n\n\nFunded:\n$15,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://wiki.r-consortium.org/view/Distributed_Computing_Working_Group and https://github.com/vertica/ddR/wiki/Design\nSummary:\nThe ISC’s Distributed Computing Working Group explores ways of enabling distributed computing in R. One of its outputs, the CRAN package ddR, defines an idiomatic API that abstracts different distributed computing engines, such as DistributedR and potentially Spark and TensorFlow. The goal of the project is to enable R users to interact with familiar data structures and write code that is portable across distributed systems. The working group will use this R Consortium grant to fund an internship to help improve ddR and implement support for one or more additional backends. Please contact Michael Lawrence to apply or request additional information.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nGetting data in and out of R is an important part of a statistician’s or data scientist’s work. If the data reside in a database, this is best done with a backend to DBI, R’s native DataBase Interface. The ongoing “Improving DBI” project supports the specification of DBI, both in prose and as an automated test, and also the adaptation of the `RSQLite` package to these specs. This follow-up project aims at implementing modern, fully spec-compliant DBI backends to two major open-source RDBMS, MySQL/MariaDB and PostgreSQL.\n\n\n\nFunded:\n$25,000\nProposed by:\nDianne Cook\nWebsite:\nhttps://forwards.github.io/edu/workshops/\nSummary:\nThe proportion of female package authors and maintainers has remained persistently low, at best at 15%, despite 20 years of the R project’s existence. This project will conduct a grassroots effort to increase the participation of women in the R community. One day package development workshops for women engaged in research will be held in Melbourne, Australia and Auckland, New Zealand in 2017, and at locations yet to be determined in the USA and Europe in 2018. Additionally, one day workshops for teenage girls focused on building Shiny apps will be developed to encourage an interest in programming. These will be rolled out in the same locations as the women’s workshops. All materials developed will be made available under a Creative Commons share-alike license on the Forwards website (http://forwards.github.io).\n\n\n\nFunded:\n$11,000\nProposed by:\nKirill Müller\nWebsite:\nhttps://github.com/krlmlr/profile and https://cran.r-project.org/web/packages/profile/index.html\nSummary:\nR has excellent facilities for profiling R code: the main entry point is the [`Rprof()`](https://www.rdocumentation.org/packages/utils/versions/3.3.2/topics/Rprof) function that starts an execution mode where the R call stack is sampled periodically, optionally at source line level, and written to a file. Profiling results can be analyzed with `summaryRprof()`, or visualized using the `profvis`, `aprof`, or `GUIProfiler` packages. However, the execution time of native code is only available in bulk, without detailed source information. This project aims at bridging this gap with a drop-in replacement to `Rprof()` that records call stacks and memory usage information at both R and native levels, and later commingles them to present a unified view to the user.\n\n\n\nFunded:\n$11,200\nProposed by:\nHeidi Seibold\nSummary:\nSchool of Data is a network of data literacy practitioners, both organizations and individuals, implementing training and other data literacy activities in their respective countries and regions. Members of School of Data work to empower civil society organizations (CSOs), journalists, civil servants and citizens with the skills they need to use data effectively in their efforts to create better, more equitable and more sustainable societies Our R consortium will develop learning materials about R for journalists, with a focus on making them accessible and relevant to journalists from various countries. As a consequence, our content will use country-relevant examples and will be translated in several languages (English, French, Spanish, German).\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://cran.r-project.org/web/packages/stars/index.html\nSummary:\nSpatiotemporal and raster data often come as dense, two-dimensional arrays while remote sensing and climate model data are often presented as higher dimensional arrays. Data sets of this kind often do not fit in main memory. This project will make it easier to handle such data with R by using dplyr-style, pipe-based workflows, and also consider the case where the data reside remotely, in a cloud environment. Questions and offers to support are welcome through issues at: https://github.com/edzer/stars" + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nTranslating R to Nepali\nRStats Mastodon Server\nTooling for internationalization of R help pages\nAccessibility Enhancements for the R Journal\nTaking r-universe to the next level\nR Kafka Client\n\n\n\n\nFunded:\n$1,000\nProposed by:\nBinod Jung Bogati, R User Group Nepal\nSummary:\nThis project aims to bridge language gaps within the R community by translating essential R resources into Nepali. This inclusivity will attract diverse talents and perspectives, fostering innovation and growth within the community. We are working with the R User Group Nepal community for a series of Translation hackathons and follow-up meetings. This initiative started before the R Project Sprint 2023 with the assistance of the R User Group Nepal.\n\n\n\nFunded:\n$1,306.80\nProposed by:\nDan Wilson, The Data Collective Consulting Pty Ltd\nSummary:\nTo help create a place for social connection to the broad R community that isn’t focussed on any specific subgroup of r users, we’d like funding to help establish an RStats Mastodon server. The goal would be to be funded for the first year with a grant from the R Consortium and develop a pathway for user funding like other Mastodon servers.\n\n\n\nFunded:\n$20,800\nProposed by:\nElio Campitelli\nSummary:\nWe propose a system in which either package maintainers or community members could create translation modules of specific packages. Users would then be able to install those translation modules and browse their documentation. By default, help() would display the documentation in the user’s preferred language if available, and fall-back to the canonical documentation otherwise. It would also include a link to the canonical documentation and warnings if translations are not up to date.\n\n\n\nFunded:\n$5,000\nProposed by:\nMalcolm Barrett\nSummary:\nIn response to a growing demand for accessible and comprehensive educational resources in causal inference within the R community, we propose the development of a Causal Inference In a Box course. Leveraging a “teach the teacher” model and building on the successful Data Science in a Box template, we will provide instructional materials, including slide decks, lab exercises, and assessments, all meticulously designed to facilitate effective learning. Additionally, we are committed to ensuring inclusivity by offering alternative formats for diverse learning preferences. This comprehensive course, supported by dedicated pedagogical software tools, will revolutionize how practitioners approach causal inference in the R environment, ultimately enhancing the quality and reliability of their research and analyses.\n\n\n\nFunded:\n$4,000\nProposed by:\nDianne Cook\nSummary:\nThe plan for the use of this funding is to check and enhance the accessibility of published R Journal articles, and to develop tools to help authors and editors ensure that new R Journal articles are at the cutting edge of accessibility. Checking the published articles will involve manual work to read each article and add meaningful alt text to each image. Screen reader accessibility will be checked using available screen readers, with advice from team member Jonathan Godfrey. Jonathan has already used the screen reader JAWS to read a sample of articles converted from the legacy format and confirms that he can now access 90% of the R Journal content as opposed to 10% previously! We will also work closely with the current editors of the R Journal to assist with checking new submissions, especially those produced with the legacy template. This will also help ensure that new articles have accessible content, with appropriate alt text.\n\n\n\nFunded:\n$40,000\nProposed by:\nJeroen Ooms, rOpenSci\nSummary:\nWe are interested to collaborate with the R consortium to make R-universe a top-level ISC in order to get a variety of stakeholders involved, grow adoption and community ownership, and to be able to guarantee the continued availability of the service to the R community. R-universe has the potential to become the central place where one can find everything the R community has to offer, complementing CRAN with open infrastructure that can continuously be adapted to new needs. Moreover, existing r-hub containers for extra checks can be integrated to make these tools more accessible. We hope to become a flagship project for the consortium, and an example of a mutually beneficial collaboration between its members and the R community.\n\n\n\nFunded:\n$24,000\nProposed by:\nAndreas Neudecker, INWT Statistics GmbH\nSummary:\nThe goal of this project is to create a robust and efficient Kafka client library for R that supports essential functionalities to communicate with a Kafka cluster. The proposed Kafka client for R will be built by creating a wrapper around the C++ librdkafka library, which is maintained and developed by Confluent which was founded by the original developers of Kafka. This approach is already common and produces reliable and stable releases in multiple other programming languages (Python, Rust, Go, …). There are packages for the major linux package managers (Debian, RPM, Gentoo) and it also runs on MacOS X and Windows." }, { - "objectID": "all-projects/2016-group-1.html", - "href": "all-projects/2016-group-1.html", + "objectID": "all-projects/2018-group-1.html", + "href": "all-projects/2018-group-1.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training\n\n\n\n\nFunded:\n$10,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://github.com/RConsortium/Distributed-Computing-WG\nSummary:\nMany Big Data platforms expose R-based interfaces that lack standardization and are therefore difficult to learn. This project will develop a common framework to simplify and standardize how users program distributed applications in R, ultimately reducing duplication of effort.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDatabase access is an important cornerstone of the R ecosystem, but today’s specifications – data type transformation, return values, error conditions – remain vague and result in data analysis errors. This project aims to improve database access in R so that porting code is simplified and less prone to error.\n\n\n\nFunded:\n$10,000\nProposed by:\nMark Hornick\nWebsite:\nhttps://riotworkshop.github.io/\nSummary:\nRIOT 2016 is a one-day workshop to unite R language developers, identify R language development and tooling opportunities, increase involvement of the R user community and more.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Cotton\nWebsite:\nhttps://github.com/RL10N/RL10N and https://libraries.io/github/RL10N\nSummary:\nAlthough the R language is used globally, very few R packages are available in languages other than English. The RL10N project will make it easier for R developers to include translations in their own packages.\n\n\n\nFunded:\n$10,000\nProposed by:\nStephanie Locke\nWebsite:\nhttps://github.com/satrdays\nSummary:\n“SatRDays” are community-led, regional conferences to support collaboration, networking and innovation within the R community. Initially three events will be hosted, with plans for additional meet-ups as the R user base grows.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://github.com/r-spatial/sf/\nSummary:\nUsing the “Simple Features” standard supported by the Open Geospatial Consortium and the International Organization for Standardization, this tool will simplify analysis on modern geospatial data.\n\n\n\nFunded:\n$10,000\nProposed by:\nLaurent Gatto\nWebsite:\nSummary:\nThis two-day in-person training course will introduce the basics of R programming and address the growing demand for training resources for the R language." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n\n\n\nFunded:\n$14,000\nProposed by:\nJulie Josse\nWebsite:\nhttps://cran.r-project.org/web/views/MissingData.html\nSummary:\nThe objective is to create a reference platform on the theme of missing data management and to federate contributors. This platform will be the occasion to list the existing packages, the available literature as well as the tutorials that allow to analyze data with missing data. New work on the subject can be easily integrated and we will create examples of analysis workflows with missing data. Anyone who would like to contribute to this exciting project can contact us.\n\n\n\nFunded:\n$10,000\nProposed by:\nFrançois Michonneau\nWebsite:\nhttps://datacarpentry.org/R-ecology-lesson/ and http://swcarpentry.github.io/r-novice-gapminder/\nSummary:\nThe first-class implementation of literate programming in R is one of the reasons for its success. While the seamless integration of code and text made possible by Sweave, knitr, and rmarkdown was designed for writing reproducible reports and documentation, it has also enabled the creation of teaching materials that combine text, code examples, exercises and solutions. However, while people creating lessons in RMarkdown are familiar with R, they often do not have a background in education or UX design. Therefore, they must not only assemble curriculum, but also find a way to present the content effectively and accessibly to both learners and instructors. As the model of open source development is being adapted to the creation of open educational resources, the difficulty to share materials due to a lack of consistency in their construction hinders the collaborative development of these resources.\nThis project will develop an R package that will facilitate the development of consistent teaching resources. It will encourage the use of tools and lesson structure that support and improve learning. By providing the technical framework for developing quality teaching materials, we seek to encourage collaborative lesson development by letting authors focus on the content rather than the formatting, while providing a more consistent experience for the learners.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDBI, R’s database interface, is a set of methods declared in the DBI R package. Communication with the database is implemented by DBI backends, packages that import DBI and implement its methods. A common interface is helpful for both users and backend implementers.\nThe “Maintaining DBI” is a follow-up project to two previous projects supported by the R Consortium, and is mostly about providing ongoing maintenance and support for DBI, the DBItest test suite, and the three backends to open-source databases (RSQLite, RMariaDB and RPostgres) that have been implemented as part of the previous projects.\n\n\n\nFunded:\n$62,400\nProposed by:\nJeroen Ooms\nWebsite:\nhttps://github.com/r-hub/homebrew-cran#how-to-use\nSummary:\nThe majority of R users rely on precompiled installers and binary packages for Windows and MacOS that are made available through CRAN. This project seeks to improve and maintain tools for providing such binaries, and relieve some of the dependence on CRAN maintainers and R-core members for doing so. On Windows we will upgrade the Rtools compiler toolchain, and provide up-to-date Windows builds for the many external C/C++ libraries used by CRAN packages. For MacOS we will expand the r-hub “homebrew-cran” tap with formulas that are needed by CRAN packages but not available from upstream homebrew-core. Eventually we want to lay the foundation for a reproducible build system that is low maintenance, automated as much as possible, and which could be used by CRAN and other R package repositories.\n\n\n\nFunded:\n$4,000\nProposed by:\nLyn Taylor (on behalf of PSI AIMS SIG)\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe documentation available for R packages currently widely varies. The Statisticians in the Pharmaceutical Industry (PSI) Application and Implementation of Methodologies in Statistics (AIMS) Special Interest Group (SIG) will collaborate with the R-Consortium and representatives from pharmaceutical companies on the setting up of an online repository /web portal, where validation which is of regulatory standard for R packages can be submitted and stored for free use. Companies (or individual R users) would still be liable to make their own assessment on whether the validation is suitable for their own use, however the online repository would serve as a portal for sharing existing regulatory standard validation documentation.\n\n\n\nFunded:\n$4,000\nProposed by:\nAri Lamstein\nWebsite:\nhttps://github.com/RConsortium/censusguide\nSummary:\nThe Proposal to Create an R Consortium Working Group Focused on US Census Data aims to make life easier for R programmers who work with data from the US Census Bureau. It will create a working group where R users working with census data can cooperate under the guidance of the Census Bureau. Additionally, it will publish a guide to working with Census data in R that aims to help R programmers a) select packages that meet their needs and b) navigate the various data sets that the Census Bureau publishes.\n\n\n\nFunded:\n$772\nProposed by:\nJohn C Nash\nWebsite:\nhttps://gitlab.com/nashjc/histoRicalg\nSummary:\nMany of the algorithms making up the numerical building-blocks of R were developed several decades ago, particularly in Fortran. Some were translated into C for use by R. Only a modest proportion of R users today are fluent in these languages, and many original authors are no longer active. Yet some of these codes may have bugs or need adjustment for new system capabilities. The histoRicalg project aims to document and test such codes that are still part of R, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future. Our initial task is to establish a ***Working Group on Algorithms Used in R*** and add material to a website/wiki currently at https://gitlab.com/nashjc/histoRicalg. Interested workers are invited to contact John Nash." }, { - "objectID": "all-projects/2016-group-1.html#funded-isc-grants-2016-1", - "href": "all-projects/2016-group-1.html#funded-isc-grants-2016-1", + "objectID": "all-projects/2018-group-1.html#funded-isc-grants-2018-1", + "href": "all-projects/2018-group-1.html#funded-isc-grants-2018-1", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified framework for Distributed Computing in R\nImproving DBI\nR Implimentation Optimization Tooling (RIOT) Workshops\nRL10N: R Localization Proposal\nSatRDays\nSimple Features for R\nSoftware Carpentry R Instructor Training\n\n\n\n\nFunded:\n$10,000\nProposed by:\nMichael Lawrence\nWebsite:\nhttps://github.com/RConsortium/Distributed-Computing-WG\nSummary:\nMany Big Data platforms expose R-based interfaces that lack standardization and are therefore difficult to learn. This project will develop a common framework to simplify and standardize how users program distributed applications in R, ultimately reducing duplication of effort.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDatabase access is an important cornerstone of the R ecosystem, but today’s specifications – data type transformation, return values, error conditions – remain vague and result in data analysis errors. This project aims to improve database access in R so that porting code is simplified and less prone to error.\n\n\n\nFunded:\n$10,000\nProposed by:\nMark Hornick\nWebsite:\nhttps://riotworkshop.github.io/\nSummary:\nRIOT 2016 is a one-day workshop to unite R language developers, identify R language development and tooling opportunities, increase involvement of the R user community and more.\n\n\n\nFunded:\n$10,000\nProposed by:\nRichard Cotton\nWebsite:\nhttps://github.com/RL10N/RL10N and https://libraries.io/github/RL10N\nSummary:\nAlthough the R language is used globally, very few R packages are available in languages other than English. The RL10N project will make it easier for R developers to include translations in their own packages.\n\n\n\nFunded:\n$10,000\nProposed by:\nStephanie Locke\nWebsite:\nhttps://github.com/satrdays\nSummary:\n“SatRDays” are community-led, regional conferences to support collaboration, networking and innovation within the R community. Initially three events will be hosted, with plans for additional meet-ups as the R user base grows.\n\n\n\nFunded:\n$10,000\nProposed by:\nEdzer Pebesma\nWebsite:\nhttps://github.com/r-spatial/sf/\nSummary:\nUsing the “Simple Features” standard supported by the Open Geospatial Consortium and the International Organization for Standardization, this tool will simplify analysis on modern geospatial data.\n\n\n\nFunded:\n$10,000\nProposed by:\nLaurent Gatto\nWebsite:\nSummary:\nThis two-day in-person training course will introduce the basics of R programming and address the growing demand for training resources for the R language." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nA unified platform for missing values methods and workflows\nDeveloping Tools and Templates for Teaching Materials\nMaintaining DBI\nOngoing infrastructural development for R on Windows and MacOS\nPSI application for collaboration to create online R package validation repository\nProposal to Create an R Consortium Working Group Focused on US Census Data\nhistoRicalg – Preserving and Transfering Algorithmic Knowledge\n\n\n\n\nFunded:\n$14,000\nProposed by:\nJulie Josse\nWebsite:\nhttps://cran.r-project.org/web/views/MissingData.html\nSummary:\nThe objective is to create a reference platform on the theme of missing data management and to federate contributors. This platform will be the occasion to list the existing packages, the available literature as well as the tutorials that allow to analyze data with missing data. New work on the subject can be easily integrated and we will create examples of analysis workflows with missing data. Anyone who would like to contribute to this exciting project can contact us.\n\n\n\nFunded:\n$10,000\nProposed by:\nFrançois Michonneau\nWebsite:\nhttps://datacarpentry.org/R-ecology-lesson/ and http://swcarpentry.github.io/r-novice-gapminder/\nSummary:\nThe first-class implementation of literate programming in R is one of the reasons for its success. While the seamless integration of code and text made possible by Sweave, knitr, and rmarkdown was designed for writing reproducible reports and documentation, it has also enabled the creation of teaching materials that combine text, code examples, exercises and solutions. However, while people creating lessons in RMarkdown are familiar with R, they often do not have a background in education or UX design. Therefore, they must not only assemble curriculum, but also find a way to present the content effectively and accessibly to both learners and instructors. As the model of open source development is being adapted to the creation of open educational resources, the difficulty to share materials due to a lack of consistency in their construction hinders the collaborative development of these resources.\nThis project will develop an R package that will facilitate the development of consistent teaching resources. It will encourage the use of tools and lesson structure that support and improve learning. By providing the technical framework for developing quality teaching materials, we seek to encourage collaborative lesson development by letting authors focus on the content rather than the formatting, while providing a more consistent experience for the learners.\n\n\n\nFunded:\n$26,500\nProposed by:\nKirill Müller\nWebsite:\nhttps://dbi.r-dbi.org/\nSummary:\nDBI, R’s database interface, is a set of methods declared in the DBI R package. Communication with the database is implemented by DBI backends, packages that import DBI and implement its methods. A common interface is helpful for both users and backend implementers.\nThe “Maintaining DBI” is a follow-up project to two previous projects supported by the R Consortium, and is mostly about providing ongoing maintenance and support for DBI, the DBItest test suite, and the three backends to open-source databases (RSQLite, RMariaDB and RPostgres) that have been implemented as part of the previous projects.\n\n\n\nFunded:\n$62,400\nProposed by:\nJeroen Ooms\nWebsite:\nhttps://github.com/r-hub/homebrew-cran#how-to-use\nSummary:\nThe majority of R users rely on precompiled installers and binary packages for Windows and MacOS that are made available through CRAN. This project seeks to improve and maintain tools for providing such binaries, and relieve some of the dependence on CRAN maintainers and R-core members for doing so. On Windows we will upgrade the Rtools compiler toolchain, and provide up-to-date Windows builds for the many external C/C++ libraries used by CRAN packages. For MacOS we will expand the r-hub “homebrew-cran” tap with formulas that are needed by CRAN packages but not available from upstream homebrew-core. Eventually we want to lay the foundation for a reproducible build system that is low maintenance, automated as much as possible, and which could be used by CRAN and other R package repositories.\n\n\n\nFunded:\n$4,000\nProposed by:\nLyn Taylor (on behalf of PSI AIMS SIG)\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe documentation available for R packages currently widely varies. The Statisticians in the Pharmaceutical Industry (PSI) Application and Implementation of Methodologies in Statistics (AIMS) Special Interest Group (SIG) will collaborate with the R-Consortium and representatives from pharmaceutical companies on the setting up of an online repository /web portal, where validation which is of regulatory standard for R packages can be submitted and stored for free use. Companies (or individual R users) would still be liable to make their own assessment on whether the validation is suitable for their own use, however the online repository would serve as a portal for sharing existing regulatory standard validation documentation.\n\n\n\nFunded:\n$4,000\nProposed by:\nAri Lamstein\nWebsite:\nhttps://github.com/RConsortium/censusguide\nSummary:\nThe Proposal to Create an R Consortium Working Group Focused on US Census Data aims to make life easier for R programmers who work with data from the US Census Bureau. It will create a working group where R users working with census data can cooperate under the guidance of the Census Bureau. Additionally, it will publish a guide to working with Census data in R that aims to help R programmers a) select packages that meet their needs and b) navigate the various data sets that the Census Bureau publishes.\n\n\n\nFunded:\n$772\nProposed by:\nJohn C Nash\nWebsite:\nhttps://gitlab.com/nashjc/histoRicalg\nSummary:\nMany of the algorithms making up the numerical building-blocks of R were developed several decades ago, particularly in Fortran. Some were translated into C for use by R. Only a modest proportion of R users today are fluent in these languages, and many original authors are no longer active. Yet some of these codes may have bugs or need adjustment for new system capabilities. The histoRicalg project aims to document and test such codes that are still part of R, possibly creating all-R reference codes, hopefully by teaming older and younger workers so knowledge can be shared for the future. Our initial task is to establish a ***Working Group on Algorithms Used in R*** and add material to a website/wiki currently at https://gitlab.com/nashjc/histoRicalg. Interested workers are invited to contact John Nash." }, { - "objectID": "all-projects/index.html", - "href": "all-projects/index.html", - "title": "Goal of ISC Grants Program", + "objectID": "all-projects/previous-top-level-projects.html", + "href": "all-projects/previous-top-level-projects.html", + "title": "Previous Top Level Projects", "section": "", - "text": "The goal of the Infrastructure Steering Committee (the ISC) is to support projects that broadly help the R community. This might be software development, developing new teaching materials, documenting best practices, standardizing APIs or doing research. Currently, the ISC chiefly provides financial support for projects proposed by individuals or teams who have the skills to carry out the work, but we can also provide administrative support, promotion and some collaboration tools for groups who would like to study more ambitious projects.\nThe ISC generally funds two grant cycles per year. Cumulatively, we have awarded over $750k in community development grants over 5 years.\nInterested in strengthening the R community? Submit a Proposal. Please note, grants from the R Consortium are not adjusted to accommodate for internal institutional overhead.\n\n\nFor activities that are well defined and scoped, yet require funding to help bring to fruition, the ISC has established a grant fund. Twice yearly, the ISC awards grants for projects such as code development, workshops, infrastructure, and other projects to help sustain the R community.\nYou can learn more about the in-progress and completed funded projects. If you have a project needing funding, learn more about the grant funding process.\n\n\n\nFor community projects of importance to the R community and needing long-term support by R Consortium, the project and ISC can consider the project for long-term status. This gives the project guaranteed funding for 3 years, along with a voting seat on the ISC. Projects looking for this status will need to justify to the ISC why the project needs long-term funding, as well as submit a 3-year plan and budget for consideration. Top level projects get priority access to grant funds available.\nThree projects are currently Top Level Projects:\n\nDBI\nR-Ladies\nR User Group Support Program (RUGS)\n\nPrevious Top Level Projects" + "text": "R Inclusion, Diversity, Equity and Accessibility (IDEA) was a group broadly considering how the R Consortium could best encourage and support diversity and inclusion in the R Community.\nhttps://github.com/RConsortium/RCDI-WG/tree/master\n\n\n\n\nR-Hub was a platform for simplifying and improving the R package development process.\nR-Hub assisted R package developers by providing facilities to test packages across multiple architectures, build binaries, and publish, distribute and maintain their packages. Developed by Gábor Csárdi, it was being leveraged by R package developers to improve the quality of their packages and to enable support for their packages across multiple architectures.\nhttps://github.com/r-hub." }, { - "objectID": "all-projects/index.html#funded-projects", - "href": "all-projects/index.html#funded-projects", - "title": "Goal of ISC Grants Program", + "objectID": "all-projects/previous-top-level-projects.html#r-inclusion-diversity-equity-and-accessibility-idea", + "href": "all-projects/previous-top-level-projects.html#r-inclusion-diversity-equity-and-accessibility-idea", + "title": "Previous Top Level Projects", "section": "", - "text": "For activities that are well defined and scoped, yet require funding to help bring to fruition, the ISC has established a grant fund. Twice yearly, the ISC awards grants for projects such as code development, workshops, infrastructure, and other projects to help sustain the R community.\nYou can learn more about the in-progress and completed funded projects. If you have a project needing funding, learn more about the grant funding process." + "text": "R Inclusion, Diversity, Equity and Accessibility (IDEA) was a group broadly considering how the R Consortium could best encourage and support diversity and inclusion in the R Community.\nhttps://github.com/RConsortium/RCDI-WG/tree/master" }, { - "objectID": "all-projects/index.html#top-level-projects", - "href": "all-projects/index.html#top-level-projects", - "title": "Goal of ISC Grants Program", + "objectID": "all-projects/previous-top-level-projects.html#r-hub", + "href": "all-projects/previous-top-level-projects.html#r-hub", + "title": "Previous Top Level Projects", "section": "", - "text": "For community projects of importance to the R community and needing long-term support by R Consortium, the project and ISC can consider the project for long-term status. This gives the project guaranteed funding for 3 years, along with a voting seat on the ISC. Projects looking for this status will need to justify to the ISC why the project needs long-term funding, as well as submit a 3-year plan and budget for consideration. Top level projects get priority access to grant funds available.\nThree projects are currently Top Level Projects:\n\nDBI\nR-Ladies\nR User Group Support Program (RUGS)\n\nPrevious Top Level Projects" + "text": "R-Hub was a platform for simplifying and improving the R package development process.\nR-Hub assisted R package developers by providing facilities to test packages across multiple architectures, build binaries, and publish, distribute and maintain their packages. Developed by Gábor Csárdi, it was being leveraged by R package developers to improve the quality of their packages and to enable support for their packages across multiple architectures.\nhttps://github.com/r-hub." }, { - "objectID": "all-projects/2022-group-1.html", - "href": "all-projects/2022-group-1.html", + "objectID": "all-projects/2019-group-2.html", + "href": "all-projects/2019-group-2.html", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n\n\n\nFunded:\n$15,000\nProposed by:\nJulien Brun and Allison Horst\nSummary:\nExpanding the lterdatasampler Package addresses the need for accessible and relevant datasets in data science education. It aims to provide modern, curated, and approachable environmental data samples from the US Long Term Ecological Research Network (LTER) through the lterdatasampler R package. By offering datasets that save time for instructors, engage students with meaningful data, and foster discussions based on real-world questions.The package serves as a valuable resource for teaching introductory statistics and data science in R. The project seeks funding to expand the package to include data samples from all 28 LTER network sites, with the goal of modernizing course materials with real-world environmental datasets.\n\n\n\nFunded:\n$20,000\nProposed by:\nLaura Sangalli\nSummary:\nFemr: There is a need for implementing finite element methods (FEM) in R to solve partial differential equations (PDEs). PDEs are crucial mathematical tools used for modeling complex phenomena in various scientific and engineering fields. However, the absence of FEM implementations in R necessitates the reliance on external software, discouraging the statistical community from developing methods involving PDEs and hindering the learning of this essential mathematical tool. The goal of the project is to develop the femR package, which will provide a finite element basis for solving second-order linear elliptic PDEs on general two-dimensional spatial domains in R.\nThis package will complement the existing deSolve package and enable users to employ finite elements instead of finite differences for solving PDEs on more diverse spatial domains. The development process will include providing comprehensive examples and a final vignette to guide users in utilizing the package’s functionalities.\n\n\n\nFunded:\n$5,000\nProposed by:\nNicholas Tierney\nSummary:\nThe proposal for “Continuing to Improve R’s Ability to Visualise and Explore Missing Values” addresses missing values in data analysis. Missing values are often dropped by default in data analysis in various stages. There is often not even a warning displayed to alert the user of missing values being dropped or discarded. This means values can be dropped without the user knowing, leading to issues such as potential bias, where missing values might be occurring in high numbers in particular groups.\nThe proposal for the ISC-funded project addressed this problem in four parts:\n\nPart one: Initial evaluation of additional missing data visualizations\nPart two: Implementation of missing data visualizations\nPart three: Will provide tutorials and workflows.\nPart four: Future extensions and beyond\n\n\n\n\nFunded:\n$2,000\nProposed by:\nThiyanga Talagala\nSummary:\nThe Dengue Data Hub project helps addresses data packages related to Dengue. Dengue is a mosquito-borne viral disease that has spread fast throughout the world, primarily in urban and semi-urban regions. The goal of the Dengue Data Hub is to provide the research community with a unified dataset helpful for dengue research and reproducibility of research. The project proposes the creation of an R package for aggregating dengue data from several sources and the ability to share them in tidy format. Based on the proposal, there will also be tutorials and good documentation for using the “Dengue Data Hub” interface. This will motivate epidemiology researchers to utilize R to analyze their data." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n\n\n\nFunded:\n$8,500\nProposed by:\nAaron Jacobs\nWebsite:\nhttps://github.com/atheriel/xrprof\nSummary:\nMany R users will be familiar with using the built-in sampling profiler ‘Rprof()’ to generate data on what their code is doing, and there are several excellent tools to facilitate understanding these samples (or serve as a front-end), including the ‘profvis’ package. However, the reach of these tools is limited: the profiler is “internal”, in the sense that it must be manually switched on to work, either during interactive work (for example, to profile an individual function), or perhaps by modifying the script to include ‘Rprof()’ calls before running it again. It cannot be used to understand R code that is already running, a capability that has proven extremely useful for diagnosing and fixing performance issues (or other bugs) in production environments.\nSeveral existing programming languages have one or more “external” profilers available, which can attach to a running process and read its memory contents to understand what is currently happening. This project aims to build such a tool for R.\n\n\n\nFunded:\n$9,500\nProposed by:\nDavid W Kang\nWebsite:\nhttps://github.com/cvxgrp/CVXR\nSummary:\nOptimization is at the core of statistical estimation and machine learning methodology. There are a number of R packages such as optimx, nloptr, ROI which either implement solvers for a wide variety of problems, or provide an interface to other solvers. The R package CVXR takes a different approach, implementing a Domain Specific Language (Fu, Narasimhan, and Boyd 2019) for formulating and solving convex optimization problems, just as cvxpy does for python. As shown in a number of examples on the CVXR website, the applications range from finance, machine learning, and to theoretical and applied statistics. Using a disciplined convex programming (DCP) approach, CVXR acts as a great tool for both prototyping and developing new methodologies as well as for quick, high-level, formulation and solution of statistical and machine learning problems.\n\n\n\nFunded:\n$6,699\nProposed by:\nEvangeline Reynolds\nWebsite:\nhttps://github.com/EvaMaeRey/flipbookr\nSummary:\nJust as classic flip books allow their readers to observe changes in a scene, coding Flipbooks allow readers to progressively track the changes of code and its output by “flipping” through their digital pages. Flipbooks are useful tools for communicating and teaching because they break down code for incremental, stepwise presentation so that audiences can easily understand each step. Flipbook-building tools automate the deconstruction and reconstruction of coding pipelines which means that building a Flipbook from existing code poses little additional burden to creators. The next stage for this project is to develop the current Flipbook-building tools into a reliable and easy-to-use R package (development is ongoing at https://github.com/EvaMaeRey/flipbookr) and also to provide educational guidance for creating Flipbooks.\n\n\n\nFunded:\n$16,800\nProposed by:\nAndrew Nicholls\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe R Validation Hub is an active R Consortium Working Group. It is a cross-industry initiative whose mission is to enable the use of R by the Bio-Pharmaceutical Industry in a regulatory setting, where the output may be used in submissions to regulatory agencies. This project sits within phase 2 of the R Validation Hub’s road map. During this phase the group will develop several tools that can be used by those wishing to use R packages within a bio-pharmaceutical regulatory setting. The aim of this specific project is to standardise and simplify the risk assessment of R packages, reducing the burden of package evaluation/testing that would otherwise fall on internal R programming experts. The project will deliver a Shiny application to aid in the assessment and documentation of package risk.\n\n\n\nFunded:\n$34,000\nProposed by:\nToby Hocking\nWebsite:\nhttps://github.com/akhikolla/RcppDeepState\nSummary:\nAbstract: Fuzzers are computer programs that send other programs inputs that may fall outside the domain of expected values, thus revealing subtle bugs. DeepState is a testing framework that allows easy testing of C/C++ programs with sophisticated fuzzers, and supports multiple back-ends for testing. DeepState has been used to test critical C++ software, including Google’s leveldb. R has some simple random testers, but no coverage-driven fuzzers that learn to produce problematic inputs. We propose to create the R packages RcppDeepState and RcppDeepStateTools which will provide easy-to-use functions for using DeepState with R packages that use C/C++ code via Rcpp. This project will thus provide the first easy-to-use solution for R programmers that want to fuzz test their C/C++ code with existing tools such as AFL, and it will provide a framework for interfacing future coverage-driven fuzzers or symbolic execution tools. We also propose to use these new tools on a wide range of R packages in order to identify bugs in their C/C++ code.\nOne masters student will be recruited to implement this project during Jan-Dec 2020 at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. Interested students should apply by emailing a resume/CV along with a cover letter to project supervisors toby.hocking@nau.edu and alex.groce@nau.edu.\n\n\n\nFunded:\n$10,000\nProposed by:\nMikkel Meyer Andersen\nWebsite:\nhttps://github.com/r-cas/caracas/\nSummary:\nR’s ability to do symbolic mathematics is largely restricted to finding derivatives. There are many tasks involving symbolic math that are of interest to R users, e.g. inversion of symbolic matrices, limits and solving non-linear equations. Users must resort to other software for such tasks and many R users (especially outside of academia) do not readily have access to such software.\nThe Python library SymPy is open source, has a stable group of developers and is powerful. As such, R users can just switch to Python and SymPy for symbolic math. However it is often very convenient to stay in the same environment to use familiar syntax and to utilise available libraries (e.g. to generate problems using symbolic math together with the exams package or to first handle symbolic computations and then afterwards move on to a numerical evaluations of the results). We will achieve this by making SymPy functionality available for R users via an R package.\nCurrently only few R packages for doing symbolic mathematics are available: Two of these are Ryacas and rSymPy. Ryacas is built around Yacas, and although Yacas can solve many problems and is extensible, the community is relatively small and Yacas is not as powerful as SymPy for certain routine tasks (e.g. integration and solving equations). rSymPy on the other hand is based on technology that requires much technical work to install and use.\nThe website of the project is:\nhttps://github.com/r-cas/caracas/\nPlease contribute by testing, writing documentation, opening issues, submitting pull requests or something else!\n\n\n\nFunded:\n$9,000\nProposed by:\nLucas van der Meer, Robin Lovelace, Andrea Gilardi, Lorena Abad\nWebsite:\nhttps://luukvdmeer.github.io/sfnetworks/\nSummary:\nR is currently lacking a generally applicable, modern and easy-to-use way of handling all kinds of spatial networks. “Tidy spatial networks in R” aims to address this issue by developing and publishing the sfnetworks package. The package, and documentation around it, will provide a bridge between network analysis and spatial analysis communities. For this, an sfnetwork class that will work with both tidygraph and sf frameworks and functions. R-users will be encouraged to contribute and engage with the package development during a hackathon organized next to the eRum 2020.\n\n\n\nFunded:\n$4,000\nProposed by:\nMauricio Vargas Sepúlveda\nWebsite:\nhttps://github.com/pachamaltese/d3po\nSummary:\nR already features excellent visualization libraries such as D3 (via the r2d3 package), plotly or highcharter. However, though those enable the creation of great looking visualisations they have very steep learning curves, require understanding of JavaScript or rely on non-free software that might be out of reach for governments and NGOs. Our intention is to solve those problems by releasing d3po. It shall be an intermediate layer between the user and D3 by providing “templates”, enabling high quality interactive visualizations oriented to and designed to be used with Shiny and Rmarkdown, and also proving easy internationalization. Please join us, this needs D3 and R skilled minds!\n\n\n\nFunded:\n$6,000\nProposed by:\nEric Scott, Tamas Stirling\nWebsite:\nhttps://github.com/ropensci/webchem\nSummary:\nwebchem: accessing chemical information from the web\nA vast amount of chemical information is freely available on the internet. The data are used by millions of professionals around the world, for purposes like pharmaceutical research, chemical process design, or environmental impact assessment, to name a few. webchem is an R project that aims to help these professionals by providing a single point programmable access to all major chemical databases around the world. The project started in 2016 and currently supports more than 10 databases. If you are interested, join us and help us build the tool that biologists and chemists will absolutely love." }, { - "objectID": "all-projects/2022-group-1.html#funded-isc-grants-2022-1", - "href": "all-projects/2022-group-1.html#funded-isc-grants-2022-1", + "objectID": "all-projects/2019-group-2.html#funded-isc-grants-2019-2", + "href": "all-projects/2019-group-2.html#funded-isc-grants-2019-2", "title": "R Consortium", "section": "", - "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nIterdatasampler: Expanding the lterdatasampler package\nFemr: Finite Element Method for Solving PDEs in R\nContinuing to Improve R’s Ability to Visualise and Explore Missing Values\nDengue Data Hub\n\n\n\n\nFunded:\n$15,000\nProposed by:\nJulien Brun and Allison Horst\nSummary:\nExpanding the lterdatasampler Package addresses the need for accessible and relevant datasets in data science education. It aims to provide modern, curated, and approachable environmental data samples from the US Long Term Ecological Research Network (LTER) through the lterdatasampler R package. By offering datasets that save time for instructors, engage students with meaningful data, and foster discussions based on real-world questions.The package serves as a valuable resource for teaching introductory statistics and data science in R. The project seeks funding to expand the package to include data samples from all 28 LTER network sites, with the goal of modernizing course materials with real-world environmental datasets.\n\n\n\nFunded:\n$20,000\nProposed by:\nLaura Sangalli\nSummary:\nFemr: There is a need for implementing finite element methods (FEM) in R to solve partial differential equations (PDEs). PDEs are crucial mathematical tools used for modeling complex phenomena in various scientific and engineering fields. However, the absence of FEM implementations in R necessitates the reliance on external software, discouraging the statistical community from developing methods involving PDEs and hindering the learning of this essential mathematical tool. The goal of the project is to develop the femR package, which will provide a finite element basis for solving second-order linear elliptic PDEs on general two-dimensional spatial domains in R.\nThis package will complement the existing deSolve package and enable users to employ finite elements instead of finite differences for solving PDEs on more diverse spatial domains. The development process will include providing comprehensive examples and a final vignette to guide users in utilizing the package’s functionalities.\n\n\n\nFunded:\n$5,000\nProposed by:\nNicholas Tierney\nSummary:\nThe proposal for “Continuing to Improve R’s Ability to Visualise and Explore Missing Values” addresses missing values in data analysis. Missing values are often dropped by default in data analysis in various stages. There is often not even a warning displayed to alert the user of missing values being dropped or discarded. This means values can be dropped without the user knowing, leading to issues such as potential bias, where missing values might be occurring in high numbers in particular groups.\nThe proposal for the ISC-funded project addressed this problem in four parts:\n\nPart one: Initial evaluation of additional missing data visualizations\nPart two: Implementation of missing data visualizations\nPart three: Will provide tutorials and workflows.\nPart four: Future extensions and beyond\n\n\n\n\nFunded:\n$2,000\nProposed by:\nThiyanga Talagala\nSummary:\nThe Dengue Data Hub project helps addresses data packages related to Dengue. Dengue is a mosquito-borne viral disease that has spread fast throughout the world, primarily in urban and semi-urban regions. The goal of the Dengue Data Hub is to provide the research community with a unified dataset helpful for dengue research and reproducibility of research. The project proposes the creation of an R package for aggregating dengue data from several sources and the ability to share them in tidy format. Based on the proposal, there will also be tutorials and good documentation for using the “Dengue Data Hub” interface. This will motivate epidemiology researchers to utilize R to analyze their data." + "text": "The R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAn External R Sampling Profiler\nCVXR\nFlipbooks\nR Package Risk Assessment Application\nRcppDeepState, a simple way to fuzz test compiled code in R packages\nSymbolic mathematics in R with SymPy\nTidy spatial networks in R\nd3po: R package for easy interactive D3 visualization with Shiny\nwebchem: accessing chemical information from the web\n\n\n\n\nFunded:\n$8,500\nProposed by:\nAaron Jacobs\nWebsite:\nhttps://github.com/atheriel/xrprof\nSummary:\nMany R users will be familiar with using the built-in sampling profiler ‘Rprof()’ to generate data on what their code is doing, and there are several excellent tools to facilitate understanding these samples (or serve as a front-end), including the ‘profvis’ package. However, the reach of these tools is limited: the profiler is “internal”, in the sense that it must be manually switched on to work, either during interactive work (for example, to profile an individual function), or perhaps by modifying the script to include ‘Rprof()’ calls before running it again. It cannot be used to understand R code that is already running, a capability that has proven extremely useful for diagnosing and fixing performance issues (or other bugs) in production environments.\nSeveral existing programming languages have one or more “external” profilers available, which can attach to a running process and read its memory contents to understand what is currently happening. This project aims to build such a tool for R.\n\n\n\nFunded:\n$9,500\nProposed by:\nDavid W Kang\nWebsite:\nhttps://github.com/cvxgrp/CVXR\nSummary:\nOptimization is at the core of statistical estimation and machine learning methodology. There are a number of R packages such as optimx, nloptr, ROI which either implement solvers for a wide variety of problems, or provide an interface to other solvers. The R package CVXR takes a different approach, implementing a Domain Specific Language (Fu, Narasimhan, and Boyd 2019) for formulating and solving convex optimization problems, just as cvxpy does for python. As shown in a number of examples on the CVXR website, the applications range from finance, machine learning, and to theoretical and applied statistics. Using a disciplined convex programming (DCP) approach, CVXR acts as a great tool for both prototyping and developing new methodologies as well as for quick, high-level, formulation and solution of statistical and machine learning problems.\n\n\n\nFunded:\n$6,699\nProposed by:\nEvangeline Reynolds\nWebsite:\nhttps://github.com/EvaMaeRey/flipbookr\nSummary:\nJust as classic flip books allow their readers to observe changes in a scene, coding Flipbooks allow readers to progressively track the changes of code and its output by “flipping” through their digital pages. Flipbooks are useful tools for communicating and teaching because they break down code for incremental, stepwise presentation so that audiences can easily understand each step. Flipbook-building tools automate the deconstruction and reconstruction of coding pipelines which means that building a Flipbook from existing code poses little additional burden to creators. The next stage for this project is to develop the current Flipbook-building tools into a reliable and easy-to-use R package (development is ongoing at https://github.com/EvaMaeRey/flipbookr) and also to provide educational guidance for creating Flipbooks.\n\n\n\nFunded:\n$16,800\nProposed by:\nAndrew Nicholls\nWebsite:\nhttps://www.pharmar.org/\nSummary:\nThe R Validation Hub is an active R Consortium Working Group. It is a cross-industry initiative whose mission is to enable the use of R by the Bio-Pharmaceutical Industry in a regulatory setting, where the output may be used in submissions to regulatory agencies. This project sits within phase 2 of the R Validation Hub’s road map. During this phase the group will develop several tools that can be used by those wishing to use R packages within a bio-pharmaceutical regulatory setting. The aim of this specific project is to standardise and simplify the risk assessment of R packages, reducing the burden of package evaluation/testing that would otherwise fall on internal R programming experts. The project will deliver a Shiny application to aid in the assessment and documentation of package risk.\n\n\n\nFunded:\n$34,000\nProposed by:\nToby Hocking\nWebsite:\nhttps://github.com/akhikolla/RcppDeepState\nSummary:\nAbstract: Fuzzers are computer programs that send other programs inputs that may fall outside the domain of expected values, thus revealing subtle bugs. DeepState is a testing framework that allows easy testing of C/C++ programs with sophisticated fuzzers, and supports multiple back-ends for testing. DeepState has been used to test critical C++ software, including Google’s leveldb. R has some simple random testers, but no coverage-driven fuzzers that learn to produce problematic inputs. We propose to create the R packages RcppDeepState and RcppDeepStateTools which will provide easy-to-use functions for using DeepState with R packages that use C/C++ code via Rcpp. This project will thus provide the first easy-to-use solution for R programmers that want to fuzz test their C/C++ code with existing tools such as AFL, and it will provide a framework for interfacing future coverage-driven fuzzers or symbolic execution tools. We also propose to use these new tools on a wide range of R packages in order to identify bugs in their C/C++ code.\nOne masters student will be recruited to implement this project during Jan-Dec 2020 at the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. Interested students should apply by emailing a resume/CV along with a cover letter to project supervisors toby.hocking@nau.edu and alex.groce@nau.edu.\n\n\n\nFunded:\n$10,000\nProposed by:\nMikkel Meyer Andersen\nWebsite:\nhttps://github.com/r-cas/caracas/\nSummary:\nR’s ability to do symbolic mathematics is largely restricted to finding derivatives. There are many tasks involving symbolic math that are of interest to R users, e.g. inversion of symbolic matrices, limits and solving non-linear equations. Users must resort to other software for such tasks and many R users (especially outside of academia) do not readily have access to such software.\nThe Python library SymPy is open source, has a stable group of developers and is powerful. As such, R users can just switch to Python and SymPy for symbolic math. However it is often very convenient to stay in the same environment to use familiar syntax and to utilise available libraries (e.g. to generate problems using symbolic math together with the exams package or to first handle symbolic computations and then afterwards move on to a numerical evaluations of the results). We will achieve this by making SymPy functionality available for R users via an R package.\nCurrently only few R packages for doing symbolic mathematics are available: Two of these are Ryacas and rSymPy. Ryacas is built around Yacas, and although Yacas can solve many problems and is extensible, the community is relatively small and Yacas is not as powerful as SymPy for certain routine tasks (e.g. integration and solving equations). rSymPy on the other hand is based on technology that requires much technical work to install and use.\nThe website of the project is:\nhttps://github.com/r-cas/caracas/\nPlease contribute by testing, writing documentation, opening issues, submitting pull requests or something else!\n\n\n\nFunded:\n$9,000\nProposed by:\nLucas van der Meer, Robin Lovelace, Andrea Gilardi, Lorena Abad\nWebsite:\nhttps://luukvdmeer.github.io/sfnetworks/\nSummary:\nR is currently lacking a generally applicable, modern and easy-to-use way of handling all kinds of spatial networks. “Tidy spatial networks in R” aims to address this issue by developing and publishing the sfnetworks package. The package, and documentation around it, will provide a bridge between network analysis and spatial analysis communities. For this, an sfnetwork class that will work with both tidygraph and sf frameworks and functions. R-users will be encouraged to contribute and engage with the package development during a hackathon organized next to the eRum 2020.\n\n\n\nFunded:\n$4,000\nProposed by:\nMauricio Vargas Sepúlveda\nWebsite:\nhttps://github.com/pachamaltese/d3po\nSummary:\nR already features excellent visualization libraries such as D3 (via the r2d3 package), plotly or highcharter. However, though those enable the creation of great looking visualisations they have very steep learning curves, require understanding of JavaScript or rely on non-free software that might be out of reach for governments and NGOs. Our intention is to solve those problems by releasing d3po. It shall be an intermediate layer between the user and D3 by providing “templates”, enabling high quality interactive visualizations oriented to and designed to be used with Shiny and Rmarkdown, and also proving easy internationalization. Please join us, this needs D3 and R skilled minds!\n\n\n\nFunded:\n$6,000\nProposed by:\nEric Scott, Tamas Stirling\nWebsite:\nhttps://github.com/ropensci/webchem\nSummary:\nwebchem: accessing chemical information from the web\nA vast amount of chemical information is freely available on the internet. The data are used by millions of professionals around the world, for purposes like pharmaceutical research, chemical process design, or environmental impact assessment, to name a few. webchem is an R project that aims to help these professionals by providing a single point programmable access to all major chemical databases around the world. The project started in 2016 and currently supports more than 10 databases. If you are interested, join us and help us build the tool that biologists and chemists will absolutely love." }, { - "objectID": "all-projects/2021-group-1.html", - "href": "all-projects/2021-group-1.html", - "title": "Funded ISC Grants (2021-1)", + "objectID": "media-partners.html", + "href": "media-partners.html", + "title": "Media Partners", "section": "", - "text": "Funded ISC Grants (2021-1)\nThe R Consortium Infrastructure Steering Committee periodically solicits proposals from the worldwide R community for projects which will help advance the state of the R ecosystem. Developers and organizations may apply to participate in the program and receive funding to help further a project or initiative.\nGrants funded in this group:\n\nAccounting/Auditing Gap-Analysis\nExtendr - Rust extensions for R.\nGoogle Earth Engine with R\nImproving Translations in R\nMinimizing wastage of blood products\nR for Engineering Applications\nSetting up an R-Girls-Schools Network\ndeposits: Deposit Research Data Anywhere\n\n\n\nAccounting/Auditing Gap-Analysis\nFunded:\n$7,000\nProposed by:\nFelix Schildorfer\nSummary:\nThere are more and more accountants and auditors who want to start using R and dig into data science. They usually have particular tasks on hand that they want to complete, facilitate, or automate. While they often have some basic stats skills and may be some coding basics, understanding the R landscape and relating tasks and processes to locate and use relevant R packages and tutorials is an extreme challenge. While other areas like finance or pharmaceuticals already have extensive infrastructure to support R newcomers (Working Groups, Courses, Task Views, etc.) accounting and auditing do not. This becomes an obstacle for such professionals - which find the “coding” part difficult on their own but doing so without any support or knowing the appropriate package becomes a nightmare.\nThis is why R Business put together this project with the aim to gauge the landscape of what functionalities are available for Auditors in the R ecosystem and how the existing functionalities can be mapped to routine accounting/auditing tasks. We will complete a systematic survey of the CRAN-ecosystem for accounting/auditing tasks to establish a mapping and identify gaps. The project will contribute to the development of the R Business ISC working group by attracting interested accounting/auditing professionals, industry bodies and R community members. This will then in turn lead to increased use of R/RStudio, development new application domains for data science, and enhancement of the quality of accounting/auditing services.\n\n\nExtendr - Rust extensions for R.\nFunded:\n$15,000\nProposed by:\nAndy Thomason\nSummary:\nRust extension framework for R.\n\n\nGoogle Earth Engine with R\nFunded:\n$5,500\nProposed by:\nCesar Luis Aybar Camacho\nSummary:\nGoogle Earth Engine (GEE) is the most popular and advanced cloud platform designed for planetary-scale environmental data analysis. Its multi-petabyte data catalog and computation services are just accessed via Python and JavaScript client libraries. In order to facilitate its use within R, six months ago, rgee was released on CRAN using reticulate to wrap the GEE Python API. Although rgee provides a familiar interface and simple integration to other R packages (e.g., sf, raster, dplyr), the lack of tutorials and examples makes it difficult for new users to adopt.\nThe main goal of this project is to leverage the documentation. For this purpose, three main tasks have been proposed: (1) create a new version of rgee with support for shiny and markdown, (2) create rgeeExtra, which extends the functionalities of rgee, and finally write (3) rgeebook, a reference book with best practices and examples of GEE API usage.\n\n\nImproving Translations in R\nFunded:\n$0\nProposed by:\nMichael Chirico\nSummary:\nThis project will provide a better formalization of translation procedures for R to be more sustainable and more scalable. In the process, it will broaden the inclusivity of R by growing the sub-community of R users comfortable producing translations and extending the reach of the R project to more non-English audiences.\n\n\nMinimizing wastage of blood products\nFunded:\n$11,200\nProposed by:\nBalasubramanian Narasimhan\nSummary:\nGuan et al. 2017 (Proc Natl Acad Sci U S A 114 (43): 11368–73) used two years worth of data to formulate and solve an optimization problem to predict platelet usage and minimize waste. Two open-source R packages were developed for this purpose:\n- Platelet Inventory Prediction or pip (https://github.com/bnaras/pip) a package that is the core ML prediction engine that uses a given set of features described in the above publication\n- Stanford Blood Center Platelet Inventory Prediction or SBCpip (https://github.com/bnaras/SBCpip) that was customized to the data workflow at SHC. SBCpip was meant to be site specific.\nThere have been a number of requests from sites wishing to deploy the software locally. The current project will generalize the model, generalize it to address more blood products with different shelf lives, provide customizations for local use, and create easily deployable solutions.\n\n\nR for Engineering Applications\nFunded:\n$3,000\nProposed by:\nBenaiah Chibuokem Ubah\nSummary:\nR for Engineering Applications is a proposed project with the aim to attract engineers and diversify the use of the R language to the broad engineering domain – electrical, electronic, communications, robotics, etc engineering. The idea is similar to such projects as R in Finance, R in Insurance, BioConductor (R in Bio-informatics), R in Environmental Statistics, etc.\n\n\nSetting up an R-Girls-Schools Network\nFunded:\n$5,000\nProposed by:\nDr. Razia Ghani\nSummary:\nGlobally, women, especially from deprived socio-economic and diverse ethnic backgrounds, are under-represented in data science. A major factor is that data science does not feature in the school curriculum which means that teachers are unaware of the enhancements data science can bring to learning and development in and beyond the school. We propose an ongoing project, called R-Girls-School Network (short name R-Girls) to address this and are keen to link up with others.\nWe are a multi-disciplinary team that includes an educationalist, subject teachers, a data scientist and administrator who will begin to develop and implement a data science curriculum using R in Green Oak Academy – an inner-city school in the UK serving girls from deprived, ethnically diverse backgrounds aged 11-16 years; independently rated as Good with Outstanding for Behaviour and Attitudes.\nSince GOA follows the UK national curriculum, which is used in 10,000+ schools and 160 countries, our work will have a broad appeal. In due course we will develop ready-to-use bite-sized learning materials (10-15 mins) for teachers of core subjects (maths, statistics, science, geography) to use via RStudio cloud. The lessons will be tested with teachers and pupils and then incorporated into the school timetable across all five-year groups (age 11-16 years), culminating in an R-Data Story project and in due course, an annual R-Girls virtual conference open to any girl and girls’ school in the world.\nR-GS will be supported by a website for showcasing the work of pupils and sharing resources.\n\n\ndeposits: Deposit Research Data Anywhere\nFunded:\n$16,000\nProposed by:\nMark Padgham\nSummary:\nPublicly depositing datasets associated with published research is becoming more common, partly due to journals increasingly requiring data sharing, and partly though more general and ongoing cultural changes in relation to data sharing. Yet data sharing is often seen as time consuming, particularly in order to meet the expectations of individual data repositories. While documentation and training can help get users familiar with processes of data sharing, browser-based data and metadata submission workflows can only be so fast, are not easily reproduced, and do not facilitate regular or automated updates of data and metadata. Better programmatic tools can transform data sharing from a mountainous climb into a pit of success.\nThis project will develop a unified interface to many different research data repositories, and which will function along the lines of dplyr through “verbs” that work identically across many “backend” data repositories. The package will initially provide access to a few of the most common data repositories, yet will implement a modular/plugin system to enable users to contribute their own plugins to extend functionality to other repositories. Users will be able to authenticate, prepare data and metadata, and finally to submit, fetch, and browse data." + "text": "Media Partners\nThe R Consortium is proud to partner with the following media and associations to amplify information about R community activities around the globe. If you are interested in becoming a media partner, please contact us at info@r-consortium.org.\n\nR news and tutorials contributed by hundreds of R bloggers" }, { - "objectID": "all-projects/submittingforpayment.html", - "href": "all-projects/submittingforpayment.html", - "title": "Submitting for payment", + "objectID": "index.html", + "href": "index.html", + "title": "R Consortium", "section": "", - "text": "Submitting for payment\nThe R Consortium provides financial support to a broad range of initiatives, in support of the global R development and user community. When organizations become members of the R Consortium, their membership dues help provide this funding, and help ensure the overall health of the ecosystem.\nThe R Consortium provides funding through a structured process. The primary funding categories are:\n\nISC Grants, which are allocated by the Infrastructure Steering Committee through an application process, and support code and community development efforts.\nRUGs Grants, which support local R User Groups.\n\nAll grant payments must be pre-approved. Please follow the formal process established by each working group to apply for funding.\n\nInvoicing for your grant\nStarting in October 2020, each grant recipient will receive a control number. Please ensure that you include this in all requests for payment. If you are unsure of your control number, please contact operations@r-consortium.org.\nWhen you are ready to submit for payment, please complete the payment request form. You will be asked to provide the following, so please have it ready:\n\nThe control number for your grant.\nA W9 form (if you are in the US and have a SSN/EIN) or an international wire form.\nThe signed contract or a PDF of the email approving your grant.\nA brief description of how the funding was used (e.g., project milestone, RUGs or R-Ladies meetup, etc).\n\nIf you have any questions, please contact operations@r-consortium.org." + "text": "R User Group Program and Small Conference Funding Program now accepting applications Partner with us to support your meetup or local event.\n\n\nLEARN MORE\n\n\n\n\nFind your local R user group Network with fellow statisticians and learn from your peers.\n\n\nFIND A USER GROUP\n\n\n\n\nR Consortium: Supporting the R community, the R Foundation and organizations developing, maintaining and distributing R software.\n\n\n\n\nFind your local R user group Network with fellow statisticians and learn from your peers.\n\n\nLEARN MORE\n\n\n\n\nR/Medicine Webinar: Visualizing Survival Data with the {ggsurvfit} R Package\n\n\nWebinar Recording\n\n\n\n\nTidy Finance Webinar Series\n\n\nWebinar Information\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWHAT IS THE R CONSORTIUM\n\n\nThe central mission of the R Consortium is to work with and provide support to the R Foundation and to the key organizations developing, maintaining, distributing and using R software through the identification, development and implementation of infrastructure projects.\n\n\nThe R language is an open source environment for statistical computing and graphics, and runs on a wide variety of computing platforms. The R language has enjoyed significant growth, and now supports over 2 million users. A broad range of industries have adopted the R language, including biotech, finance, research and high technology industries. The R language is often integrated into third party analysis, visualization and reporting applications.\n\n\n\n \n\n\n\nLEARN MORE\n\n\nREAD OUR ANNUAL REPORT 2023\n\n\n\n\nJoining R Consortium\n\n\nIndustry-leading organizations have joined the R Consortium to support an open source governance and foundation model to provide support to the R community, the R Foundation and groups and individuals, using, maintaining and distributing R software.\n\n\nLEARN MORE ABOUT MEMBERSHIP\n\n\n\n\nNeed Help?\n\n\nIf you need help such as with billing, mailing lists or other wise then please use this service desk for support.\n\n\nGET HELP\n\n\n\n\nBLOG\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nReviving Sheffield R User Group and Building Tools for Thyroid Cancer Prediction\n\n\nNeil Shephard, co-organizer of the Sheffield R User Group in Sheffield, United Kingdom (also on fosstodon), recently spoke to the R Consortium about his journey from Genetic…\n\n\n\nR Consortium\n\n\nNov 1, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nStreamlining API Integration: Jon Harmon’s Journey with the api2r Package\n\n\nThe R package api2r simplifies the process of wrapping APIs in R. The R Consortium interviewed Jon Harmon, Principal Data Solutions Engineer at Atorus, about this R…\n\n\n\nR Consortium\n\n\nOct 30, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers\n\n\nFrans van Dunné, the organizer of the San Carlos R User Group, recently discussed with the R Consortium the development of the R community in Costa Rica and the broader…\n\n\n\nR Consortium\n\n\nOct 23, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEndophytes, Oaks, and R: How R-Ladies Morelia is Cultivating Science and Community in Morelia, Mexico\n\n\nGoretty Mendoza, the organizer of the R-Ladies Morelia, recently spoke to the R Consortium about her experience with the group and her work using R in molecular biology.\n\n\n\nR Consortium\n\n\nOct 18, 2024\n\n\n\n\n\n\n\n\n\n\n\n\nThe U.S. Federal Reserve quarterly model in R\n\n\n\n\n\n\nGuest Blog Post\n\n\nOct 16, 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEmpowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative\n\n\nThe Dengue Data Hub, an ambitious initiative funded by the R Consortium ISC, transforms how researchers access and utilize dengue-related data.\n\n\n\nR Consortium\n\n\nOct 15, 2024\n\n\n\n\n\n\n\n\nNo matching items" }, { - "objectID": "codeofconduct.html", - "href": "codeofconduct.html", - "title": "Code of Conduct", + "objectID": "posts/pharma-rug-the-rise-of-r/index.html", + "href": "posts/pharma-rug-the-rise-of-r/index.html", + "title": "Pharma RUG: The Rise of R in China’s Pharmaceutical Industry", "section": "", - "text": "The R Consortium and its working groups are dedicated to providing a harassment-free experience for participants at all of our events, whether they are held in person or virtually. R Consortium events are working conferences intended for professional networking and collaboration within the open source community. They exist to encourage the open exchange of ideas and expression and require an environment that recognizes the inherent worth of every person and group. While at R Consortium events or related ancillary or social events, any participants, including members, speakers, attendees, volunteers, sponsors, exhibitors, booth staff and anyone else, should not engage in harassment in any form.\nThis Code of Conduct may be revised at any time by The R Consortium and the terms are non-negotiable. Your registration for or attendance at any R Consortium event, whether it’s held in person or virtually, indicates your agreement to abide by this policy and its terms.\n\n\nAll event participants, whether they are attending an in-person event or a virtual event, are expected to behave in accordance with professional standards, with both this Code of Conduct as well as their respective employer’s policies governing appropriate workplace behavior and applicable laws.\n\n\n\nHarassment will not be tolerated in any form, whether in person or virtually, including, but not limited to, harassment based on sex, gender, sexual orientation, disability, physical appearance, body size, race, age, religion or any other status protected by laws in which the conference or program is being held. Harassment includes the use of abusive, offensive or degrading language, intimidation, stalking, harassing photography or recording, inappropriate physical contact, sexual imagery and unwelcome sexual advances or requests for sexual favors. Any report of harassment at one of our events, whether in person or virtual, will be addressed immediately. Participants asked to stop any harassing behavior are expected to comply immediately. Anyone who witnesses or is subjected to unacceptable behavior should notify a conference organizer at once.\nExhibitors should not use sexualized images, activities, or other material in their booths and must refrain from the use of sexualized clothing, uniforms, costumes, or otherwise creating a sexualized environment. Speakers should not use sexual language, images, or any language or images that would constitute harassment as defined above in their talks.\nIndividuals who participate (or plan to participate) in R Consortium events, whether its an in-person event or a virtual event, should conduct themselves at all times in a manner that comports with both the letter and spirit of this policy prohibiting harassment and abusive behavior, whether before, during or after the event. This includes statements made in social media postings, on-line publications, text messages, and all other forms of electronic communication.\n\n\n\nIf a participant engages in harassing behavior, whether in person or virtually, the conference organizers may take any action they deem appropriate depending on the circumstances, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nIf a participant (or individual wishing to participate in an R Consortium event, in-person and/or virtual), through postings on social media or other online publications or another form of electronic communication, engages in conduct that violates this policy, whether before, during or after a R Consortium event, the R Consortium may take appropriate corrective action, which could include imposing a temporary or permanent ban on an individual’s participation in future R Consortium events, events, working groups, trainings or other activities.\n\n\n\nIf you are being harassed, notice that someone else is being harassed, or have any other concerns relating to harassment, please contact a member of the conference staff immediately. You are also encouraged to contact abuse@r-consortium.org.\n\n\n\nOur staff has taken incident response training and responds to harassment reports quickly and thoroughly. As referenced above, if a participant engages in harassing behavior, whether in-person or virtually, the conference organizers may take any action they deem appropriate, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund, depending on the circumstances. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nConference staff will also provide support to victims, including, but not limited to:\n\nProviding an Escort\nContacting Hotel/Venue Security or Local Law Enforcement\nBriefing Key Event Staff For Response/Victim Assistance\nAnd otherwise assisting those experiencing harassment to ensure that they feel safe for the duration of the conference.\n\n\n\n\nIf you are planning to attend an upcoming event, whether in-person or virtually and have concerns regarding another individual who may be present, please contact conduct@r-consortium.org. Precautions will be taken to ensure your comfort and safety, including, but not limited to providing an escort, prepping onsite event staff, keeping victim and harasser from attending the same talks/social events and providing onsite contact cell phone numbers for immediate contact." + "text": "PharmaRUG, China organizer Joe Zhu, spoke with the R Consortium about the growing R community and the increasing use of R in the pharmaceutical industry in China. The group has contributed to the pharmaceutical R community through several R packages. Since its establishment last year, the group has organized large-scale hybrid events. Joe also shared some tools and techniques for smoothly organizing and running hybrid events.\n\nPlease share about your background and involvement with the RUGS group.\nI have a PhD in statistics and studied in New Zealand for my undergraduate and postgraduate degrees in statistics. My PhD work focused on theoretical coalescent theory and probabilistic modeling for phylogenetics models. I also completed a postdoc at Oxford, focusing on statistical genomics for the human genome and malaria parasite genome projects. During this time, I developed open source software tools for statistical genomics, primarily using R as a front end and developing C++ software.\nFor the past four years, I’ve worked at Roche, where I started leading a major collaboration initiative in pharma three years ago. I’ve created TLG (table, listing, and figures) for regulatory submissions to the FDA. Throughout this initiative, we have open sourced around 30 software packages, including `formatters`, `rtables`, `rlistings` and `tern`. Last year, we submitted these packages to CRAN.\nAt first, we open sourced the project on GitHub and then submitted it to CRAN. I’m heavily involved in one of China’s R user groups, PharmaRUG. We use the group to share posts about developments in the area, and we organize events and conferences. In March last year, we hosted the first event with over 100 people on-site and around 100 online. The event covered topics like R package usage in the pharma industry. Later that year, we organized another event called “Open Source Clinical Reporting summeR“. \n\nLately, I have been busy organizing several events. I recently gave a talk (about R package dependencies as directed in acyclic graphs) at a conference hosted by the R community in China. Early next month, on August 1st, I will attend a pharma conference where I will conduct a workshop on good practices in software package development. The conference schedule is quite packed for me as I also have a session on how teams operate and collaborate within the Pharma industry to develop R packages. On the third day of the conference, I will organize a series of 11 data visualization talks, one of which is about Python. Most of the talks will focus on using R, except for one discussion on Python.\nCan you share what the R community is like in China? \n\nWe have opened up seats for students to join our events in the pharmaceutical industry. In the past, fewer than 20 students, mostly from academia, have joined us for these conferences. The events include big names like Roche, Johnson & Johnson, Novartis, Boehringer Ingelheim, and Sanofi and local companies such as Fosun, Hengrui, and Legend Biotech. There is a big R community in China across academia and industry. Our user group primarily focuses on the pharma industry. Our WeChat channel has nearly a thousand subscribers, and our group chat has almost 500 members. It’s a very active community. \nLater this year, we will collaborate with the “R in Pharma” for the October conference. Daniel Sabanes Bove and I have contacted Harvey and Phil, and we will organize an APAC track, including India, China, Japan, Australia, Singapore, and Korea. \nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nWe have created a GitHub account called PharmaRUG. We use this platform to share websites, posts, slides, and videos related to our events. The Pharma RUG 2024 conference was particularly successful this year, thanks to the support from the R Consortium. We also utilize WeChat groups to call for speakers and interact with others. In addition to GitHub and WeChat, we use Tencent Docs to share documents. This is particularly useful in China, where using company-specific platforms like Google or Microsoft can be hindered by firewalls. Tencent Docs works perfectly in China, making sharing and synchronizing documents easy.\nCan you share some valuable tips for organizing succesful Hybrid events?\n\nWe have a series of planning sessions where we actively communicate using WeChat. We meet at a community center where everyone is open, and we have preset meetings. We test the audio and everything beforehand. This is our second year organizing these events, so we have gained more experience. We are now familiar with the standards and know what needs to be done. For example, when two companies, like MNCs, use different systems, we find it better to use one shared system to ensure everything is synchronized.\nWe’ve found that Microsoft Teams is easy to use for setting up meetings and scheduling them ahead of time. For live demos, we recommend pre-recording the demos and taking questions. In the case of hybrid sessions with multiple locations, we prioritize asking and answering questions based on the primary and secondary locations, as well as online participation. If we cannot answer questions quickly, we host Q&A sessions afterward and share them online.\nI believe that for the event to be successful, timing is crucial. We must stick to the schedule because it’s a hybrid event. However, we should also allow for some flexibility when unexpected things come up. We haven’t created a YouTube account yet because YouTube isn’t accessible in China. One alternative could be setting up a Bilibili web page and account to share the videos. All our files are currently on GitHub, which is convenient. We need to trim the videos to smaller sizes to fit GitHub’s file size limits, maybe at four and a half speeds or similar.\nWhat trends do you currently see in R language and your industry?\nSo, SAS has dominated the software space for the Pharma industry for decades. While it used to be used for exploratory and research purposes, there have been successes with using Office to support missions in recent years. Roche also has success stories in this area. There are several initiatives, with PharmaVerse being a significant player. Roche is part of PharmaVerse, taking inspiration from the tidyverse multiverse concept. The end-to-end clinical reporting process is considered in this space, from data preparation to TLG generations. A lot has happened in the past three to four years, especially in China last year. There’s been significant development in China, and you can see a shift from SAS to R in the tools used. At the PharmaSUG meeting, which was previously dominated by SAS users, in the past few years, a quarter to one-third of the tools are using languages other than SAS. It’s clear that things are moving away from SAS towards software languages like R.\nThis year, I don’t have the complete statistics with me right now, but you do see a lot of topics. In my session, I’m sharing, and you know, many talks use visualization because it’s much likable. So, the trend is that R is becoming more acceptable than before, from PLCs to things in production. There are very high standards for codes and validation.\nIn the end, I would like to thank my dear friends and colleagues for their support and for making this happen\n\nYan Qiao, Associate Director of Scientific Programming, Beigene, \nBaoqin Li, China Head Clinical & Statical Programming, Johnson & Johnson\nDong Guo, China head of Stats Analyst, Eli-lilly&Company\nYun Ma, Director, clinical data Sciences, Boehringer Ingelheim (china) Investment Co.\nYanli Chang, Head of Data Operations China, Novartis\n\nHow do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute." }, { - "objectID": "codeofconduct.html#committed-to-a-safe-and-inclusive-environment-for-the-r-consortium-community", - "href": "codeofconduct.html#committed-to-a-safe-and-inclusive-environment-for-the-r-consortium-community", - "title": "Code of Conduct", + "objectID": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html", + "href": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html", + "title": "Offa R Users Group: Empowering Data-Driven Education in Nigeria", "section": "", - "text": "The R Consortium and its working groups are dedicated to providing a harassment-free experience for participants at all of our events, whether they are held in person or virtually. R Consortium events are working conferences intended for professional networking and collaboration within the open source community. They exist to encourage the open exchange of ideas and expression and require an environment that recognizes the inherent worth of every person and group. While at R Consortium events or related ancillary or social events, any participants, including members, speakers, attendees, volunteers, sponsors, exhibitors, booth staff and anyone else, should not engage in harassment in any form.\nThis Code of Conduct may be revised at any time by The R Consortium and the terms are non-negotiable. Your registration for or attendance at any R Consortium event, whether it’s held in person or virtually, indicates your agreement to abide by this policy and its terms.\n\n\nAll event participants, whether they are attending an in-person event or a virtual event, are expected to behave in accordance with professional standards, with both this Code of Conduct as well as their respective employer’s policies governing appropriate workplace behavior and applicable laws.\n\n\n\nHarassment will not be tolerated in any form, whether in person or virtually, including, but not limited to, harassment based on sex, gender, sexual orientation, disability, physical appearance, body size, race, age, religion or any other status protected by laws in which the conference or program is being held. Harassment includes the use of abusive, offensive or degrading language, intimidation, stalking, harassing photography or recording, inappropriate physical contact, sexual imagery and unwelcome sexual advances or requests for sexual favors. Any report of harassment at one of our events, whether in person or virtual, will be addressed immediately. Participants asked to stop any harassing behavior are expected to comply immediately. Anyone who witnesses or is subjected to unacceptable behavior should notify a conference organizer at once.\nExhibitors should not use sexualized images, activities, or other material in their booths and must refrain from the use of sexualized clothing, uniforms, costumes, or otherwise creating a sexualized environment. Speakers should not use sexual language, images, or any language or images that would constitute harassment as defined above in their talks.\nIndividuals who participate (or plan to participate) in R Consortium events, whether its an in-person event or a virtual event, should conduct themselves at all times in a manner that comports with both the letter and spirit of this policy prohibiting harassment and abusive behavior, whether before, during or after the event. This includes statements made in social media postings, on-line publications, text messages, and all other forms of electronic communication.\n\n\n\nIf a participant engages in harassing behavior, whether in person or virtually, the conference organizers may take any action they deem appropriate depending on the circumstances, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nIf a participant (or individual wishing to participate in an R Consortium event, in-person and/or virtual), through postings on social media or other online publications or another form of electronic communication, engages in conduct that violates this policy, whether before, during or after a R Consortium event, the R Consortium may take appropriate corrective action, which could include imposing a temporary or permanent ban on an individual’s participation in future R Consortium events, events, working groups, trainings or other activities.\n\n\n\nIf you are being harassed, notice that someone else is being harassed, or have any other concerns relating to harassment, please contact a member of the conference staff immediately. You are also encouraged to contact abuse@r-consortium.org.\n\n\n\nOur staff has taken incident response training and responds to harassment reports quickly and thoroughly. As referenced above, if a participant engages in harassing behavior, whether in-person or virtually, the conference organizers may take any action they deem appropriate, ranging from issuance of a warning to the offending individual to expulsion from the conference with no refund, depending on the circumstances. The R Consortium reserves the right to exclude any participant found to be engaging in harassing behavior from participating in any further R Consortium events, working groups, trainings or other activities.\nConference staff will also provide support to victims, including, but not limited to:\n\nProviding an Escort\nContacting Hotel/Venue Security or Local Law Enforcement\nBriefing Key Event Staff For Response/Victim Assistance\nAnd otherwise assisting those experiencing harassment to ensure that they feel safe for the duration of the conference.\n\n\n\n\nIf you are planning to attend an upcoming event, whether in-person or virtually and have concerns regarding another individual who may be present, please contact conduct@r-consortium.org. Precautions will be taken to ensure your comfort and safety, including, but not limited to providing an escort, prepping onsite event staff, keeping victim and harasser from attending the same talks/social events and providing onsite contact cell phone numbers for immediate contact." - }, - { - "objectID": "members.html#platinum-members", - "href": "members.html#platinum-members", - "title": "R Consortium", - "section": "Platinum Members", - "text": "Platinum Members" + "text": "The R Consortium had a conversation with Anietie Edem Udokang, who is the founder and organizer of the Offa R Users Group (ORUG). He discussed the emerging local R community and the use of R for his research in time series analysis.\nThe Offa R Users Group has a Meetup coming up on March 26th, 2024, titled “Test for the Assumptions of Linear Regression Using R.” The group is also seeking individuals to serve as guest speakers for their online events.\nPlease share about your background and involvement with the RUGS group.\nMy name is Anietie Edem Udokang, and I am a chief lecturer at the Federal Polytechnic Offa. I hold a Master of Science degree in Statistics. It was during my postgraduate studies that my supervisor introduced me to R, which was around 2012. Since then, I’ve been using R and have discovered that it’s far superior to some of the other software programs I had previously used.\nI have found that interacting with others and utilizing specific features, such as the ability to download applications, has been incredibly beneficial to my analysis work. These special packages have helped me greatly, and I believe it is important to attach relevant packages when organizing data. This experience has made me passionate about using R for data analysis.\nEver since I began using R, I have had the privilege of engaging with a diverse group of individuals, including data scientists and software users. These interactions have led me to the realization that to continue growing and learning, it would be beneficial to establish a user group within our community. Initially, we called it the “Fedpofa R Users Group,” but later changed the name to “Offa R Users Group.” We have been organizing meetings, providing training, and engaging in other activities to keep the community vibrant.\nCan you share what the R community is like in Offa?\nR is not limited to academic use, but it is also used in industry. The reason for this is that polytechnics act as a bridge between the industry and academic institutions. If the students have a good grasp of how to use R, it means that industry will be directly or indirectly affected. Consultants often visit our ORUG and ask for some analysis, which we provide using R. Additionally, students also use R for their projects.\nI use R for many of my publications. R has gained a lot of popularity, not only within our institution but also among sister institutions in the area. Some departments have even made R the only software that students are required to use for analysis.\nWhat industry are you currently in? How do you use R in your work?\nI am in the education sector, and I use R for my work in time series analysis, which is my area of specialization. I rely on TSA, tseries and other related time series packages to carry out my work. For example, I used R for Modeling the Residuals of Financial Time Series with Missing Values for Risk Measures, which was my MSc project. I have also used R in the Application of the Seasonal Autoregressive Moving Average Model to Analyze and Forecast the Food Price Index (free registration required). Additionally, I used R in a paper titled “Volatility of Exchange Rates in Nigeria: An Investigation of Risk on Investment.” In another innovative project was Modelling Circular Time Series with Applications. These are just a few examples of the papers and research where I’ve personally used R.\nYou have a Meetup titled Test for the Assumptions of Linear Regression Using R, can you share more on the topic covered? Why this topic?\nSome authors use regression models without checking whether the assumptions hold or not. Instead of carrying out tests to confirm this, they assume that the model is valid if the assumptions are fulfilled. This topic aims to highlight the importance of carrying out such tests to ensure reliable and comprehensive results. Lack of adherence to the assumptions may lead to inaccurate conclusions. The focus will be on commonly used tests for normality, linearity, autocorrelation, heteroscedasticity/homoscedasticity, and multicollinearity, with illustrative examples using R.\nI appreciate the R Consortium for their valuable RUGs grant assistance in 2022. With this grant, I could open two other user groups: the Ilorin R Users Group and the Kwara Environmental Statistics R Group. I also want to express my gratitude to the R Consortium for sponsoring my Meetup subscription and covering other minor expenses in 2022. The subscription is still ongoing, and I hope that we can continue our partnership to promote the use of R in our community.\nI would like to request for speakers to present at our R User Group. We are currently seeking speakers for our upcoming events and would be delighted to welcome speakers from all over the world to share their R-related knowledge with us." }, { - "objectID": "members.html#silver-members", - "href": "members.html#silver-members", - "title": "R Consortium", - "section": "Silver Members", - "text": "Silver Members" + "objectID": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html#how-do-i-join", + "href": "posts/offa-r-users-group-empowering-data-driven-education-in-nigeria/index.html#how-do-i-join", + "title": "Offa R Users Group: Empowering Data-Driven Education in Nigeria", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html", - "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html", - "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", + "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html", + "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html", + "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", "section": "", - "text": "The R Consortium is excited to announce that, on September 20, 2024, the R Submissions Working Group successfully submitted its latest test submission package—featuring a WebAssembly component—through the FDA’s Electronic Common Technical Document (eCTD) gateway! This marks a significant milestone as the FDA Center for Drug Evaluation and Research (CDER) staff has officially received the submission package.\nStatistician Eric Nantz at pharmaceuticals company Eli Lilly in Indianapolis, Indiana, says that using WebAssembly “will minimize, from the reviewer’s perspective, many of the steps that they had to take to get the application running on their machines.”\nThe complete set of submission materials is available publicly on GitHub: R Consortium Submissions Pilot 4." + "text": "The R Validation Hub next meeting is May 21st, 12:00 PM EST." }, { - "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-pilot-4-project", - "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-pilot-4-project", - "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", - "section": "About the Pilot 4 Project", - "text": "About the Pilot 4 Project\nThe objective of the R Consortium R submission Pilot 4 Project is to explore the use of novel technologies such as Linux containers and WebAssembly to bundle a Shiny application into a self-contained package, facilitating a smoother process of both transferring and executing the application. The application was built using the source data sets and analyses contained in the R submission Pilot 1-3. To our knowledge, this is the first publicly available submission package that includes a WebAssembly component. We hope this submission package and what we have learned can serve as a good reference for future regulatory submission efforts. The WebAssembly technology compiles applications into a portable, consistent environment driven by a web browser, allowing agency reviewers to easily run and evaluate software without complex setups. The second half of the Pilot 4 Project (leveraging container technology to package a Shiny application) will be submitted as an additional package later this year. Additional agency feedback will be shared in future communications." + "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here", + "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here", + "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", + "section": "Join the call here! ", + "text": "Join the call here! \nIn the dynamic field of pharmaceutical research, open source R packages offer incredible potential to innovate and enhance efficiency. The R Validation Hub is guiding the community building riskmetric and the riskassessment app. riskmetric is a framework to quantify an R package’s “risk of use” by assessing a number of meaningful metrics designed to evaluate package development best practices, code documentation, community engagement, and development sustainability. Together, the riskassessment app and the riskmetric package aim to provide some context for validation within regulated industries. \nThe benefits of utilizing open source tools in pharmaceutical projects are compelling. To address these issues and maximize their potential, join us at the R Validation Hub community meeting on May 21st at 12:00 PM EST. This gathering will focus on sharing best practices, troubleshooting common problems, and exploring innovative solutions together.\nEmbrace the opportunity to transform pharmaceutical research with us. Let’s innovate, collaborate, and overcome these hurdles together." }, { - "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-r-submissions-working-group", - "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#about-the-r-submissions-working-group", - "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", - "section": "About the R Submissions Working Group", - "text": "About the R Submissions Working Group\nThe R Consortium R Submissions Working Group is focused on improving practices for R-based clinical trial regulatory submissions.\nHealth authority agencies from different countries require electronic submission of data, computer programs, and relevant documentation to bring an experimental clinical product to market. In the past, submissions have mainly been based on the SAS language.\nIn recent years, the use of open source languages, especially the R language, has become very popular in the pharmaceutical industry and research institutions. Although the health authorities accept submissions based on open source programming languages, sponsors may be hesitant to conduct submissions using open source languages due to a lack of working examples.\nTherefore, the R Submissions Working Group aims to provide R-based submission examples and identify potential gaps while submitting these example packages. All materials, including submission examples and communications, are publicly available on the R consortium GitHub page." + "objectID": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here-1", + "href": "posts/Tackling-Hurdles-Embracing-Open-Source-Packages-in-Pharmaceutical-Research/index.html#join-the-call-here-1", + "title": "Tackling Hurdles: Embracing Open Source Packages in Pharmaceutical Research", + "section": "Join the call here!", + "text": "Join the call here!" }, { - "objectID": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#join-the-r-submissions-working-group", - "href": "posts/using-r-to-submit-research-to-the-fda-pilot-4-successfully-submitted/index.html#join-the-r-submissions-working-group", - "title": "Using R to Submit Research to the FDA: Pilot 4 Successfully Submitted to FDA Center for Drug Evaluation and Research", - "section": "Join the R Submissions Working Group", - "text": "Join the R Submissions Working Group\nThe R Submissions Working Group comprises members from over 10 pharmaceutical companies, as well as regulatory agencies. We are a collaborative community open to anyone interested in contributing to this important work. For more information, or to get involved, visitour website or contact us directly at director@r-consortium.org." + "objectID": "posts/r4socialscience-empowering-social-science-research/index.html", + "href": "posts/r4socialscience-empowering-social-science-research/index.html", + "title": "R4SocialScience: Empowering Social Science Research with R in India", + "section": "", + "text": "Dr. Mohit Garg, organizer of the R4SocialScience group in Delhi, India recently talked to the R Consortium about his experience of starting an R user group. The R4SocialScience group aims to bridge the gap between social science research and data analysis, offering support and training to academics, researchers, and industry professionals. Dr. Garg shares his experiences, the growth of the R community in India, and his plans for expanding R’s reach.\nPlease share about your background and involvement with the RUGS group.\nI’m currently working as an assistant librarian at the Indian Institute of Technology, Delhi, one of the premier institutions in India.  My academic background includes a BTech in Information Technology from Guru Gobind Singh Indraprastha University followed by an MS in Librarian Information Science from the Indian Statistical Institute, an institution dedicated to statistics in India started by the late Professor P.C. Mahanobis. After that, I completed my PhD in Library and Information Science from IGNOU, New Delhi.\nMy interest in R began in 2013 when I started my MS at the Indian Statistical Institute.  Since then, I have taken various courses as part of my MS program and some online courses. I became interested in R due to its open source nature and the free availability of packages for all kinds of analysis. Then, I started promoting R in the academic community. However, in 2013, there was little interest in R because the prevalent approach in India was more focused on using commercial software for data analysis.  However, in the past few years, there has been an increasing interest in R, with many workshops and government-funded events dedicated to it.\nI have been providing R training to professors, teachers, and research scholars, and I have also worked on web-based development using Shiny packages. Furthermore, we have developed a web dashboard to visualize real-time research productivity data obtained from sources like Scopus through API. Recently, we completed a 12-week MOOC course on NPTEL SWAYAM platform with a focus solely on R. The course was quite popular, with 2584 learners from India joining, and 515 learners registering for the final examination. Although the course was free, participants had the option to pay for certification.\nCan you share what the R community is like in India?\nI have been involved in the academic profession since 2016 and have been giving lectures and providing resource points at various institutions. I believe that there is a need to build a community focused on social sciences, especially for those who may have a limited understanding of mathematics, and statistics. The idea is to create a specific community related to social science, not just in India, but also in collaboration with other institutions. The community will cater to three main groups: those who are proficient in coding and development of R packages, those who are familiar with basic R but need further guidance, and those who are completely new to R.\nThe community aims to provide support for those interested in social science and to make R more accessible by offering packages related to social science, basic R tutorials. One specific package gaining popularity in academia is “biblo shiny bibliometrics,” which facilitates scientific productivity mapping using R.\nWe want to emphasize that R is not just a programming language, but a software for data analysis, to encourage more people to explore its potential. While both R and Python are interpreted languages, we aim to dispel the fear of programming and demonstrate how these languages can be used effectively. Although Python appears to be more widely used in the industry, there is still a growing interest in R.\nWhat are your plans for the group going forward?\nI have been teaching R for more than 10 years, and I found that researchers are interested in using R. I have identified three potential co-organizers from different regions in India to make a team of four people. We have already received a grant, and we plan to conduct training sessions in different locations across India.\nI am focusing on a “train the trainer” model, where I aim to train individuals who can then carry out training sessions in their respective regions. India has over 50,000 colleges and around 1,200 universities, all involved in significant research and analysis activities. We also aim to have dedicated R trainers in all districts in India by 2026.\nOur approach involves dividing the country into five zones, followed by state-wise and district-wise planning. We are not heavily reliant on industry support, as our activities are primarily related to academia and research.\nWe plan to charge a nominal registration fee, which would cover expenses such as food and refreshment. We are hoping to minimize travel expenses, as they can be quite costly. But we will explore some way to fund the travel and accommodation expenses. We have hosted a one day workshop on “Doing Research using R” at Galgotias University.\nI am currently focusing on building a community and providing training sessions. I have noticed that online sessions may not be as effective as I had hoped, as participants seem to encounter many problems. Therefore, I am considering conducting more in-person workshops, which I believe will help popularize the training sessions. Additionally, I aim to develop specialized packages for social science and build a dedicated team. I am optimistic about these plans. During a recent workshop, I noticed that many participants preferred simple tools for data analysis. I intend to introduce such tools to make the training more accessible and user-friendly for participants. This is my vision for the community.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nWe have developed a platform utilizing the shiny and other text mining packages. This platform is still in the testing phase. The platform allows real-time data fetching from the Scopus API.\nFor example, if I search for a faculty member, it will display the publication data such as the number of publications, H-index, citations, types of publications, sources of publication, and annual publication distribution. We can also download this data.\nWe have also developed a word cloud based on the titles of the publications for each faculty member, processed using the TM package. This helps to infer the expertise of the professors. Furthermore, we have included a feature for identifying the H-classic, which is related to the H-index.  This platform is quite useful and efficient, especially for academic institutions. We now have the capability to download data from a specific date range as an Excel file. The data includes publication dates and the number of citations.\nWe’re in the process of creating a full dashboard for universities or institutions. We’ve also conducted a pilot study for other institutions. We are also considering publishing this work as a research paper to increase its visibility." }, { - "objectID": "posts/the-cleveland-r-user-groups-journey-through-pandemic-adaptations-and-baseball-analytics-r-consortium/index.html", - "href": "posts/the-cleveland-r-user-groups-journey-through-pandemic-adaptations-and-baseball-analytics-r-consortium/index.html", - "title": "The Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics", - "section": "", - "text": "Last year, R Consortium talked to John Blischak and Tim Hoolihan of the Cleveland R User Group about their regular structured and casual virtual meetups during the pandemic. Recently, Alec Wong, another co-organizer of the Cleveland R User Group, updated the R Consortium about how the group provides a networking platform for a small but vibrant local R community. Alec shared details of a recent event from the group regarding the use of R for analyzing baseball data. He also discussed some tools for keeping the group inclusive and improving communication among group members.\n\n\n\nPlease share about your background and involvement with the RUGS group.\nI completed my Bachelor of Science degree in Fisheries and Wildlife from the University of Nebraska-Lincoln in 2013, and my Master of Science degree in Statistical Ecology from Cornell University in late 2018. During my graduate program, I gained extensive experience using R, which is the de facto language of the ecological sciences. I discovered a passion for the language, as it is extremely intuitive and pleasant to work with.\nAfter completing my program in 2018, I moved to Cleveland and immediately began attending the Cleveland R User Group in 2019, and have been a consistent member ever since. I eagerly look forward to each of our events.\nAfter completing my graduate program, I started working at Progressive Insurance. Working for a large organization like Progressive provides me with many diverse opportunities to make use of my extensive experience with R. I was happy to find a vibrant R community within the company, which allowed me to connect with other R users, share knowledge, and I enthusiastically offer one-on-one assistance to analysts from all over Progressive.\nStarting in 2022, I accepted the role of co-organizer of the Cleveland R User Group. As a co-organizer, I help with various tasks related to organizing events, such as the one we held last September. I am passionate about fostering the growth of these communities and helping to attract more individuals who enjoy using R.\nOur group events are currently being held in a hybrid format. When we manage to find space, we will meet in person, such as when we met to view the 2023 posit::conf in October–several members visited in person and watched and discussed videos from the conference. Most of our meetups continue to be virtual, including our Saturday morning coffee meetups, but we are actively searching for a more permanent physical space to accommodate our regular meetups.\nI am only one of several co-organizers of the Cleveland R user group. The other co-organizers include Tim Hoolihan from Centric Consulting, John Blischak who operates his consulting firm JDB Software Consulting, LLC, and Jim Hester, currently a Senior Software Engineer atNetflix. Their contributions are invaluable and the community benefits tremendously from their efforts.\nCan you share what the R community is like in Cleveland? \nI believe interest in R has been fairly steady over time in Cleveland since 2019. We have a handful of members who attend regularly, and typically each meeting one or two new attendees will introduce themselves.\nI would venture to say that R continues to be used frequently in academic settings in Cleveland, though I am ‌unfamiliar with the standards at local universities. At least two of our members belong to local universities and they use R in their curricula.\nAs for industry usage, many local companies, including Progressive use R. At Progressive, we have a small, but solid R community; although it is not as large as the Python community, I believe that the R community is more vibrant. This seems characteristic of R communities in varying contexts, as far as I’ve seen. Another Cleveland company, the Cleveland Guardians baseball team, makes use of R for data science. In September 2023 we were fortunate to invite one of their principal data scientists to speak to us about their methods and analyses. (More details below.)\nTypically, our attendance is local to the greater Cleveland area, but with virtual meetups, we’ve been able to host speakers and attendees from across the country; this was a silver lining of the pandemic. We also hold regular Saturday morning coffee and informal chat sessions, and it’s great to see fresh faces from outside Cleveland joining in.\nYou had a Meetup titled “How Major League Teams Use R to Analyze Baseball Data”, can you share more on the topic covered? Why this topic?\nOn September 27th, 2023, we invited Keith Woolner, principal data scientist at the Cleveland Guardians baseball team, to give a presentation to our group. This was our first in-person meetup after the pandemic, and Progressive generously sponsored our event, affording us a large presentation space, food, and A/V support. We entertained a mixed audience from the public as well as Progressive employees.\nKeith spoke to us about “How Major League Baseball Teams Use R to Analyze Baseball Data.” In an engaging session, he showcased several statistical methods used in sports analytics, the code used to produce these analyses, and visualizations of the data and statistical methods. Of particular interest to me was his analysis using a generalized additive model (GAM) to evaluate the relative performance of catchers’ ability to “frame” a catch; in other words, their ability to convince the umpire a strike occurred. The presentation held some relevance for everyone, whether they were interested in Cleveland baseball, statistics, or R, making it a terrific option for our first in-person presentation since January 2020. His presentation drove a lot of engagement both during and after the session.\n\n\n\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future? \nOne of our co-organizers, John Blischak, has created a slick website using GitHub Pages to showcase our group and used GitHub issue templates to create a process for speakers to submit talks. Additionally, the Cleveland R User group has posted recordings of our meetups to YouTube since 2017, increasing our visibility and accessibility. Many people at Progressive could not attend our September meetup and asked for the recording of our September 2023 meetup as soon as it was available.\nRecently, we have also created a Discord server, a platform similar to Slack. This was suggested by one of our members, Ken Wong, and it has been a great addition to our community. We have been growing the server organically since October of last year by marketing it to attendees who visit our events, particularly on the Saturday morning meetups. This has opened up an additional space for us to collaborate and share content asynchronously. Ken has done an excellent job of organizing the server and has added some automated processes that post from R blogs, journal articles, and tweets from high-profile R users. Overall, we are pleased with our progress and look forward to continuing to improve our initiatives.\n\nHow do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/r4socialscience-empowering-social-science-research/index.html#how-do-i-join", + "href": "posts/r4socialscience-empowering-social-science-research/index.html#how-do-i-join", + "title": "R4SocialScience: Empowering Social Science Research with R in India", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/r-ladies-cotonou-a-community/index.html", - "href": "posts/r-ladies-cotonou-a-community/index.html", - "title": "R-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women", + "objectID": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html", + "href": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html", + "title": "Gergely Daróczi’s Journey: Empowering R Users in Hungary", "section": "", - "text": "Nadejda Sero, the founder of the R Ladies Cotonou chapter, shared with the R Consortium her experiences learning R, the challenges of running an R community in a developing country, and her plans for 2024. She also emphasized the importance of considering the realities of the local R community when organizing an R User Group (RUG).\nPlease share about your background and involvement with the RUGS group.\nMy name is Nadejda Sero, and I am a plant population and theoretical ecologist. I have a Bachelor of Science in Forestry and Natural Resources Management and a Master of Science in Biostatistics from the University of Abomey-Calavi (Benin, West Africa). I discovered R during my Master’s studies in 2015. From the first coding class, I found R exciting and fun. However, as assignments became more challenging, I grew somewhat frustrated due to my lack of prior experience with a programming language.\nSo, I jumped on Twitter (current X). I tweeted, “The most exciting thing I ever did is learning how to code in R!” The tweet caught the attention of members of the R Ladies global team. They asked if I was interested in spreading #rstats love with the women’s community in Benin. I was thrilled by the opportunity and thus began my journey with R-Ladies Global.\nThe early days were challenging due to the novelty of the experience. I did not know much about community building and social events organization. I started learning about the R-Ladies community and available resources. The most significant work was adjusting the resources/tools used by other chapters to fit my realities in Benin. My country, a small French-speaking developing African country, had poor internet access and few organizations focused on gender minorities. (We are doing slightly better now.) On top of that, I often needed to translate some materials into French for the chapter.\nAs I struggled to make headway, the R-Ladies team launched a mentoring program for organizers. I was fortunate enough to participate in the pilot mentorship. The program helped me understand how to identify, adjust, and use the most effective tools for R-Ladies Cotonou. I also gained confidence as an organizer and with community work. With my fantastic mentor’s help, I revived the local chapter of R-Ladies in Cotonou, Benin. I later joined her in the R-Ladies Global team to manage the mentoring program. You can read more about my mentoring experience on the R-Ladies Global blog.\nHappy members of R-Ladies Cotonou sharing some pastries after the presentation. At our first official meetup, the attendees discovered and learned everything about R-Ladies Global and R-Ladies Cotonou.\nI am grateful for the opportunity to have been a part of the R-Ladies community these last six years. I also discovered other fantastic groups like AfricaR. I am particularly proud of the journey with R-Ladies Cotonou. I am also thankful to the people who support us and contribute to keeping R-Ladies Cotonou alive.\nCan you share what the R community is like in Benin?\nR has been commonly used in academia and more moderately in the professional world over the past 2-3 years. For example, I worked with people from different areas of science. I worked in a laboratory where people came to us needing data analysts or biostatisticians. We always used R for such tasks, and many registered in R training sessions. The participants of these sessions also came from the professional world and public health. I have been out of the country for a while now, but the R community is booming. More people are interested in learning and using R in different settings and fields. I recently heard that people are fascinated with R for machine learning and artificial intelligence. It is exciting to see that people are integrating R into various fields. There are also a few more training opportunities for R enthusiasts.\nCan you tell us about your plans for the R Ladies Cotonou for the new year?\nMore meetups from our Beninese community, other R-Ladies chapters, and allies.\nWe are planning a series of meetups that feature students from the training “Science des Données au Féminin en Afrique,” a data science with R program for francophone women organized by the Benin chapter of OWSD (Organization for Women in Science for the Developing World). We have three initial speakers for the series: the student who won the excellence prize and the two grantees from R-Ladies Cotonou. The program is an online training requiring good internet, which is unfortunately expensive and unreliable. If you want good internet, you must pay the price.\nR-Ladies Cotonou supported two students (from Benin and Burkina Faso) by creating a small “internet access” grant using the R Consortium grant received in 2020.\nThe meetup speaker is taking us through a review of the most practical methods of importing and exporting datasets in R. The attendees are listening and taking notes.\nThis next series of meetups will focus on R tutorials with a bonus. The speakers will additionally share their stories embracing R through the training. The first speaker, Jospine Doris Abadassi, will discuss dashboard creation with Shiny and its potential applications to public health. I hope more folks from the training join the series to share their favorite R tools.\nI believe these meetups will assist in expanding not only the R-Ladies but the entire R community. I particularly enjoy it when local people share what they have learned. It further motivates the participants to be bold with R.\nAbout “Science des Données au Féminin en Afrique“, it is the first time I know that a data science training is free for specifically African women from French-speaking areas. Initiated by Dr. Bernice Bancole and Prof. Thierry Warin, the program trains 100 African francophone women in data science using R, emphasizing projects focused on societal problem resolution. The training concluded its first batch and is now recruiting for the second round. So, the community has expanded, and a few more people are using R. I appreciate that the training focuses on helping people develop projects that address societal issues. I believe that it enriches the community.\nAs I said in my last interview with the R consortium, “In some parts of the world, before expecting to find R users or a vivid R community, you first need to create favorable conditions for their birth – teach people what R is and its usefulness in professional, academic, and even artistic life.” It is especially true in Benin, whose official language is French. English is at least a third language for the average multilingual Beninese. Many people are uncomfortable or restrained in using R since most R materials are in English. I hope this OWSD Benin training receives all the contributions to keep running long-term. You can reach the leading team at owsd.benin@gmail.com.\nOur other plan is to collaborate with other R-Ladies chapters and RUGS who speak French. If you speak French and want to teach us something, please email cotonou@rladies.org.\nOtherwise, I will be working on welcoming and assisting new organizers for our chapter. So, for anyone interested, please email cotonou@rladies.org.\nAre you guys currently hosting your events online or in-person? And what are your plans for hosting events in 2024?\nWe used to hold in-person events when we started. Then, the COVID-19 pandemic hit, and we had to decide whether to hold events online. Organizing online events became challenging due to Cotonou’s lack of reliable internet access or expensive packages. As a result, we only held one online event with poor attendance. We took a long break from our activities.\nGoing forward, our events will be hybrid, a mix of in-person and online events. In-person events will allow attendees to use the existing infrastructure of computers and internet access of our allies. It also offers an opportunity to interact with participants. Therefore, I am working with people in Cotonou to identify locations with consistent internet access where attendees can go to attend the meetups. Online events will be necessary to accommodate speakers from outside of the country. It will be open to attendees unable to make it in person.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nThe techniques and tools should depend on the realities of the community. What language is comfortable for attendees? What meeting modality, online or in person, works best for participants?\nAs mentioned earlier, I was inexperienced, and organizing a chapter was daunting. My mentoring experience shifted my perspective. I realized that I needed to adjust many available resources/tools. Organizing meetups became easier as I integrated all these factors.\nFor example, our chapter prioritizes other communication and advertisement tools like regular emails and WhatsApp. The group is mildly active on social media, where the R community is alive (X/Twitter, Mastodon). It is easier to have a WhatsApp group to share information due to its popularity within our community. We recently created an Instagram account and will get LinkedIn and Facebook pages (with more co-organizers). I would love a website to centralize everything related to R-Ladies Cotonou. Using emails is an adjustment to Meetup, which is unpopular in Benin. Getting sponsors or partners and providing a few small grants for good internet would help tremendously our future online events.\nAdjusting helps us to reach people where they are. It is imperative to consider the community, its realities, and its needs. I often asked our meetup participants their expectations, “What do you anticipate from us?” “What would you like to see in the future?” Then, I take notes. Also, we have Google Forms to collect comments, suggestions, potential speakers, contributors, and preferred meeting times. It is crucial to encourage people to participate, especially gender minorities less accustomed to such gatherings.\nI have also attempted to make the meetups more welcoming and friendly in recent years. I always had some food/snacks and drinks available (thanks to friends and allies). It helps make people feel at ease and focus better. I hope the tradition continues for in-person meetups. It is valuable to make the meetups welcoming and friendly. How people feel is essential. If they come and feel like it is a regular lecture or course, they may decide to skip it. But, if they come to the meetup and learn while having fun, or at the very least, enjoy it a little, it benefits everyone.\nThese are some of the key aspects to consider when organizing a meetup. It is critical to consider the people since you are doing it for them. Also, make sure you have support and many co-organizers if possible.\nAll materials live on our GitHub page for people who can’t attend physical events. Another solution would be recording and uploading the session on the R-Ladies Global YouTube or our channel.\nWhat industry are you currently in? How do you use R in your work?\nI am now a Ph.D. student in Ecology and Evolutionary Biology at the University of Tennessee in Knoxville.\nR has no longer been my first programming language since I started graduate school. I still use R for data tidying data analysis but less extensively. I worked a lot with R as a master’s student and Biostatistician. It was constant learning and growth as a programmer. I had a lot of fun writing my first local package. However, I now work more with mathematical software like Maple and Mathematica. I wish R were as smooth and intuitive as this software for mathematical modeling. I like translating Maple code to R code, especially when I need to make visualizations.\nI am addicted to ggplot2 for graphs. I love learning new programming languages but am really attached to R (it’s a 9-year-old relationship now). I developed many skills while programming in R. R helped me become intuitive, a fast learner, and sharp with other programming languages.\nMy most recent project that utilized R, from beginning to end, was a project in my current lab on the evolutionary strategies of plants in stochastic environments. We used R for demographic data tidying and wrangling. Data analysis was a mix of statistical and mathematical models. It was a good occasion to practice writing functions and use new packages. I enjoy writing functions for any task to automate repetitive tasks, which reduces the need for copying and pasting code. I also learned more subtleties in analyzing demographic data from my advisor and colleagues who have used R longer." + "text": "Gergely Daróczi, the founder and organizer of the Budapest Users of R Network, updated the R Consortium about the group’s recent activities. Last year, Gergely discussed the group’s inception, and the challenges faced by the group during the pandemic. The group has now resumed in-person meetings, followed by networking sessions. The recent events organized by the group have focused on bioinformatics, large language models, and mathematical modeling.\nPlease share about your background and involvement with the RUGS group.\nI have a background in social sciences, and it was during one of my university classes 20 years ago that I was introduced to the R language. We had to use R to run simulations related to the chaotic behavior of the Hungarian potato market. I found R more enjoyable and versatile than other GUI tools like IBM’s SPSS and started using it for other projects as well. Later, I even developed some additional packages for R.\nI have been working with R for almost 20 years now. Despite my academic background in social sciences, I have worked in various industries, such as ad tech, fintech, and health tech, for the past 10 years.\nIn 2013, I attended my first useR! conference in Albacete, Spain, and it was a great experience to meet fellow R users from around the world. At the conference, I met Szilard Pafka, a Hungarian living in LA and organizer of the Los Angeles R User group. He suggested that I start an R User group in Hungary. After returning home, I decided to give it a shot, and we held our first meeting at the end of the summer of 2013. In a university room, it felt like there were only a dozen R users from academia. However, a lot has changed since then, as we now have almost 2,000 members in the local R User group, which exceeded my original expectations for such a small country like Hungary. It has been an interesting and great experience.\nIn Hungary, the community’s growth began slowly, with only 20 to 30 members in the first few years. However, it gradually increased over time. The community also hosted some famous personalities such as Romain Francois, Matt Dowle, and Hadley Wickham, which further accelerated its growth. Additionally, the community organized the first satRday and second ERUM conference, which provided a platform for networking and knowledge sharing, further strengthening the community.\nHow has the group been doing since our last conversation?\nAfter COVID, restarting the meetups was very challenging. We didn’t organize any virtual events because the main benefit of meetups was meeting in person, having face-to-face conversations, and getting to know each other. Therefore, we waited until the quarantine was over and it was safe to meet in person. We started slowly, organizing only two events per year with around 30 to 70 attendees, which was much lower than before COVID-19. However, it has been great to reconnect with old friends and make new ones.\nRecently, we have been focusing on bioinformatics and I was introduced to a local company that offered help with reaching out to speakers. Speakers drive these community meetings by bringing in a topic for discussion and talk, which we continue to discuss later on. Our past few events have focused on life sciences and have followed a lightning talk format, where we had around five 15-minute talks at each event. The topics were diverse, covering life sciences, some with LLMs involved, others focused on highly advanced math for modeling. We also had shiny applications that showed the biodiversity of forests in Hungary and some open-source tools besides R.\nAny techniques you recommend using for planning for or during the event?\nI can only offer subjective experiences on the matter, but I have witnessed the success of both virtual and in-person communities. However, our focus is on providing an exceptional in-person experience. To achieve this, we search for a central venue that is easily accessible for most of our members. This can be challenging, even in Hungary, a small country, as it can be difficult for members from other cities to travel to the capital for meetups. Nevertheless, we do our best to find a central venue, such as a university or an industry partner who can offer a space for talks and a networking opportunity afterward.\nIt is important to have a room with plenty of chairs and a larger area for people to gather after the talks. We can provide soft drinks, beer, or wine along with some pizzas and have a chat for an hour or two after the talk. The venue is a crucial factor. It’s also important to have speakers who are interested in the community so that they will come to learn as well. It’s great to have speakers with interesting topics, but the most important thing for me is networking. After the talks, coming together and getting to know others, learning about their struggles, and maybe sharing some tips in person with each other, becoming friends, or learning about opportunities in other industries. Networking and facilitating connections are crucial tasks for R user group organizers.\nWhat trends do you currently see in R language?\nFive years ago, machine learning models were a hot topic, and everyone discussed different implementations of GBM. However, things have changed, and nowadays, large language models (LLM) rule over all the topics. LLMs are often implemented in languages other than R, making it difficult to train them from R. Despite this, there are still many use cases for LLMs, even in life sciences and health tech. However, caution must be taken when using AI and LLMs in these fields. Recently, at two bioinformatics events, some nice use cases of LLMs were shared with the audience. This has attracted new members interested in learning how to use AI or LLMs, which can be as simple as doing some API integrations in R, such as calling the chatGPT API to generate text or images.\nI’m excited that COVID restrictions are easing up and meetups are returning to normal. I can’t wait for the first in-person useR! conference in Salzburg in a few months. I highly recommend that anyone who can travel to Salzburg in July join us. The city has excellent train connections to European cities, so I hope many people from Europe can make it. I’m looking forward to attending an in-person useR! conference again.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nCurrently, I’m focusing on the ETL pipeline of the Spare Cores project, collecting information on cloud compute resources, which will soon have the R bindings as well. In the past, I’ve been working on R packages related to reporting (e.g. “pander”) and using R in production (e.g. “logger,” “dbr” or “boto3”). Recently, I enjoyed integrating APIs and frameworks from other programming languages, such as Python (kudos to the reticulate team!), in R." }, { - "objectID": "posts/r-ladies-cotonou-a-community/index.html#how-do-i-join", - "href": "posts/r-ladies-cotonou-a-community/index.html#how-do-i-join", - "title": "R-Ladies Cotonou – A Community that Makes R Accessible for French-Speaking African Women", + "objectID": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html#how-do-i-join", + "href": "posts/gergely-daroczis-journey-empowering-r-users-in-hungary/index.html#how-do-i-join", + "title": "Gergely Daróczi’s Journey: Empowering R Users in Hungary", "section": "How do I Join?", "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/the-r-consortium-2023-a-year-of-growth-and-innovation/index.html", - "href": "posts/the-r-consortium-2023-a-year-of-growth-and-innovation/index.html", - "title": "The R Consortium 2023: A Year of Growth and Innovation", + "objectID": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html", + "href": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html", + "title": "Bridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students", "section": "", - "text": "Excerpted from the Annual Report\n\nAccess the annual report here!\nLetter from the Chair — Mehar Pratap Singh, Chairman\nWelcome to the 2023 Annual Report of the R Consortium. This document reflects a year of significant growth, innovation, and community engagement within and beyond the R ecosystem. As we present the accomplishments and milestones of the past year, we also set our sights forward, laying out the path for an even more collaborative and impactful future.  \nThe R Consortium serves as a central hub for the R community, bringing together industry leaders, academic institutions, and individual contributors to foster the development and proliferation of the R language. Our mission is to support the R community through funding, infrastructure improvement, community initiatives, and global outreach.  \nIn 2023, the R Consortium played a pivotal role in shaping the development of the R ecosystem. Through monetary grants, nearly $200,000 dollars to develop R packages and other technical infrastructure, through fostering industry wide collaborative working groups, and by supporting R-Ladies, R user groups, and several important industry conferences, including Latin-R, New York R, and Bioconductor conferences. This report highlights some of these achievements, showcasing the collective effort of our members and the broader community.  \nRecognizing the dynamic nature of data science technologies and the evolving needs of industry, we also recognize the responsibility of the R Consortium to help set a vision for the evolution of the R ecosystem. As you read through this report, we hope you’ll appreciate the strides we’ve made together and feel inspired by the potential of what we can achieve in the future. The R Consortium is more than just an organization: it’s a vibrant community of innovators, problem-solvers, and thought leaders. Together, we are shaping a future where the power of R is accessible to all and continues to drive progress across industries worldwide.   \nThank you for your continued support and dedication to the R Consortium and the wider R community. \n\n\nAccess the annual report here!" + "text": "Umar Isah Adam, the founder and organizer of the R User Group Kano, Nigeria, spoke with the R Consortium during the pandemic about his efforts to engage the next generation of students in the R community. Recently, the R Consortium followed up with Umar to discuss the group’s progress over the past few years. He discussed the increasing acceptance and interest in R within academia. The user group is working with various colleges in Kano state to introduce R to students and teach them the fundamentals. Umar also shared his experience using R for managerial tasks related to student data. He hopes to persuade college management to use R for data handling instead of the current manual processes.\nPlease share your background and involvement with the RUGS group.\nMy name is Umar Isah Adam, and I’m from Kano State, Nigeria. I studied mathematics at the Federal University Dutse, Jigawa State. During my studies, I became interested in statistics and technology. One of my lecturers mentioned R as a statistical analysis tool, which piqued my interest. I learned it by researching online and watching videos. Later, a friend introduced me to R User Groups. I found that I was interested in R and noticed there wasn’t a group in Kano State, so I applied to start a chapter there, and it was approved.\nCan you share what the R community is like in Kano, Nigeria?\nThe use of R is relatively new in Kano State. Most academics in the area use SPSS in their work. It makes it challenging for R to gain traction in this environment. Despite the challenges, we have been making progress with the support of our user group. Currently, I work as an assistant lecturer at a college in Kano State. I recently organized a well-attended seminar for lecturers and students at the Kano State College of Education and Preliminary Studies. I also posted a video of the workshop on YouTube and have received requests for more information.\nThere’s room for improvement. We’ve received requests from academic institutions to host events or provide information about the power of R. However, we cannot do so now due to the nature of my work and inadequate funding. However, we plan to start a 10-week training session soon. It will likely be free, as we are collaborating with the Kano State College of Education and Preliminary Studies to organize it. R isn’t very popular here, and more than 70% of academicians need help understanding what it is and how to use it effectively. However, those introduced to it have shown a high interest in learning and utilizing it.\nWe aim to introduce R to the academic community, and after this, we plan to move on to another college and launch a new program. In summary, R is not widely known in our society, but we are progressing. There has been an increase in the acceptance of R and a growing interest from different people in academia, particularly in R. Many are interested. Still, there needs to be more awareness about it. Most people need to learn what R is and how to use it. Therefore, most of our upcoming programs will focus on introducing the R language.\nAdditionally, there is an issue with student access. Most of our students don’t have personal computers and can only access them on campus, usually at the ICT department. This lack of access also affects student engagement. However, among academics and lecturers in our colleges, there is growing interest in R.\nDo you host in-person or online events? How do you make your events inclusive?\nIt’s important to remember that online events became essential during the pandemic. However, due to internet connectivity issues, we avoid online meetings or events most of the time. As a result, our sessions are usually held offline. We have been hosting events within colleges and other institutions to make them easily accessible to students and academics. It is also more cost-effective and popular than hosting in private locations. Advertising these events has proven effective, as interested individuals are usually willing to attend when they see the advertisement.\nWe attempted to transfer between colleges, such as those owned by the state government. The majority of the data and processes are research-based. Therefore, we strive to incorporate more R programming aligned with academic requirements. We aim to limit topics to the use of R in academia to ensure that attendees feel more connected and can see the practical applications of using R. For instance, compared to using SPSS, where one often needs to use code or convert data into another format, with R, one can easily import data into the working environment and manipulate it as needed.\nPlease share about a project you are currently working on or have worked on using the R language. What is the goal/reason, result, or anything interesting, especially related to your industry?\nI usually demonstrate to people around me, including the school management, how easy it is to use R. For example, we need help with the examination office potentially losing some of their data. However, they have a backup on an external drive. I am importing the data from the old template to the new one in Excel format. I am also working on calculating the student results and offloading them into the new portal we have developed. Doing this job manually might take a month, but if I successfully create this program, it will complete the job in two to three days. It will demonstrate to the school management the importance and impact of using R.\nI am proposing to the college management to introduce a certified course of study on “Introduction to R” within the ICT department. Showcasing how this programming language can impact the working environment will help them understand the need for this course. Many students rely on fundamental analyses using questionnaires, frequency, and percentage without exploring visualization techniques. As a supervisor, I encourage using R for data analysis in student projects, as it provides a more comprehensive approach. However, many students need access to computers. Therefore, by offering this course, we can equip them with valuable skills and knowledge to benefit their future careers." }, { - "objectID": "posts/R-Medicine-is-coming-June-10-14-2024-See-Top-Five-R-Medicine-Talks-from-Previous-Years/index.html", - "href": "posts/R-Medicine-is-coming-June-10-14-2024-See-Top-Five-R-Medicine-Talks-from-Previous-Years/index.html", - "title": "R/Medicine is coming June 10-14, 2024 – See Top Five R Medicine Talks from Previous Years", - "section": "", - "text": "What to get a feel for the kind of content will be available at R/Medicine 2024? We’re spotlighting the most engaging and educational sessions from past R Medicine Virtual Conferences. Whether you’re a healthcare professional, a data scientist, or simply curious about the intersection of healthcare and technology, these selected talks offer a wealth of knowledge and innovation using the R programming language. Dive into these sessions to enhance your understanding and skills in medical data science.\n\n🔗 Register for the R Medicine 2024 Virtual Conference here!\n\n\n1. GitHub Copilot in Rstudio, It’s Finally Here! – R Medicine Virtual Conference 2023\nThis session introduces GitHub Copilot for RStudio, a highly anticipated tool that enhances coding efficiency and innovation in medical research. Watch as experts demonstrate its capabilities and potential impact on healthcare data analysis.\n\n\n\n\n2. Analyzing Geospatial Data in R (Sherrie Xie) – R/Medicine 2022 Virtual Conference\nFeaturing Sherrie Xie, this presentation explores the applications of geospatial data analysis within the healthcare sector using R. Gain insights into the importance of spatial data in understanding health trends and outcomes.\n\n\n\n\n3. R/Medicine 101: Intro to R for Clinical Data (Stephan Kadauke, Joe Rudolf, Patrick Mathias) – R/Medicine 2022\nThis introductory session is perfect for those new to using R in a clinical setting. The speakers guide you through the basics and demonstrate how R can revolutionize medical research and patient care.\n\n\n\n\n4. Introduction to R for Medical DataTidy Spreadsheets in Medical Research – R/Medicine 2021\nUMich Prof and {medicaldata} author Peter Higgins will cover best practices for using medical data in spreadsheets like Excel and Google Sheets.\n\n\n\n\n5. Multistate Data Using the {survival} Package – R/Medicine 2021\nExplore the use of the {survival} package in R for analyzing multistate data. Discover the methods and models that are shaping the future of survival analysis in medical research.\n\n\nEngage and Learn More!\nEach of these sessions provides unique insights and practical tools for harnessing the power of R in medical research and healthcare analytics. Whether you are watching these for the first time or revisiting them, each video promises a deep dive into the capabilities of R that are driving advancements in the field.\n📢 Mark Your Calendars! The R Medicine Conference for this year is scheduled for June 10-14. Register now to secure your spot and connect with a community of like-minded professionals!\n\n\n🔗 Register for the R Medicine 2024 Virtual Conference here!\nRemember to subscribe to the R Medicine channel for more updates and upcoming conference information. Enhance your skills in medical data science today!" + "objectID": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html#how-do-i-join", + "href": "posts/bridging-the-digital-divide-umar-isah-adam-on-expanding-r-access-for-kano-nigeria-students/index.html#how-do-i-join", + "title": "Bridging the Digital Divide: Umar Isah Adam on Expanding R Access for Kano, Nigeria Students", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html", - "href": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html", - "title": "Navigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors", + "objectID": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html", + "href": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html", + "title": "Empowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative", "section": "", - "text": "The R Consortium recently spoke with Mario Annau, co-organizer of the Vienna R User Group. During the conversation, he discussed the use of R in the finance and pharmaceutical industries in Vienna. He also shared insights into the latest and upcoming trends in using R in these sectors and tips for organizing successful hybrid meetups with minimal overhead.\nIn September 2022, Mario Annau talked to the R Consortium about the role of the local financial industry in the Robust Vienna R Community. Recently, the R Consortium reached out to Mario for a detailed discussion about the use of R in the finance and pharmaceutical industries in Vienna. Mario shared his insights regarding the latest and upcoming trends in using R in these sectors and tips for organizing successful hybrid meetups with minimal overhead.\nPlease share about your background and involvement with the RUGS group.\nI became interested in R during my university studies in computer science. I earned a bachelor’s degree in software engineering and a master’s in intelligent systems or computational intelligence. During my master’s studies, I began using R. I also found out that Kurt Hornik, was at a different university in Vienna and was also using R. Together with other R core developers, he created R with its package repository and many features. Although I am not a trained statistician, I became more involved in statistics and machine learning, which are closely related. I did my master’s thesis with Kurt Hornik.\nDuring my second thesis, I became increasingly involved with R, which led me to explore text mining and sentiment analysis with this language. This interest ultimately kick-started my career. I am proud to say that I am one of the few people who have truly benefited from using R in my professional life. Back then, using open source software in companies was uncommon, and many people preferred Matlab and other professional tools. People would often ask me who supported R and why it was free. However, I found that having this skill set was very beneficial.\nThe experience of using open source languages and technologies has been really helpful for me. Over the years, I have switched jobs and worked for different employers, but the knowledge I gained has always been useful in other settings and companies. Unlike bigger corporations, I never had to worry about buying licenses or running into budget issues. For example, Matlab is expensive, so it’s always a concern for some companies. But since I’ve had experience with open source technologies, I never had to deal with those issues.\nI learned about open source technologies during my university studies and discovered that they are free to use even in my professional career. This has been very helpful to me, and I am amazed at how far I have been able to go with it. Although R is not as widely used in the professional field as other languages, it has served me very well, and I am happy to be able to use it in my career. The Vienna R User Group allows me to bring it to the local R community.\nCan you share what the R community is like in Vienna?\nIt’s evident that the industry has started accepting open source, including R. I work primarily in the financial sector and pharma, which are industries where R is widely used. R is also a strong contender, alongside Python, in these fields.\nThe acceptance of using R in production environments is increasing, but some companies still view it as just a tool for creating graphs and nothing else. Despite this perception, I still use R a lot in production, and it works well. However, some wrong assumptions about using R in production are still present, which makes it challenging to deploy. Since R is a dynamic language and not compiled, some issues need to be addressed. Python also faces similar issues but is seen as easier to use. Although it is possible to use R in production, it depends on the department, as IT departments tend to be less accepting of R compared to the statistics or math departments.\nThere are always discussions regarding the best programming language to use in various industries. However, with the emergence of cloud technology and containerization, it is possible to package everything up into a nice container, making it work well. R is an industry-standard, and many risk departments in the financial industry use it to develop core models. Although people may complain and want to learn other languages like Python, R is still widely used.\nWhat industry are you currently in? How do you use R in your work?\nWe apply our expertise to various industries, including finance and pharmaceuticals. As external consultants, we assist clients in setting up proper procedures and creating useful dashboards and applications. We often work with existing R codes or other resources to improve their functionality and create helpful add-ons. Our focus is on maximizing existing knowledge and leveraging the existing code base. Our services often involve package creation, documentation, containerization, and dashboard framework development. We tailor our approach to suit the unique needs of each project.\nNowadays, we are developing more and more frameworks to set up departments in the industry with the right infrastructure. This includes developing R packages and connecting everything with the rest of the organization. Initially, we started by creating small models and calculations, but it gradually became more significant, and now we are mostly helping entire departments set themselves up in the right way and make the most of R and their people.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nThe trend of containerization has been around for some time now, where you package your app or REST API dashboard in a Docker container and deploy it in an environment such as the cloud. This trend is prevalent in both R and Python. As for upcoming trends, I am excited about the web assembly initiative, which makes it possible to run a Shiny app within a browser without a server. This initiative has great potential and can bring R to people who are unaware of its existence. It is exciting to see R bring data and statistics to life in various applications. I hope that this initiative can go further and reach more people.\nRegarding the deployment of our Shiny projects, it is always surprising to see how complicated it can be depending on the environment. This tool aims to make the deployment process easier and accessible to a broader audience. Currently, the loading times are still too long, but these issues can be optimized with some improvements.\nI have noticed another trend in certain industries, which is the increasing demand for regulatory compliance. For example, the FDA regulates the pharmaceutical industry, while finance has its own regulatory authorities. This trend encompasses ensuring that packages and codes are properly regulated and reviewed. I am seeing this trend in both the finance and pharmaceutical industries.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nWe have a GitHub page and a Meetup page, which is our setup. We tried to ensure that everything we present is also available, such as code and slides on GitHub, so that it’s easy for everyone to access. However, finding speakers and rooms is always a challenge. The good news is that finding rooms is getting easier than finding speakers. Some companies are always willing to host an hour-long meetup and have some online meetings. We are a group of smart people who like to talk about interesting things.\nThe most challenging aspect is locating speakers, particularly female speakers. I am pleased that initiatives like R Ladies provide a dedicated space for women in this field. Generally, finding speakers is a difficult task for us, and we rely heavily on referrals from friends and acquaintances. However, as a community, we always work to overcome this obstacle.\nIt’s important to always have a stream of topics and speakers available for events, but this can be difficult, especially when finding female speakers. Creating a welcoming and safe community where everyone feels comfortable sharing their knowledge is essential. Organizing these events is worth the effort, as you get to meet many like-minded people in your industry, and it can help you professionally. You’ll learn a lot and get to know people in your field, which is always an advantage. So, if you’re thinking of organizing meetups, just do it, and you’ll see how far it can take you.\nBefore COVID, our meetings were always in person. We tried recording them, but it didn’t work out. During COVID, we had to switch to online meetings only, and afterward, we started having hybrid meetings. I don’t find online meetups very satisfying because you miss out on the networking and socializing aspects. Going out to a bar or a pub and talking with people is an important part of the experience for me. That’s why I still prefer in-person meetups. However, thanks to COVID, things have changed, and I think we can now find more ways to combine the benefits of in-person and online meetings.\nYou are creating a lot of content that some people miss due to various reasons. There may be people who wanted to attend but couldn’t due to certain difficulties. To address this issue, we have now set up hybrid meetings, which require more equipment, like microphones and cameras. Most of the time, I have to carry this equipment. However, it makes sense to have this kind of content and share it with your community. Sometimes, speakers may not be happy about it, but it’s rare. Most of the time, it makes sense to do it hybrid.\nAs for the hybrid, I can say that recording can be difficult, and it rarely works out perfectly the first time around. However, I would recommend setting up a system that reduces your overhead for platforms like YouTube Live. Strive for minimal overhead to make your life easier. Don’t make the mistake we did once when Hadley Wickham was in town and we had to do a lot of editing and cutting because the recording wasn’t perfect. Instead, aim for a setup that works seamlessly and consider doing live streams instead.\nThe most practical way to share content with YouTube is to stream it live. This automatically uploads the content online, eliminating the need for further actions. As a result, when users visit the platform, the content is readily available for viewing.\nI have realized that delaying uploading our content to perform tasks such as editing and rearrangement is a time-consuming process that‌ does not offer significant benefits. Therefore, we are working towards improving our setup by acquiring high-quality microphones and mobile cameras to make the process more efficient and provide our viewers with a seamless experience.\nI am often amazed by the gratitude expressed by individuals around the world who get the opportunity to participate. Without the necessary infrastructure, achieving this would be impossible. However, some members of my community believe that it requires an excessive amount of work.\nIn light of the current global situation, people are less likely to travel or move to different cities for work or other purposes. Therefore, hybrid events are the most suitable way to improve accessibility and encourage community participation. Event organizers should consider using hybrid formats to provide a more inclusive and efficient experience for all participants." + "text": "The Dengue Data Hub, an ambitious initiative funded by the R Consortium ISC, transforms how researchers access and utilize dengue-related data. At its core, the Dengue Data Hub aims to provide a centralized repository for dengue incidence, mortality, and risk-related data, streamlining the research process and empowering scientific inquiry into this global health issue. The platform offers easy access through the denguedatahub R package, a Shiny app, and an informative website, making data analysis more efficient and accessible.\nPlease note: denguedatahub version 2.1.1 was published on CRAN on Sep 22, 2024.\nDr. Thiyanga Talagala, a Senior Lecturer at the University of Sri Jayewardenepura in Sri Lanka, spearheads this initiative. With a PhD from Monash University, where she honed her skills in R programming and data science, Dr. Talagala is deeply passionate about leveraging her expertise to address Sri Lanka’s public health challenges, particularly dengue. Together with her sister, Dr. Priyanga Talagala, she co-founded the R-Ladies Colombo group and has been instrumental in bringing innovative solutions to the scientific community. Dr. Talagala’s commitment to enhancing dengue research through accessible data resources is central to her ongoing work, making the Dengue Data Hub a vital tool for researchers worldwide.\nTell us about your background and how it connects to the Dengue Data Hub project\nCurrently, I am working as a Senior Lecturer, Department of Statistics, Faculty of Applied Sciences, University of Sri Jayewardenepura, Sri Lanka. I earned my PhD from Monash University, Australia. During my time at Monash University in Australia, I was part of the NUMBAT research group, where I developed a deep interest in the R programming language and discovered its incredible potential for data analysis and research. I also had the opportunity to meet and collaborate with leading experts in the field, which further fueled my passion for R and data science. I also got to know about the R Ladies community, and I attended events organized by R-Ladies Melbourne.\nOnce I returned to Sri Lanka after completing my PhD, I felt a strong desire to contribute to my country using the knowledge I had gained. I, along with my Sister, Dr Priyanga Dilini Talagala (we both did our PhDs together at Monash University), established the R Ladies Colombo meetup group.\nDengue is a major public health issue in Sri Lanka. As a data scientist, I can contribute to its mitigation by establishing a centralized repository for dengue data for data analysis and modeling, which empowers dengue research. This project was funded by R Consortium ISC 2022 - 1 Grant and I have been working on it since 2022.\nWhat is the Dengue Data Hub?\nThe Dengue Data Hub is a centralized repository that provides access to a variety of data sets related to dengue incidence and other relevant factors. This includes data on dengue deaths, reported cases, indigenous cases, local cases, dengue serotypes, breeding sites, and country-wise levels of risk. I have data related to annual dengue incidence for 195 countries around the world.\nWhy is this project important for the research community?\nDengue researchers often spend their valuable time searching for datasets, web scraping and cleaning data. The publication of data in a centralized repository helps to prevent duplicate efforts. The dengue data hub enables the community to focus on analysis and modeling rather than data collection and cleaning. Additionally, it enhances research sustainability by allowing researchers to utilize data for their studies while preserving it for future researchers.\nHow do researchers use the Dengue Data Hub?\nThere are three straightforward ways for anyone to participate. Use the denguedatahub R software package, use the Dengue Data Hub Shiny app (for non-programmers), or use our website which provides tutorials and examples.\nThe denguedatahub R package allows researchers to download dengue-related data easily. For Sri Lanka, it includes web scraping functions that directly retrieve weekly epidemiological reports published by the Epidemiology Unit, Ministry of Health, Sri Lanka. This functionality also cleans the data into a tidy format. Additionally, the package offers various data manipulation functions tailored for dengue data visualization and modeling. You can find the package on GitHub at https://github.com/thiyangt/denguedatahub.\nThe Shiny app provides an interface for non-programmers to access dengue data. It is available at: https://denguedatahub.shinyapps.io/denguedatahub/\nThis website is the home for the projects. It provides tutorials and examples. The site was developed using Quarto.\nWhat impact do you hope the Dengue Data Hub will have?\nMy hope is that the Dengue Data Hub will become a go-to resource for dengue researchers globally. I believe the hub will accelerate dengue research and discoveries which will help in developing effective strategies to combat dengue. The dengue data hub also serves as a\nteaching tool for data science and statistics, as it includes comprehensive data sets.\nDo you have any final thoughts or messages you’d like to share with the research community?\nI invite dengue researchers worldwide to collaborate on this project. I do not have access to clinical trial data, so contributions in that area would be especially valuable. We are looking to expand the datasets available, as comprehensive data sharing is essential for advancing our collective understanding of dengue epidemiology. Additionally, we welcome contributions of data, analytical tools, and insights that can help strengthen the hub’s capacity to serve as a central resource for researchers globally.\nYou can learn more about how to collaborate here. We can build a stronger network to enhance dengue research and response efforts worldwide." }, { - "objectID": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html#how-do-i-join", - "href": "posts/navigating-r-impact-in-vienna-insights-from-the-finance-and-pharmaceutical-sectors/index.html#how-do-i-join", - "title": "Navigating R’s Impact in Vienna: Insights from the Finance and Pharmaceutical Sectors", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html#about-isc-funded-projects", + "href": "posts/empowering-dengue-research-through-the-dengue-data-hub/index.html#about-isc-funded-projects", + "title": "Empowering Dengue Research Through the Dengue Data Hub: R Consortium Funded Initiative", + "section": "About ISC Funded Projects", + "text": "About ISC Funded Projects\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nhttps://r-consortium.org/all-projects/callforproposals.html" }, { - "objectID": "posts/enhancing-clinical-trial-data-sharing-with-r-consortiums-r-submissions-working-group/index.html", - "href": "posts/enhancing-clinical-trial-data-sharing-with-r-consortiums-r-submissions-working-group/index.html", - "title": "Enhancing Clinical Trial Data Sharing with R Consortium’s R Submissions Working Group", + "objectID": "posts/empowering-r-enthusiasts-satrdays-london-2024-unveiled/index.html", + "href": "posts/empowering-r-enthusiasts-satrdays-london-2024-unveiled/index.html", + "title": "Empowering R Enthusiasts: SatRDays London 2024 Unveiled", "section": "", - "text": "The R Consortium’s working group R Submissions Working Group is spearheading an innovative approach to clinical trial data sharing, according to a feature in Nature. This initiative, led by Eric Nantz, a statistician at Eli Lilly in Indianapolis, Indiana, involves a pilot project with the US Food and Drug Administration (FDA). Sharing clinical trial data traditionally requires each scientist to install custom computational dashboards, a cumbersome and error-prone process.\nNantz elaborates on the benefits of using webR and WebAssembly in this context: “Using WebAssembly, [it] will minimize, from the reviewer’s perspective, many of the steps that they had to take to get the application running on their machines.” This technology not only simplifies the data sharing process but also has the potential to accelerate drug approval timelines and enhance collaborative research across various fields.\nFor more details, read the full article on Nature’s website:Read the full article here (Paid subscription required).\nTo further explore Eric Nantz’s insights on using R and Shiny in regulatory submissions, you can also check out the R/Adoption Series: R and Shiny in Regulatory Submissions with Eric Nantz." + "text": "SatRDays London 2024 is set to ignite the data science community with a vibrant lineup of speakers and a rich array of topics ranging from survival analysis to geospatial data. This inclusive event, designed for R enthusiasts at all levels, emphasizes networking and collaboration amidst the backdrop of King’s College London’s iconic Bush House. Keynote speakers like Andrie de Vries, Nicola Rennie, and Matt Thomas bring unparalleled expertise, offering attendees a unique opportunity to deepen their knowledge and connect with peers. As a hub of innovation and learning, SatRDays London promises to be a cornerstone event for anyone passionate about R and its applications in the real world.\n\nRegister Now!\nHow does this year’s satRDays in London compare to last year’s event? What’s new and different?\nAfter a successful SatRdays London in 2023, we are keeping the format the same, but with a whole new lineup of speakers! This year we’re excited to welcome:\n\nAndrie de Vrie – Posit\nHannah Frick – Posit\nCharlie Gao – Hibiki AI Limited\nMichael Hogers – NPL Markets Ltd\nMatthew Lam & Matthew Law – Mott MacDonald\nMyles Mitchell – Jumping Rivers\nNicola Rennie – Lancaster University\nMatt Thomas – British Red Cross\n\nTalk topics for the day include survival analysis, geospatial data, styling PDFs with Quarto and using R to teach R, as well as a range of other exciting themes! The talks can reach a varied audience from aspiring data scientists right to the experienced audiences.\nTake a look at the full list on the conference website for more information.\nWho should attend? And what types of networking and collaboration opportunities should attendees expect?\nAnyone and everyone with an interest in R! The SatRdays conferences are designed to be low cost, to allow as many to attend as possible, and they’re on a SatRday, so you don’t have to worry about getting time off work if your job isn’t necessarily R focussed.\nNetworking is the main focus of the event. We have multiple coffee breaks to give attendees the opportunity to interact with fellow R enthusiasts. If you’re brand new to this kind of event, and are not sure where to start, don’t worry! Find one of the attendees from JR, and we’ll be happy to help you make introductions!\nCan you share some insights into the keynote speakers, their areas of expertise, and how they will contribute to the overall experience at SatRDays?\nAt this year’s event, we have talks from three invited speakers – Andrie de Vries of Posit, Nicola Rennie from the University of Lancaster and Matt Thomas of the British Red Cross.\nAndrie is Director of Product Strategy at Posit (formerly RStudio) where he works on the Posit commercial products. He started using R in 2009 for market research statistics, and later joined Revolution Analytics and then Microsoft, where he helped customers implement advanced analytics and machine learning workflows.\nNicola is a lecturer in health data science based at the Centre for Health Informatics, Computing, and Statistics at Lancaster University. She is particularly interested in creating interactive, reproducible teaching materials and communicating data through effective visualisation. Nicola also collaborates with the NHS on analytical and software engineering projects, maintains several R packages, and organises R-Ladies Lancaster.\nMatt is Head of Strategic Insight & Foresight at the British Red Cross. His team conducts research and analysis to understand where, how and who might be vulnerable to various emergencies and crises within the UK.\nCould you elaborate on the types of sessions and workshops available and how they cater to different interests and skill levels within the R community?\nThe day will consist of eight 25-ish minute talks, plus Q&A, from a variety of speakers across various sectors.\nThe talks are on a wide range of topics. For example, last year we had speakers talking about everything from using R for mapping air quality, to EDI and sustainability in the R project, and why R is good for data journalism. If you want to take a look at what you can expect, we have a playlist of last year’s talk recordings available on our YouTube channel.\nWith the event being hosted at King’s College London, how does the venue enhance the experience for attendees, both in terms of facilities and location?\nWe’re very excited to be partnering with CUSP London again this year, who provide the amazing Bush House venue at King’s College London. The venue is a beautiful listed building, right in the heart of London, only a few minutes walk from Covent Garden.\nBeing in the center of London means easy access to multiple public transport links, both for national and international attendees!\nThe venue facilities and supporting technology provides a great space for sharing insights and networking.\n\n\nDon’t miss out, register today!" }, { - "objectID": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html", - "href": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html", - "title": "Improving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade", + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html", + "title": "The U.S. Federal Reserve quarterly model in R", "section": "", - "text": "The R Consortium recently connected with Kylie Bemis, assistant teaching professor at the Khoury College of Computer Sciences at Northeastern University. She has a keen interest in statistical computing frameworks and techniques for analyzing intricate data, particularly focusing on datasets with complex correlation patterns or those that amalgamate data from various origins.\nKylie created matter, an R package that offers adaptable data structures suitable for in-memory computing on both dense and sparse arrays, incorporating multiple features tailored for processing nonuniform signals, including mass spectra and various other types of spectral data. Recently, Kylie upgraded matter to version 2.4. Since our May 2023 discussion, Kylie has enhanced its signal processing capabilities, focusing on analytical tools like principal component analysis and dimension reduction algorithms, which are crucial for imaging and spectral data. A grant from the R Consortium supports this project.\nWe talked with you about matter in May 2023. You were providing support for matter and looking to improve the handling of larger data sets and sparse non-uniform signals. matter has been updated to version 2.4. What’s new?\nLast time we spoke, I had already rewritten most of the matter infrastructure in C++ for better maintainability. Since then, my focus has been on enhancing our signal processing capabilities. This summer, I’ve been adding essential signal processing functions and basic analytical tools, which are particularly useful in fields dealing with spectra or various types of signals.\nI’ve incorporated fundamental techniques like principal component analysis, non-negative matrix factorization, and partial least squares. I’ve also added several dimension reduction algorithms and a range of signal processing tools for both 1D and 2D signals. This includes smoothing algorithms for images and 1D signals and warping tools applicable to both.\nThese enhancements are crucial for working with imaging and spectral data and include features like distance calculation and nearest neighbor search.\nMy aim has been to augment matter with robust signal processing tools, particularly for sparse and non-uniform signals. This is inspired by my experience in augmented reality (AR) and my desire to integrate tools similar to MATLAB’s Signal Processing Toolbox or SciPy in Python. As someone primarily analyzing mass spectrometry imaging data, I found these tools initially in my Cardinal package. I wanted to transfer them to a more appropriate platform, not specific to mass imaging, and reduce Cardinal’s reliance on compiled native code for easier version updates.\nAdditionally, I’ve been building a more robust testing infrastructure for these tools and documenting them thoroughly, including citations for the algorithms I used for key picking and smoothing techniques. This documentation details the implementation of various algorithms, such as guided filtering and nonlinear diffusion smoothing, citing the sources of these algorithms.\nBy providing support for non-uniform signal data, matter provides a back end to mass spectrometry imaging data. But working with large files is applicable in a lot of domains. What are some examples?\nI deal with large files and data sets across various fields. Matter can be particularly impactful in areas dealing with signal, spectral, or imaging data. One field that comes to mind is remote sensing, where the imaging tools I’ve incorporated would be highly beneficial. That’s one key application area.\nAnother field is biomedical imaging, especially MRI data. For instance, a data format we often use for mass spectrometry imaging was originally developed for MRI – it’s called Analyze, and there’s a more recent variant known as NIfTI. This format is also supported in Cardinal for mass spec imaging data, but it’s primarily used in MRI and fMRI data analysis. While matter doesn’t directly offer plug-and-play functionality for MRI data, with some modifications, it could certainly be adapted for importing and processing MRI data stored in these formats.\nWe don’t have a specific function to read NIfTI files directly, but the structure of these files is quite similar to the mass imaging files we commonly work with. They consist of a binary file organized in a particular format, with a header that functions like a C or C++ struct, indicating where different image slices are stored. Understanding and interpreting this header, which is well-documented elsewhere, is key.\nSo, with some effort to read and attach the header file correctly, it’s entirely feasible to build a function for reading and importing MRI data. We’ve already done something similar with the Analyze format. Someone could definitely examine our approach and develop a method to handle MRI data effectively.\nPreviously, you indicated you wanted to improve R data frames and string support. You have a prototype data frame in the package already? What’s the schedule for improvements?\nI’m currently evaluating how far we’ll expand certain features in our project. One of these features is supporting strings, which is already implemented. Regarding data frames, I believe there might be better solutions out there, but it’s quite simple to integrate our data with them. For instance, taking a vector or an array, whether a matter matrix or a matter vector, and inserting it into a data frame column works well, particularly with Bioconductor data frames.\nI’m not entirely convinced that developing standalone, specialized data frame support in matter is necessary. It seems that other platforms, especially those like Bioconductor, are already making significant advancements in this area. For now, it seems sufficient that users can easily incorporate a matter vector or array into a data frame column. I’m hesitant to duplicate efforts or create overlapping functionalities with what’s already being done in this field.\nWhat’s the best way for someone to try matter? How should someone get started?\nLike any Bioconductor package, we offer a vignette on the Bioconductor website. This vignette provides a basic guide on how to start using our package, including creating matrices and arrays. It shows how these can serve as building blocks to construct larger matrices, arrays, and vectors. This is a straightforward way for users to begin.\nRegarding the applicability of our package, it really depends on the specific data needs of the user. For instance, our package provides out-of-memory matrices and arrays. If that’s the primary requirement, then our package is certainly suitable. However, there are other packages, both in Bioconductor, like HDF5 array support, and on CRAN, such as big memory and FF, that also offer similar functionalities.\nThe real advantage of our package becomes apparent when dealing with specific data types. If you’re working with data formats like MRI, where you have a binary file and a clear understanding of its format, our package can be very helpful. It simplifies attaching different parts of the file to an R data structure.\nMoreover, if your work involves signal data, particularly non-uniform signals like those in mass spectrometry or imaging data, our package becomes even more beneficial. Over the summer, I’ve added extensive support for preprocessing, dimension reduction, and other processes that are crucial for handling these types of data. So, in these scenarios, our package can be a valuable tool.\nAnything else you would like to share about matter 2.0?\nI’ve spent much of the summer working on improvements to the matter package, and it’s now in a good place, particularly regarding signal processing capabilities. These enhancements are largely aligned with the needs of mass spectrometry, an area I closely focus on. As new requirements emerge in mass spectrometry, I’ll look to add relevant features to matter, particularly in signal and image processing.\nHowever, my current priority is updating the Cardinal package to support all these recent changes in matter. Ensuring that Cardinal is fully compatible with the new functionalities in matter is my next major goal, and I’m eager to get started on this as soon as possible." + "text": "Guest Post contributed by Andrea Luciani, Bank of Italy, Directorate General for Economics, Statistics and Research, maintainer of the bimets package (Time Series and Econometric Modeling) in CRAN\nThe US Federal Reserve’s econometric model for the US economy (i.e., FRB/US) is publicly available at federalreserve.gov. The website states, “FRB/US is a large-scale estimated general equilibrium model of the US economy that was developed at the Federal Reserve Board, where it has been in use since 1996 for forecasting, analysis of policy options, and research projects.”\nFRB/US is a quarterly model with hundreds of equations and variables. The model definition and time series data are available for download on the Federal Reserve website, as is the source code, which allows users to perform several econometric exercises. However, the Federal Reserve publicly distributes source codes only for EViews™ and python.\nIn this post, we show how to load the FRB/US model, and perform in R the same econometric exercises provided by the Federal Reserve." }, { - "objectID": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html#how-do-i-join", - "href": "posts/improving-with-r-kylie-bemis-unveils-enhanced-signal-processing-with-matter-2-4-upgrade/index.html#how-do-i-join", - "title": "Improving with R: Kylie Bemis Unveils Enhanced Signal Processing with Matter 2.4 Upgrade", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#the-frbus-model", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#the-frbus-model", + "title": "The U.S. Federal Reserve quarterly model in R", + "section": "The FRB/US model", + "text": "The FRB/US model\nThe Federal Reserve website also states, “Compared with DSGE models, however, FRB/US applies optimization theory more flexibly, which permits its equations to better capture patterns in historical data and facilitates modeling the economy in greater detail… A distinctive feature of FRB/US is its ability to switch between alternative assumptions about how economic agents form expectations. Under the VAR-based option, expectations are derived from the average historical dynamics of the economy as manifested in the predictions of estimated VAR models. Under model-consistent (MC), agents are assumed to form accurate expectations of future outcomes as generated by simulations of FRB/US itself.”\nFRB/US is a quarterly model, and counts 284 equations and 365 variables (Feb. 2024 version). The XML model definition is available for download on the Federal Reserve website, and contains, for each endogenous variable, the following information: the variable name, the variable definition with a short description, the economic sector the variable belongs to, the related equation in both EViews™ and python format, coefficients and exogenous variables involved in the equation.\n64 endogenous variables are marked as stochastic and, during the stochastic simulation exercise, will be transformed by applying sequences of shocks as drawn randomly from their historical residuals.\n14 endogenous variables belong to the MCE group (i.e., Model-Consistent Expectations) and have an alternative equation that contains forward-looking references.\nFinally, at the end of the XML model definition, users can find additional information on economic sectors and exogenous variables involved in the model definition." }, { - "objectID": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html", - "href": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html", - "title": "The Evolution of Melbourne’s Business Analytics and R Business User Group", - "section": "", - "text": "Maria Prokofieva, organizer of the Business Analytics and R Business User Group, spoke to the R Consortium last year about the Adoption of R by the Actuaries Community in Melbourne. Recently, Maria updated the R Consortium on the group’s focus, which has shifted towards business consultancy. The group provides a platform for graduate students to gain valuable industry experience and mentorship through various projects. The group is committed to ethical data governance and inclusive community building and prioritizes these values in all its initiatives.\nPlease share about your background and your involvement in the R Community.\nMy name is Maria Prokofieva. I work as a Leading ML Engineer at Mitchell Institute at Victoria University. I lead a stack of projects that use data to inform strategy and policy development. I am also an academic at the university, conducting research and teaching courses on ML/AI and data analysis. Through my work, I have the privilege of collaborating with various organizations, governments, and scholars to assist them in utilizing data to make decisions that impact the lives of many. I love open source, and what we see today is amazing – the world is changing. I have been a member of R and Python communities for many years, and seeing us grow is great.\nHow has your R User Group been doing since the last time we spoke?\nThe group has been performing well. As we grow, we focus on projects and become extremely busy with them. We already have a small community of people involved in different projects who also work together and communicate regularly. Once a month, we organize meetups where we present master classes—we moved to an in-person space but occasionally do online events. Our group has two main directions: business consultancy and business knowledge exchange.\nWe have been quite successful in building connections with bigger and smaller businesses interested in doing more data analysis. Some smaller businesses have staff who can perform their duties, and this is where community members have been fantastic.\nThe backbone of my community comprises my current and former Master’s students, who completed a course on business analytics. They are passionate about using R in everyday tasks and already possess some knowledge and experience, which they are happy to share. They are also interested in building connections and networking for their future jobs. This platform provides a mutually beneficial relationship for new students who get valuable industry experience through unpaid volunteering. These students receive mentorship from business leaders and senior software developers who share their programming knowledge and their knowledge of business negotiations and working with clients through the entire project life cycle.\nWe have been successful in working with cloud services such as AWS. We are actively exploring ways to automate data science on AWS and have several upcoming workshops where we will dive deeper into this topic. One workshop will focus on AWS Bedrock, where we will introduce non-technical business community members to employing large language models to perform their tasks. Our workshops focus on addressing specific problem-solving tasks rather than just the environment. We look into the business problems and how they can be solved.\nIt’s better to identify a problem and brainstorm solutions than to focus on tools. It’s fascinating to see how the community comes up with unique solutions to the problem. This approach is exactly what we need today, where no single preferred tool exists. Even if we use R Studio, we can easily integrate Python and other environments to accomplish the task. The focus should always be on the task guiding the process rather than the tools themselves.\nAny recent project you have worked on using R?\nOur recent project is based on utilising AWS Bedrock and GPT-4 to implement a Retrieval-Augmented Generation (RAG) system for a business. This system streamlines customer email communication using internal documents and company FAQs to auto-generate tailored responses. With some components there, we successfully integrated data analysis in R with Python implementation. We also have a few projects using open source models and integrating transformer models from Hugging Face. R is a star for any data-wrangling tasks and data visualizations!\nWhat are your plans for the upcoming months?\nOne area of interest that we plan to focus on is the use of responsible AI and responsible practices. This is crucial not only for AI but also for any data management that we undertake. Responsible modeling and responsible data science are important concepts that need more attention. We have seen instances where people intentionally or accidentally manipulate statistics, and this needs to change. We must focus on being data governors and ensure our analysis is responsible. This includes managing the data and the application size, as well as ensuring continuity of work. Many packages are available, but maintaining and updating them is challenging. Our future work is to contribute to the community by ensuring the continuity of our packages so developers can rely on them.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nMany people talk about large language models, but the focus is often on their applicability and use cases. While many amazing models are available, businesses need to see how they can be practically applied to their needs. It’s not just about text generation – image generation and other areas are also important. When we share the use cases with the businesses, the possibilities they haven’t considered often amaze them. Therefore, there is a growing demand for case studies demonstrating these models’ practical applications rather than just tutorials.\nWe focus on the practical applications of tools. Our approach is to identify a problem and explore various solutions. I’m not interested in specific software packages but in finding efficient solutions to problems. If there’s a new tool that can help me solve a problem more effectively, I’m open to learning about it and sharing my experience with others.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nThe most important technique is interaction, networking, and keeping the connection alive among the group members. This is especially crucial when you have a larger proportion of new users in the group. It’s important to ensure that once they learn the skills, they understand that we are all busy and have business obligations to attend to. Therefore, it’s necessary to make sure that we keep the group relevant to all members, without getting carried away by our busy lives.\nThis is more about sitting together and engaging in problem-solving exercises, such as preparing for AWS certification. The group can help with other tasks, too, creating additional value beyond just learning. This is where the benefits of membership come in. Members are also motivated to give back to the community, as they can use their skills in real life, not just for learning purposes.\nFor instance, we have an AWS data practitioner interested in learning R. However, this is an opportunity for that person to share their expertise and contribute to the group. Similarly, we have a cybersecurity professional who is also interested in learning R. But this is an opportunity for them to present a use case on how machine learning can automate some of their tasks. They are also willing to share their knowledge, which may not have been considered. Therefore, it’s important to create a diverse experience for all members and engage with them in all possible ways. While it can be difficult to involve every group member, it’s crucial to understand their general interests and what’s important for them and focus on their professional development.\nTake a moment to analyze where your members come from and their future plans and steps. Discuss their next career moves. It will be beneficial to provide networking opportunities where members can get referrals for job searches and advice for their next career move. These opportunities are quite important. Therefore, promotions should always be the end goal. You cannot become complacent or content with where you are because life is about growth and evolution." + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#moving-towards-r", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#moving-towards-r", + "title": "The U.S. Federal Reserve quarterly model in R", + "section": "Moving towards R", + "text": "Moving towards R\nFRB/US model definition is available to R users in the FRB__MODEL dataset of the bimets package (bimets ver. 4.0.2, a software framework for time series analysis and econometric modeling):\n\n#load bimets\nlibrary(bimets)\n\n\n#load FRB/US MDL definition\ndata(FRB__MODEL)\n\n#print first 4 equations in model definition\ncat(substring(FRB__MODEL,1,1615))\n\nMODEL\n\n$DOWNLOADED FROM federalreserve.gov AND CONVERTED TO BIMETS MDL IN Feb, 2024\n\n$FRB/US is a large-scale estimated general equilibrium model of the U.S. economy \n$that was developed at the Federal Reserve Board, where it has been in use since 1996 \n$for forecasting, analysis of policy options, and research projects. \n\n$--------------------------------------------------------------------------\n\n$ ENDOGENOUS SECTION\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for both thresholds\n$DMPTMAX equals one when either the unemployment threshold or\n$the inflation threshold is breached.\nIDENTITY> dmptmax\nIF> dmptlur>=dmptpi\nEQ> dmptmax=\ndmptlur\nIDENTITY> dmptmax\nIF> dmptlur<dmptpi\nEQ> dmptmax=\ndmptpi\n\n$-----------------------------------------------\n$Federal funds rate, first diff\nIDENTITY> delrff\nEQ> delrff=\nTSDELTA(rff)\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for unemployment threshold\n$DMPTLUR equals zero when the unemployment rate is above its\n$threshold (LURTRSH) one when it is below. A logistic function\n$smoothes the transition, improving solution convergence properties.\nIDENTITY> dmptlur\nEQ> dmptlur=\n1/(1+EXP(25*(lur-lurtrsh)))\n\n$-----------------------------------------------\n$Financial Sector\n$Monetary policy indicator for inflation threshold\n$DMPTPI equals zero when expected inflation is below its threshold\n$and one when it is above. A logistic function smoothes the\n$transition, improving solution convergence properties.\nIDENTITY> dmptpi\nEQ> dmptpi=\n1/(1+EXP(-25*(zpic58-pitrsh)))" }, { - "objectID": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html#how-do-i-join", - "href": "posts/the-evolution-of-melbournes-business-analytics-and-r-business-user-group/index.html#how-do-i-join", - "title": "The Evolution of Melbourne’s Business Analytics and R Business User Group", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#dynamic-simulation-in-a-monetary-policy-shock", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#dynamic-simulation-in-a-monetary-policy-shock", + "title": "The U.S. Federal Reserve quarterly model in R", + "section": "Dynamic simulation in a monetary policy shock", + "text": "Dynamic simulation in a monetary policy shock\nThe first econometric exercise proposed by the Federal Reserve is a dynamic simulation of the FRB/US model under a monetary policy shock. The simulation is operated from 2040-Q1 to 2045-Q4, after the rffintay time series, defined as “Value of eff. federal funds rate given by the inertial Taylor rule”, is shocked by 100 base points in 2040-Q1.\n\n# Load data\ndata(LONGBASE)\n\n# Load model\ndata(FRB__MODEL)\nmodel <- LOAD_MODEL(modelText = FRB__MODEL)\n\nAnalyzing behaviorals...\nAnalyzing identities...\nOptimizing...\nLoaded model \"FRB__MODEL\":\n 0 behaviorals\n 284 identities\n 0 coefficients\n...LOAD MODEL OK\n\n# Load data into model\nmodel <- LOAD_MODEL_DATA(model, LONGBASE, quietly=TRUE)\n\n# Specify dates\nstart <- c(2040,1)\nend <- normalizeYP(start+c(0,23),4)\n\n# Standard configuration, use surplus ratio targeting\nmodel$modelData$dfpdbt[[start,end]] <- 0\nmodel$modelData$dfpsrp[[start,end]] <- 1\n\n# Solve to baseline with adds\nmodel <- SIMULATE(model,\n simType='RESCHECK',\n TSRANGE=c(start,end),\n ZeroErrorAC = TRUE,\n quietly=TRUE)\n\n# 100 bp monetary policy shock\ntrac <- model$ConstantAdjustmentRESCHECK\ntrac$rffintay[[start]] <- trac$rffintay[[start]]+1\n\n# Solve\nmodel <- SIMULATE(model,\n simAlgo = 'NEWTON',\n TSRANGE = c(start,end),\n ConstantAdjustment = trac,\n BackFill = 12,\n quietly=TRUE)\n\nR code produces the following charts:\n\nOn the other hand, the python code provided by the US Federal Reserve produces very similar results:" }, { - "objectID": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html", - "href": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html", - "title": "Unlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research", - "section": "", - "text": "The R Consortium recently interviewed Kristina Riemer, director of the CCT Data Science Team at the University of Arizona, and Eric Scott, Scientific Programmer and Educator in the CCT Data Science Team, the developers behind the volcalc package, to discuss the motivation and development of this innovative tool designed to automate the calculation of chemical compound volatilities. volcalc streamlines the process by allowing users to input a compound and quickly receive its volatility information, eliminating the need for time-consuming manual calculations. Initially created to assist Dr. Laura Meredith in managing a large database of volatile compounds, volcalc has since grown into a more versatile tool under Eric’s leadership, now supporting a wider range of researchers.\nKristina and Eric share insights into the challenges they faced, including managing dependencies, integrating with CRAN and Bioconductor, and refining complex molecular identification methods. They also discuss future enhancements, such as incorporating temperature-specific volatility calculations and expanding the package’s functionality to estimate other compound characteristics. This project was funded by the R Consortium.\nCould you share what motivated the development of the volcalc package and how it aligns with the broader goals of the R ecosystem, particularly in scientific computing?\nKristina: I was heavily involved in the initial development of volcalc, and later on, Eric took over the project. We developed volcalc because we began collaborating with Dr. Laura Meredith, who was compiling a database of volatile chemical compounds. At the time, she had around 300 compounds, and her students manually gathered details for each one by examining their representations and calculating various associated values. This process was tedious and prone to errors, so we thought there must be a more efficient and automated way to handle it.\nThat’s when we came up with the idea of creating a pipeline where someone could input a compound and quickly receive its volatility information, eliminating the need for all the manual labor. The purpose of volcalc was to transform the process from taking months to gather details for 300 compounds to obtaining information for thousands in a much shorter time.\nEric: volcalc was initially developed specifically for a project where the researchers were mainly interested in chemical compounds from the KEGG database (Kyoto Encyclopedia of Genes and Genomes). When I joined the team and learned about the project, I was thrilled because, as a chemical ecologist, I saw its potential. However, I also recognized a limitation: the tool only worked with the KEGG database. This was a drawback because many researchers, including food scientists and others who work with similar compounds, might not find their compounds in that specific database.\nThis realization inspired me to apply for the R Consortium grant. We saw a significant opportunity to expand volcalc, making it more flexible and applicable to a wider range of researchers. We also wanted to improve its integration within the R ecosystem by adding features like returning the file path of a molecule representation after downloading it, so it could be easily piped into subsequent steps. These enhancements aimed to make the tool more versatile and user-friendly for a broader audience.\nWhat were the most significant challenges you faced during the development of the initial version of volcalc, and how did you overcome them?\nKristina: One of the most challenging aspects of developing volcalc, which continues to be an issue, is managing dependencies. Specifically, we rely heavily on a command-line program to handle much of the processing. Early on, we struggled with how to enable users to run volcalc without needing to install this program on their own computers, as many of our users aren’t familiar with that kind of setup. I spent a lot of time trying to create a reproducible environment using Binder, but I was never able to get it fully working. Even today, there are still issues related to managing these dependencies, which Eric can elaborate on further.\nIt was incredibly important to have Eric on this project because I don’t have a strong background in chemistry. His ability to come in and figure out some of the intricate details that would have taken me much longer to grasp was a huge advantage. The more we can collaborate with domain experts, the better our results will be.\nEric: One thing that has helped with the dependency challenges is that we’ve started building volcalc on R-Universe, which means binaries are available there. While it’s not on CRAN yet, having these binaries on R-Universe makes installation a bit easier. However, we’ve faced some challenges with dependencies, particularly because two of them are from Bioconductor. We didn’t originally aim to develop this package for Bioconductor, which uses S4 objects and has different standards than CRAN. Our goal was to get it on CRAN, but our first submission was rejected because the license field for the Bioconductor package wasn’t formatted to CRAN’s liking. These differences between Bioconductor and CRAN have created barriers, even though the authors of the Bioconductor package have been very responsive. Their package works fine on Bioconductor, but it doesn’t meet CRAN’s criteria, which has been a frustrating challenge.\nAnother major challenge in developing volcalc relates to the method we use for estimating volatility. This method involves counting the numbers of different functional groups on molecules—such as hydroxyl groups or sulfur atoms—and assigning coefficients to them. To do this programmatically, we use something called SMARTS, which is essentially like regular expressions but for molecular structures. Regular expressions for text are already challenging, but SMARTS is even more complex because it deals with three-dimensional molecules.\nBefore I joined the group, the first version of volcalc had most of these functional groups figured out, but not all. I spent a significant amount of time trying to develop SMARTS strings to match additional molecules. Moving forward, I hope that if we implement new versions, we can get help from the community to refine these SMARTS strings, as there are likely people out there who are more skilled at it than I am.\nThe original project proposal mentions expanding volcalc to work with any chemical compound with a known structure. What are the key technical challenges you anticipate in achieving this goal?\nEric: This task turned out to be less difficult than I initially expected, but let me explain. In the original version of volcalc, before we received the R Consortium funding, the main function started with a KEGG ID—an identifier specific to the KEGG database. The function would download a MOL file, which is a text representation of a molecule corresponding to that ID. It would then identify and count the functional groups in the molecule, and finally, calculate the volatility based on those counts.\nThe major change we needed to implement to make volcalc more versatile was to decouple these steps. In the current version of volcalc, the functionality to download a MOL file from KEGG is still available, but it’s now separate from the main function that calculates volatility. This means that the inputs for calculating volatility can now be any MOL file, not just ones from KEGG. The file can come from any database, be exported from other software, or even be downloaded manually. Additionally, the tool now supports SMILES, which is another, simpler text-based representation of molecules.\nThere are various ways to represent chemicals in text, including another format called InChI. The Bioconductor packages we use, ChemmineR and ChemmineOB, have the ability to translate from InChI and other types of chemical representations. However, that feature isn’t available on Windows. So, I decided to keep volcalc focused on SMILES and MOL files. I believe that chemists and other researchers should be able to obtain data in one of these two formats, or use another tool to translate their data into these formats. I didn’t want to overload volcalc with the responsibility of being a chemical representation translator, as that didn’t seem like its primary purpose.\nCan you walk us through the process of implementing the SIMPOL algorithm within the volcalcc package?\nKristina: The algorithm itself is fairly simple; it’s just basic math. You need to input some constants, the mass of the compound, and the counts of the functional groups we discussed earlier. Writing the code for this was straightforward and not particularly challenging.\nEric: Each functional group has a coefficient associated with it, which is multiplied by the number of times that group appears in the molecule. These values are then summed up, and the mass of the molecule is factored in as well. The challenging part wasn’t the algorithm itself, which is straightforward—just multiplying by coefficients and adding them up. The real difficulty was interpreting what the authors of the algorithm meant by each of the functional groups. Some were oddly specific, like how the hydroxyl group that is part of a nitrophenol group isn’t supposed to count toward the total number of hydroxyl groups. I spent a lot of time poring over the paper, particularly one table, to fully understand how they defined each group. That interpretation was the hardest part.\nWhat future functionalities or expansions do you see as crucial for volcalc, especially in the context of evolving research needs in chemoinformatics?\nEric: Right now, we’re working on allowing users to specify different temperatures. The paper that describes the SIMPOL.1 method includes equations for how the coefficients of each functional group change with temperature. These changes aren’t always linear, and the contributions of functional groups can shift in importance as the temperature varies. This is an important feature to include because the version of volcalc we currently have uses coefficients calculated at 20°C, based on a table from the original paper. To accommodate other temperatures, we need to integrate another table that provides equations for calculating these coefficients based on temperature, and that’s what we’re working on.\nAnother key feature we want to leave room for in the future is the ability to add other methods for estimating volatility. SIMPOL.1 is just one type of group contribution method, but there are other approaches described in various papers that use different functional groups, equations, and coefficients. The basic idea remains the same: count the functional groups in a molecule, apply an equation, and estimate volatility. We’re trying to structure the code in a way that makes it easy to incorporate additional methods later, even if we don’t add them right away. I think these are the most important features we’re focusing on right now.\nKristina: We’re focused on the features I mentioned in the near future, but looking further ahead, I could see volcalc expanding to estimate other characteristics of compounds beyond just volatility. While I’m not a chemistry expert or a chemical ecologist, I imagine that those interested in volatility might also be interested in other compound characteristics that currently lack automated tools for estimation. So, it’s possible the package could evolve to include those features.\nThat said, one of the things I appreciate about the R package ecosystem is that it allows for specialized tools. Since anyone can build what they need, we don’t end up with massive, overly complex packages that try to do everything and become difficult to maintain. It might be better to keep volcalc focused and leave room for separate packages to handle additional functionality. This way, the tools remain manageable and easier to maintain in the long run.\nHow has it been working with the R Consortium? Would you recommend applying for an ISC grant to other R developers?\nKristina: The application process was straightforward, and I found the grant format to be very practical. It was focused on milestones and product development, which is refreshing compared to many academic research grants that tend to avoid specific deliverables. I highly recommend considering this grant. I believe people often overlook smaller funding sources, but even small amounts can make a big impact on the work you’re doing.\nEric: The first time I applied for an R Consortium grant was as a grad student, and I strongly encourage trainees to apply as well. It was a great experience for me because I could do it independently—my advisor wasn’t involved as one of the authors, and it wasn’t a complex process like applying for an NSF grant. It was straightforward and really rewarding. The only tricky part was figuring out the payment process, but that’s something people can work out.\nI’ve noticed there seem to be fewer projects in recent years, and I don’t think it’s due to a lack of funding. It seems like fewer people are applying, which is why I especially encourage others to give it a shot. From what I’ve seen, there’s a very good chance of getting funded if you apply right now.\nPeople should be creative and think broadly about how their project can benefit the broader R community. This doesn’t mean you need to develop the next big thing like R-Universe or CRAN. It can be something smaller, like a package that other R users will find helpful. For example, with our project, volcalc, our main goal was to encourage chemists—who usually use point-and-click software—to start using R. That was enough of a contribution to the R community to get funded. So, I really encourage people to think creatively about what “benefiting the R community” can mean." + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#stochastic-simulation", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#stochastic-simulation", + "title": "The U.S. Federal Reserve quarterly model in R", + "section": "Stochastic simulation", + "text": "Stochastic simulation\nAnother econometric exercise proposed by the Federal Reserve is a stochastic simulation of the FRB/US model. The stochsim procedure in the pyfrbus python package (available on the Federal Reserve web site) performs a stochastic simulation by applying sequences of shocks to 64 endogneous variables of the model, as drawn randomly from historical residuals. In a similar way in R, the STOCHSIMULATE procedure allows users to shock the same endogenous variables with randomly sampled historical residuals.\nR code, omitted for brevity, produces the following charts:\n\nOn the other hand, the python code provided by the US Federal Reserve produces very similar results, despite the random numbers generator being different between R and python:" }, { - "objectID": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html#about-isc-funded-projects", - "href": "posts/unlocking-chemical-volatility-how-the-volcalc-r-package-is-streamlining-scientific-research/index.html#about-isc-funded-projects", - "title": "Unlocking Chemical Volatility: How the volcalc R Package is Streamlining Scientific Research", - "section": "About ISC Funded Projects", - "text": "About ISC Funded Projects\nA major goal of the R Consortium is to strengthen and improve the infrastructure supporting the R Ecosystem. We seek to accomplish this by funding projects that will improve both technical infrastructure and social infrastructure.\nLearn More!" + "objectID": "posts/us-federal-reserve-quarterly-model-in-r/index.html#section", + "href": "posts/us-federal-reserve-quarterly-model-in-r/index.html#section", + "title": "The U.S. Federal Reserve quarterly model in R", + "section": "________________", + "text": "________________\nAdditional exercises, e.g., rational expectations, endogenous targeting, etc., and computational details are available in the package vignette The U.S. Federal Reserve quarterly model in R with bimets" }, { - "objectID": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html", - "href": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html", - "title": "Cakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group", + "objectID": "posts/elevate-your-r-community-with-the-2024-rugs-grant-program/index.html", + "href": "posts/elevate-your-r-community-with-the-2024-rugs-grant-program/index.html", + "title": "Elevate Your R Community with the 2024 RUGS Grant Program", "section": "", - "text": "Rasmus Bååth, the organizer of the CopenhagenR UseR Group, recently spoke to the R Consortium about his experience in organizing the group. After joining the Copenhagen R User Group in 2013, he took the lead in reviving the group in 2023 after a period of inactivity. Under his guidance, the group now focuses on industry-related topics, personal projects, and emerging tools like Quarto. Rasmus is dedicated to fostering a vibrant local R community through in-person meetups that encourage learning and collaboration.\nThe CopenhagenR UseR Group is hosting an exciting “Two Tools for Report Generation in R” event on October 3, 2024. The event will feature two presentations on using Sweave and Quarto for report generation, followed by discussions and networking at PROSA, København, Denmark.\nPlease share your background and involvement with the RUGS group.\nI currently work as a Data Science Manager at Normative.io. I’ve used R on and off for about 15 or 16 years. It all started when I was doing my bachelor’s in academia and needed to plot a histogram. At that time, plotting a histogram in Excel wasn’t easy, so my supervisor suggested trying out R. I gave it a shot and got hooked. After that, I pursued a PhD in cognitive science, where I used R extensively for statistical analysis.\nI used R for a lot of graphing during my academic years. After academia, I became a data scientist in the industry, and R was my preferred tool. I work with R and Python, depending on the job’s requirements. In 2013, there were no R meetups in the south of Sweden where I live. I found out about an R meetup in Copenhagen and decided to attend. There, I met Kenneth Rose, the organizer, who was full of energy and charisma. It was a fun group, so I started attending regularly despite the commute from Sweden to Copenhagen. Kenneth was very active and enthusiastic in running the meetup group.\nAfter a couple of years, the group’s activity declined. A new organizer revived the group, but COVID hit, ending the meetups. The group had been around for ten years by 2023, and I felt it was a shame to let it die. I decided to restart it, and now we have a small but active group. We enjoy discussing industry-related topics and personal projects.\nCan you share what the local R community is like?\nIt is the Copenhagen meetup group located in Denmark. However, I can speak for Denmark and Sweden since I live in Sweden. R is widely used in academia and is considered the language of choice for statistics. Python is more prevalent in the industry due to the large number of programmers who are familiar with the language. In Denmark, the pharmaceutical industry is significant. R is still widely used there due to its close ties to academia and the specific requirements for reporting, statistics, and visualization, in which R excels.\nDo you guys host online or in-person events?\nDuring the COVID-19 pandemic, we tried some online events, but creating a sense of community online with so much content is challenging. I believe online events are great, and people should consider them. However, we also recognize the need for in-person events. For those unable to attend, there is plenty of valuable content online. We don’t have the setup to record events, but we would consider doing so if feasible.\nYou have a Meetup titled “Two tools for report generation in R.” Can you share more on the topic covered? Why this topic?\nOur next meetup will focus on automatic reporting in R. We’ll have two speakers: Dmytro Perepolkin and an anonymous speaker. The anonymous speaker will present on Sweave, an older tool used to generate reports in R, while Dmytro will present on Quarto, a more recent and popular tool for combining R code and text. This meetup will depart from the usual topics, focusing on automatic reporting rather than visualization.\nI’m looking forward to our upcoming event. It will be a history lesson and a great opportunity to learn about a useful minimalistic tool (Sweave). I’m also excited about Quarto and the potential for new developments. We could have a Quarto meetup every year to stay updated with the latest advancements. The meetup will feature different presentations, including introductions to new tools and discussions about projects and code. It will be a great way to learn and connect with others in the field.\nWhat are some of the popular R-related topics in the group?\nThe topics we typically cover are where R is at its strongest. We often discuss personal projects, and although I wonder if they receive a great response, I love them. Additionally, we frequently explore new tools and libraries, particularly those related to dashboarding, Shiny, and visualization. Presentations are highly technical, and I’ve noticed that our audience may not be accustomed to text-heavy or math-intensive presentations. Therefore, topics such as statistics and statistics packages might not receive as much attention despite my interest in them. Surprisingly, machine learning is not a common focus at our meetups, as most speakers are more inclined towards visualization, reporting, and statistics rather than machine learning.\nDo you recommend any techniques for planning for or during the event? (GitHub, Zoom, other.) Can these techniques be used to make your group more inclusive to people who cannot attend physical events in the future?\nThere are three key components needed to get started with organizing an event. First, you need people who are interested in attending your event. It can be challenging if you’re in a small town or a location where it’s difficult to attract attendees. Second, you need to secure speakers who are willing to participate. Lastly, finding a suitable venue is crucial. Having a reliable and cost-free location for your event is essential. We were fortunate to secure a free venue through a union for IT workers in Copenhagen, which aligns with our goal of offering free courses without being tied to a specific company.\nFinding speakers can be challenging, but constantly contacting and asking for volunteers is the best approach. To make it easier for potential speakers, consider organizing events where multiple speakers can do shorter presentations, which may be less intimidating than a full-hour presentation. However, attracting speakers and attendees remains the most difficult aspect of organizing events. Nevertheless, securing a dependable venue is a great starting point.\nAnd then there are some small things. Make sure to make nice announcements. They need a nice picture. They need friendly text so that people feel welcome. That’s the minimal thing. And the other thing is, if it’s allowed in the meetup space, bring some cakes or cookies and have some snacks. If people know there will be a little bit of snacks, they’re more likely to show up. So it’s a small thing, but I think that helps. This meetup is in Copenhagen, and I’m from Sweden. However, Denmark and Copenhagen have a special relationship with beer. I distinctly remember my first Copenhagen meetup when Kenneth Rose was the organizer. Back then, he brought a big case of beer cans to each meetup, and everyone was having a nice time. I don’t say you need a beer at your meetup, but bringing drinks and snacks is always nice." + "text": "The R Consortium is rolling out its 2024 R User Groups (RUGS) Grant Program, and it’s an opportunity you don’t want to miss. The program, which aims to foster vibrant R communities worldwide, is in full swing, and we are eagerly awaiting your application!\n\nApply here!\n\n\nWhy Apply and… For What?\nUser Group Grants: Boost engagement and initiate user-focused activities.\nConference Grants: Support for R-related events, either hosting or attending.\nSpecial Projects Grants: Kickstart innovative projects with the potential to impact the R community.\nWith 74 active groups and a thriving community of over 67,000 members, the RUGS network is a hub of innovation and knowledge sharing. Your participation could be the next milestone in this growth journey.\nExamples of some recent R Consortium sponsored RUGS activities:\n\nThe Cleveland R User Group’s Journey Through Pandemic Adaptations and Baseball Analytics\nR-Ladies Goiânia: Promoting Diversity and Inclusion in Local R Community\n\n\n\nKey Information\nApplication Deadline: September 30th, 2024. Don’t delay!\nEligibility: Open to initiatives aimed at community building, not software development (for that, see ISC Grant Program).\nBe part of shaping the future of R. Visit here for more details and to apply. Your contribution matters to the global R narrative. Apply now, and let’s grow together!\n\nFor details and to apply, visit here." }, { - "objectID": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html#how-do-i-join", - "href": "posts/cakes-code-and-community-reviving-the-copenhagenr-user-group/index.html#how-do-i-join", - "title": "Cakes, Code, and Community: Rasmus Bååth’s Secret to Reviving the CopenhagenR UseR Group", - "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn More!" + "objectID": "posts/earl-early-bird-tickets-are-now-available/index.html", + "href": "posts/earl-early-bird-tickets-are-now-available/index.html", + "title": "EARL Early Bird Tickets Are Now Available!", + "section": "", + "text": "Contributed by Abbie Brookes, Senior Data Analyst at Datacove\n\nDatacove is pleased to announce the availability of tickets for the upcoming EARL (Enterprise Applications of the R Language) conference.\nThe EARL conference is a cross-sector event that will be held at the Grand Hotel in Brighton. This venue promises to provide attendees with a blend of Victorian elegance and modern conference facilities over three days, from the 3rd to the 5th of September 2024. The conference schedule includes high-quality workshops on the first day (3rd September) and two days of presentations and talks (4th – 5th September). An evening networking event is planned for the 4th of September at the British Airways i360 venue, offering attendees the opportunity to connect with peers and speakers in a relaxed setting.\nWe are offering tickets at a reduced early bird rate. Additionally, we provide discounts for government employees, NHS staff, charity workers, academics, and those making bulk purchases. For more detailed information on ticket pricing and discounts, contact Abbie Brookes at abbie.brookes@datacove.co.uk.\nThe EARL conference draws attendees from across the globe and from a variety of sectors. Previous participants have included notable organizations such as The Dogs Trust, BBC, Microsoft, Swiss RE, Posit, Sainsburys, and Bupa.\nThis year’s keynote speakers include:\n\nProfessor Andy Field, known for his contributions to statistics education\n\nChristel Swift, a senior data scientist at the BBC\n\nHadley Wickham, a key figure in the R community and author of the Tidyverse\nIn addition to the main conference, a selection of pre-conference workshops will be available, offering in-depth training opportunities. For more information on the conference venue, schedule, and registration, please visitour website. We invite you to join us for what promises to be an informative and engaging event for the R and Python communities" }, { - "objectID": "posts/one-more-step-forward-the-r-consortium-submission-working-group-presentation-to-swissmedic-on-regulator-submission-using-r-and-shiny/index.html", - "href": "posts/one-more-step-forward-the-r-consortium-submission-working-group-presentation-to-swissmedic-on-regulator-submission-using-r-and-shiny/index.html", - "title": "One More Step Forward: The R Consortium Submission Working Group’s Presentation to Swissmedic on Regulatory Submission using R and Shiny", + "objectID": "posts/the-crucial-role-of-release-control-in-r-for-healthcare-organizations/index.html", + "href": "posts/the-crucial-role-of-release-control-in-r-for-healthcare-organizations/index.html", + "title": "The Crucial Role of Release Control in R for Healthcare Organizations", "section": "", - "text": "This post was authored by Gregory Chen, Biostatistics and Research Decision Sciences (BARDS), MSD, Switzerland, and Ning Leng, Product Development Data Sciences (PDD), F. Hoffmann-La Roche, USA\n\nOn January 30, 2024, the R Consortium Submission Working Group made a presentation to Swissmedic in Bern, Switzerland, with 10 attendees in person and 50 online. It started with a motivation as to why to consider using open source and specifically R for regulatory submissions. The group then proceeded to show cases of the pilot 1 and 2 submission to FDA.\nThe conclusion was an insightful discussion for about 20 minutes with the participants on the lessons learned, key factors to sort in line for broader adoption of R and Shiny for regulatory submissions, and what would be most added value for a regulatory shiny app, namely\n\nHow to deploy the submitted R package and Shiny App to guarantee the clinical outcomes can be smoothly reproduced on the regulatory side\nWhat would be the ultimate purpose of a regulatory shiny app, and what are value-added features? Should the app only focus on offering interactivities to facilitate the review of tables, figures, and listings in CSR, or should it also include designed features to enable exploratory, descriptive analysis (e.g., for subgroups) to certain degrees, which may greatly shorten back-and-forth inquiry between regulator and drug developer?\nValidation and version traceability of dependent open source R packages used in the submission package\nHow to leverage existing and emerging cross-industrial initiatives (e.g. R consortium) in the open source space to support and ease the potential technical issue during the adoption of R for submission\n\nAccompanying this post, the full presentation slide deck is made publicly available here, inviting further exploration and discussion.\nThe R Consortium’s presentation at Swissmedic represents a hopeful step toward more interactive, efficient, and transparent regulatory submissions. As the conversation between the R Consortium and regulatory bodies continues, our future collection of pilot projects hopefully will offer richer examples and templates to our growing R community within the pharmaceutical sector, spanning both regulatory and drug developer sides.\nTo find out more about the R Consortium Submission Working Group, please see: https://rconsortium.github.io/submissions-wg/" + "text": "Guest blog contributed by Ning Leng, People and Product Leader, Roche-Genentech; Eric Nantz, Director, Eli Lilly and Company; Ben Straub, Principal Programmer, GSK; Sam Parmar, Statistical Data Scientist, Pfizer\nSupporting the science of drug development requires computational tools with careful implementations of core statistical functions and data structures. The R programming language, a general purpose language developed by statisticians that grows dynamically through the contributions of a worldwide community of developers, is a common choice for serious statistical work. However, managing new versions of the core R language and the hundreds of specialized libraries (called packages in R) necessary to support multiple development groups in a way that ensures the consistency, reproducibility, and reliability of results poses many practical challenges\nThe FDA, for example, requires that the software and tools supporting a clinical trial submission are capable of producing reproducible results for an extended period of time. This means submitting code based on a version of R that is sufficiently tested and stable yet new enough to support the critical R packages over the required FDA time horizon.\nSo, how is the R environment release managed across different healthcare organizations? We interviewed individuals from different pharma companies to learn their internal approaches to keep their R environment up-to-date and secure.\n\nRoche’s Scientific Computing Environment is container based, with clinical reporting done from managed qualified images being released twice per year – roughly timed to capture the last update to an R major version (April release) and a 6 month later update (September release). For each image, R packages undergo a mostly automated risk assessment to document package quality. Automated indicators of package quality include test coverage, thoroughness of documentation, test coverage of exported objects (using covtracer), and may be supplemented with package adoption measured using download counts, author reputation or other peripheral knowledge of the package’s history. Prior to internal publication, a representative sample of reverse dependencies are re-evaluated to safeguard against breaking changes. If the package meets our quality criteria it is published to a continuously updated repository of validated packages corresponding to the image’s R minor version (e.g. x.x). This allows flexibility for teams to roll forward to newer releases of packages within a managed release by moving their renv snapshot to a later date, easing the transition between bi-annual image releases. A generalized version of Roche’s automated process has been open sourced as ’theValidator’, and more details on the Roche process was shared within the R Validation case studies series.\nEli Lilly currently updates its qualified R environment only after a new major release of R is available and the corresponding release of Bioconductor (utilizing that version of R) is also available. In a new release, all packages currently installed from the CRAN and Bioconductor repositories are refreshed to their latest versions at the time of the release. Once the new R version is deployed, all packages are frozen for that particular release to ensure stability and reproducibility. Lilly maintains multiple R versions for backward compatibility. Only packages available on CRAN or Bioconductor are permitted for installation in the central package library. Lilly uses a hybrid approach of automation and risk-based assessment when a new package is requested for installation. In the event that a new version of a package is necessary for a project (such as a new Shiny application), the users are encouraged to leverage the renv package created by Posit to create a project-based environment which will not impact the central package library. As technology evolves and the R language becomes more prominent in clinical data analysis, Lilly continues to assess the current and future possibilities of a robust clinical computing environment primed for innovation while adhering to the foundational principles of reproducibility and transparency.\nGSK releases “frozen R environments” for clinical reporting work on a 6-12 month cycle. The choice of R version is the latest stable release with at least one patch release of R, e.g. 4.3.1 rather than 4.3.0. As R itself is stable with decades of use, we prefer to focus on package assessment for building of our “frozen R environments.” Packages for this environment can be from external sources (CRAN, Bioconductor) or internally built at GSK, regardless of origin we assess the same way. We pay close attention to author qualification and institutional backing, types and breadth of testing, documentation and examples, and the practice of software development life cycle practices. Once a package is approved in this process it will be included in the frozen environment. Packages change over time, if substantial changes are implemented in the packages, then we re-assess with a focus on those changes for allowing up-versioning of the package in the frozen environment. These frozen environments ensure that clinical reporting can be easily reproduced if needed as all packages versions and the version of R used during the analysis are contained in the frozen environment.\nPfizer releases one new R version every year. We typically target R-x.y.1 releases to pick up patches – so we might consider this a “stable” release. The process of testing, documenting, and deploying R into validated containers is performed every 6 months, with a new release of R once per year, e.g. R-4.3.1, and an update to package set and package versions 6 months later (for the same R version). We take a snapshot date of CRAN to form the basis of our package set for the container build. We try to balance competing priorities of getting latest versions of packages and newest package releases, while maintaining a snapshot and version-controlled release to ensure reproducibility and stability.\n\nHere is what we have: four companies and four somewhat complex bespoke solutions. It seems likely that if we interviewed a hundred representatives from a hundred different companies we would get at least a hundred different solutions. It is also not difficult to imagine that multiple protocols for managing R and package versions imposed a fairly complex project management solution on the FDA as it simultaneously deals with submissions from multiple sponsors.\nIn the R Consortium’s R Submissions Work Group meeting we have been discussing whether there might be a simple solution for at least dealing with the R versioning problem that might serve as a de facto standard for the industry. One suggestion that has gained some traction is that sponsors use the previous minor and latest patched R version for a submission. For example, if R version 4.4.0 is currently available then it is suggested that a sponsor uses the latest patch version (4.3.z). If R version 4.5.0 becomes available, then it is suggested that a sponsor uses the latest patch version (4.4.z). This ensures that the minor version is stable and most likely available to all stakeholders. Of course, if a version change eliminates a security problem, that might be preferred. (Note that R versions are organized R x.y.z where, x is the major version, y is the minor version, and z is the patch version.)\nWe would love to hear what you think. Please, go to Issue number 117 on the GitHub repository of our working group and leave a comment." }, { - "objectID": "posts/announcing-health-technology-assessment-HTA-working-group/index.html", - "href": "posts/announcing-health-technology-assessment-HTA-working-group/index.html", - "title": "Announcing the Health Technology Assessment (HTA) Working Group", + "objectID": "posts/aligning-belief-and-profession-using-r-in-protecting-the-penobscot-nation-traditional-lifeways-r-consortium/index.html", + "href": "posts/aligning-belief-and-profession-using-r-in-protecting-the-penobscot-nation-traditional-lifeways-r-consortium/index.html", + "title": "Aligning Beliefs and Profession: Using R in Protecting the Penobscot Nation’s Traditional Lifeways", "section": "", - "text": "The R Consortium is pleased to announce a new Working Group (WG) focused on Health Technology Assessment (HTA). The HTA WG has a mission of promoting the use of R in all aspects of HTA analytics, including both clinical assessment and economic evaluation. It aims to build on the success of other R Consortium working groups in bringing together and promoting dialogue between the broadest range of stakeholders from the HTA ecosystem (industry, HTA bodies, academics and others) to identify needs and address challenges through practical tools and pilot exercises. Health Technology Assessment (HTA) helps decision-makers determine which medical technologies and treatments are effective and worth paying for. It can help ensure that the right treatments reach the right patients at the right time by assessing clinical evidence and economic evaluations to inform policy-making about reimbursement and market access.\nRecent policy changes, such as the EU HTA Regulation, require pharmaceutical companies to face stricter standards and shorter deadlines for submitting evidence. At the same time, HTA authorities must review an increasing number of complex analyses under the pressure for timely evidence-based decisions. Lastly, there is pressure on academia to provide easy-to-use HTA software and tools.\nInitially, the WG will focus on the following objectives.\n\nFoster Collaboration and Knowledge Sharing:\n\nUnderstanding the needs of all stakeholders for HTA analytics, and where the use of R may best fit.\nPromote the common goal of delivering HTA analytics work that meets those needs and efficiently utilizes R.\nBecome a central hub for connecting existing and new R initiatives in the HTA space, ensuring efficient and unified efforts.\n\nDevelop and Document Best Practices:\n\nDevelop and disseminate best practices for using R in HTA analytics work for clinical and economic evaluation.\nPromote transparency and reproducibility in HTA analytics work.\n\nExplore Pilot Studies with HTA authorities\n\nExplore pilot studies to test and refine open source R-based tools and frameworks for clinical and economic evaluation.\nPursue collaborative efforts with HTA authorities to validate these tools, demonstrating their value in real-world HTA scenarios.\n\n\nIf you think any of this is exciting and would like to become involved, please leave your name and email in issue number 1 at the HTA GitHub repository." + "text": "Jan Paul, Water Quality Lab Coordinator at Penobscot Nation, sampling in field\n\n\nIn a recent interview by the R Consortium, Angie Reed, Water Resources Planner for the Penobscot Indian Nation, shared her experience learning and using R in river conservation and helping preserve a whole way of life. Educated in New Hampshire and Colorado, Angie began her career with the Houlton Band of Maliseet Indians, later joining the Penobscot Indian Nation. Her discovery of R transformed her approach to environmental statistics, leading to the development of an interactive R Shiny application for community engagement.\npαnawάhpskewi (Penobscot people) derive their name from the pαnawάhpskewtəkʷ (Penobscot River), and their view of the Penobscot River as a relative guides all of the Water Resources Program’s efforts. This perspective is also reflected in the Penobscot Water Song, which thanks the water and expresses love and respect. Angie has been honored to:\n\nwork for the Water Resources Program,\ncontribute to the Tribal Exchange Network Group,\nengage young students in environmental stewardship and R coding, blending traditional views with modern technology for effective environmental protection and community involvement, and\nwork with Posit to develop the animated video about Penobscot Nation and show it at the opening of posit:conf 2024\n\nPlease tell us about your background and how you came to use R as part of your work on the Penobscot Indian Nation.\nI grew up in New Hampshire and completed my Bachelor of Science at the University of New Hampshire, followed by a Master of Science at Colorado State University. After spending some time out west, I returned to the Northeast for work. I began by joining the Houlton Band of Maliseet Indians in Houlton, Maine, right after finishing my graduate studies in 1998. Then, in 2004, I started working with the Penobscot Indian Nation. Currently, I work for both tribes, full-time with Penobscot and part-time with Maliseet.\nMy first encounter with R was during an environmental statistics class taught by a former USGS employee, Dennis Helsel during a class he taught for his business Practical Stats. He introduced us to a package in R called R Commander. Initially, I only used it for statistics, but soon, I realized there was much more to R. I began teaching myself how to use ggplot for graphing. I spent months searching and learning, often frustrated, but it paid off as I started creating more sophisticated graphs for our reports.\nWe often collaborate with staff from the Environmental Protection Agency (EPA) in Region One (New England, including Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont and 10 Tribal Nations). One of their staff, Valerie Bataille, introduced us to R Carpentries classes. She organized a free class for tribal staff in our region. Taking that class was enlightening; I realized there was so much more I could have learned earlier, making my journey easier. This experience was foundational for me, marking the transition from seeing R as an environmental statistics tool to recognizing its broader applications. It’s a bit cliché, but this journey typifies how many people discover and learn new skills in this field.\nThe Penobscot Nation views the Penobscot River as a relative or family. How does that make water management for the Penobscot River different from other water resource management?\nIf you watch The River is Our Relative, the video delves deeper into seeing the river from a relative, beautiful, and challenging perspective. This view fundamentally shifts how I perceive my work, imbuing it with a deeper meaning that transcends typical Western scientific approaches to river conservation. It’s a constant reminder that my job aligns with everything I believe in, reinforcing that there’s a profound reason behind my feelings.\nWorking with the Penobscot Nation and other tribal nations to protect their waters and ways of life is an honor and has revealed the challenges of conveying the differences in perspective to others. Often, attempts to bridge the gap get lost in translation. Many see their work as just a job, but for the Penobscot people, it’s an integral part of their identity. It’s not merely about accomplishing tasks; it’s about their entire way of life. The river provides sustenance, acts as a transportation route, and is a living relative to whom they have a responsibility.\nHow does using open source software allow better sharing of results with Penobscot Nation citizens?\nMy co-worker, Jan Paul, and I had the pleasure of attending and presentingat posit::conf 2023 and working with Posit staff to create an animated video that describes what we do and how opensource and Posit tools help us do it. It was so heart-warming to watch the video shown to all attendees at the start of conf, and was a great introduction to my shameless ask for help during my presentation and through a table where I offered a volunteer sign-up sheet/form, I was humbled by the number of generous offers and am already receiving some assistance on a project I’ve been eager to accomplish. Jasmine Kindness, One World Analytics, is helping me recreate a Tableau viz I made years ago as an interactive, map-based R Shiny tool.\n\nI find that people connect more with maps, especially when it comes to visualizing data that is geographically referenced. For instance, if there’s an issue in the water, people can see exactly where it is on the map. This is particularly relevant as people in this area are very familiar with the Penobscot River watershed. My aim is to create tools that are not only interactive but also intuitive, allowing users to zoom into familiar areas and understand what’s happening there.\nThis experience has really highlighted the value of the open source community. It’s not just about the tools; it’s also about the people and the generosity within this community. The Posit conference was a great reminder of this, andthe experience of working with someone so helpful and skilled has truly reinforced how amazing and generous the open source community is.\nHow has your use of R helped to achieve more stringent protections for the Penobscot River?\nBefore we started using open source tools, my team and I had been diligently working to centralize our data management system, which significantly improved our efficiency. A major shift occurred when we began using R and RStudio (currently Posit) to extract data from this system to create summaries. This has been particularly useful in a biennial process where the State of Maine requests data and proposals for upgrading water quality classifications.\nIn Maine, water bodies are classified into four major categories: AA, A, B, and C. If new data suggests that a water body, currently classified as a lower grade, could qualify for a higher classification, we can submit a proposal for this upgrade. In the past we have facilitated upgrades for hundreds of miles of streams, however it took much longer to compile the data. For the first time in 2018 we used R and RStudio to prepare a proposal to the Maine Department of Environmental Protection (DEP) to upgrade the last segment of the Penobscot River from C to B. Using open source tools, we were able to quickly summarize data and compile data into a format that could be used for this proposal, a task that previously took a significantly longer time. DEP accepted our proposal because our data clearly supported the upgrade. In 2019, the proposal was passed and we anticipate this process continuing to be easier in the future.\nYou are part of a larger network of tribal environmental professionals, working together to learn R and share data and insights. Can you share details about how that works?\n\n\n\nJan Paul, Water Quality Lab Coordinator at Penobscot Nation, sampling in field\n\n\nI’m involved in the Tribal Exchange Network Group (TXG), which is a national group of tribal environmental professionals like myself and is funded by a cooperative agreement with the Office of Information Management (OIM) at the Environmental Protection Agency (EPA). We work in various fields, such as air, water, and fisheries, focusing on environmental protection. Our goal is to ensure that tribes are well-represented in EPA’s Exchange Network, and we also assist tribes individually with managing their data.\nSince attending a Carpentries class, I’ve been helping TXG organize and host many of them. We’ve held one every year since 2019, and we’re now moving towards more advanced topics. In addition to trainings, TXG provides a variety of activities and support, including small group discussions, 1-on-1 assistance and conferences. Although COVID-19 disrupted our schedule we are planning our next conferencefor this year.\nOur smaller, more conversational monthly data drop-in sessions always include the opportunity to have a breakout room to work on R. People can come with their R-related questions, or the host might prepare a demo.\nOur 1-on-1 tribal assistance hours allows Tribes tosign up for help with issues related to their specific data. I work with individuals on R code for various tasks, such as managing temperature sensor data or generating annual assessment reports in R Markdown format. This personalized assistance has significantly improved skill building and confidence among participants and are particularly effective as they use real data and often result in a tangible product, like a table or graph, which is exciting for participants. We’ve also seen great benefits, especially in terms of staff turnover. When staff members leave, the program still has well-documented code, making it easier for their successors to pick up where they left off. These one-on-one sessions.\nAdditionally, I’ve been involved in forming a Pacific Northwest Tribal coding group, which still doesn’t have an official name as it is only a few months old. It began from discussions with staff from the Northwest Indian Fisheries Commission (NWIFC) and staff from member Tribes. And I am thrilled to say we’ve already attracted many new members from staff of the Columbia River Inter-Tribal Fish Commission (CRITFC). This group is a direct offshoot of the TXG efforts with Marissa Pauling of NWIFC facilitating, and we’re excited about the learning opportunities it presents.\nOur work, including the tribal assistance hours, is funded through a grant that reimburses the Penobscot Nation for the time I spend on these activities. As we move forward with the coding group, planning to invite speakers and organize events, it’s clear there’s much to share with this audience, possibly in future blogs like this one. This work is all part of our broader effort to support tribes in their environmental data management endeavors. If anyone would like to offer their time toward these kinds of assistance, they can use the TXG google form to sign up.\nHow do you engage with young people?\nI am deeply committed to engaging the younger generation, especially the students at Penobscot Nation’s Indian Island school (pre-K through 8th grade). In our Water Resources Program at Penobscot Nation, we actively involve these students in our river conservation efforts. We see our role as not just their employees but as protectors of the river for their future.\n\n\n\nSampling for Bacteria\n\n\nOur approach includes hands-on activities like taking students to the river for bacteria monitoring. They participate in collecting samples and processing them in our lab, gaining practical experience in environmental monitoring. This hands-on learning is now being enhanced with the development of the R Shiny app I’m working on with Jasmine, to make data interpretation more interactive and engaging for the students.\nRecognizing their budding interest in technology, I’m also exploring the possibility of starting a mini R coding group at the school. With students already exposed to basic coding through MIT’s Scratch, advancing to R seems a promising and exciting step.\nBeyond the Penobscot Nation school, we’re extending our reach to local high schools like Orono Middle School. We recently involved eighth graders, including two Penobscot Nation citizens, in our bacteria monitoring project. This collaboration has motivated me to consider establishing an R coding group in these high schools, allowing our students continuous access to these learning opportunities.\n\n\n\nProcessing bacteria sample\n\n\nMy vision is to create a learning environment in local high schools where students can delve deeper into data analysis and coding. This initiative aims to extend our impact, ensuring students have continuous access to educational opportunities that merge environmental knowledge with tech skills and an appreciation of Penobscot people, culture and the work being done in our program.\nOver the years, witnessing the growth of students who participated in our programs has been immensely gratifying. . A particularly inspiring example is a young Penobscot woman, Shantel Neptune, who did an internship with us through the Wabanaki Youth in Science (WaYS) Program a few years back , then a data internship through TXG and is now a full-time employee in the Water Resources Program. Shantel is also now helping to teach another young Penobscot woman, Maddie Huerth, about data collection, management, analysis and visualization while she is our temporary employee. We’re planning sessions this winter to further enhance their R coding skills, a critical aspect of their professional development.\nIt’s essential to me that these women, along with others, receive comprehensive training. Our program’s success hinges on it being led by individuals who are not only skilled but who also embody Penobscot Nation’s values and traditions. Empowering young Penobscot citizens to lead these initiatives is not just a goal but a necessity. Their growth and development are vital to the continuity and integrity of our work, and I am committed to nurturing their skills and confidence. This endeavor is more than just education; it’s about preserving identity and ensuring our environmental efforts resonate with the Penobscot spirit and needs." }, { - "objectID": "posts/thank-you-joseph-rickert-a-legacy-of-leadership/index.html", - "href": "posts/thank-you-joseph-rickert-a-legacy-of-leadership/index.html", - "title": "Thank You, Joseph Rickert: A Legacy of Leadership and Innovation in the R Community", + "objectID": "posts/r-addicts-paris-promoting-diversity-in-r/index.html", + "href": "posts/r-addicts-paris-promoting-diversity-in-r/index.html", + "title": "R Addicts Paris: Promoting Diversity in R", "section": "", - "text": "As we announce the end of Joseph (Joe) Rickert’s tenure as the Executive Director of the R Consortium, we reflect on his remarkable contributions that have significantly contributed to the R community. Joe’s leadership has been instrumental in fostering growth, innovation, and collaboration within the R ecosystem.\nFounding the R Consortium\nJoe has been with the R Consortium since its inception in 2014. He was initially appointed to be Microsoft’s representative to the Infrastructure Steering Committee (ISC) and was soon tasked with creating the R User Groups (RUGS) grants program. Joe also pioneered the formation of ISC working groups to foster industry-wide collaborative projects. In 2016, Joe was appointed to be RStudio’s representative to the Board of Directors. In 2018, he took on the role of Secretary, and by 2019, he was elected Chair of the Board. In 2023, Joe took on the role of Executive Director. Under his guidance, the R Consortium has grown into an inclusive organization supporting the R programming language and its community. Our new executive director, Terry Christiani, was affirmed by the board of directors in our August 2024 board meeting after a selection committee interviewed candidates and made recommendations.\nAdvancing User Groups\nOne of Joe’s notable achievements is his unwavering support for R user groups worldwide. He recognized the importance of grassroots movements in spreading the use of R and provided essential resources and funding to these groups. He was instrumental in funding the R-Ladies as a top-level ISC project that operates worldwide to provide safe places for women to come together and learn from each other in an otherwise male-dominated space. Joe was also directly involved with the Bay Area useR Group (BARUG), organizing events, speaking, or contributing to discussions around the R programming language, especially in the context of data science and statistical computing. This support has enabled countless R enthusiasts to connect, share knowledge, and collaborate on projects, thereby strengthening the global R community.\nIndustry Collaboration and Working Groups\nJoe actively reached out to industry leaders to create unique working groups aimed at solving industry-wide problems. These collaborations have led to the development of working groups focused on R programming solutions that benefit not only the community but also industries that rely on data science and statistical computing.\nA Legacy of Innovation\nThroughout his tenure, Joe has been a driving force behind numerous initiatives that have propelled the R community forward. His efforts have ensured that the R Consortium remains a dynamic and inclusive organization, fostering a spirit of collaboration and innovation. His leadership has left an indelible mark on the R community, and his legacy will continue to inspire future generations of R users and developers.\nAs we welcome new leadership, we extend our heartfelt gratitude to Joe Rickert for his dedication, vision, and tireless efforts in advancing the R community. Thank you, Joe, for your invaluable contributions and for paving the way for a brighter future for the R ecosystem." + "text": "Vincent Guyader, organizer of the R Addicts Paris and president of ThinkR, recently updated the R Consortium on the group’s activities. Last year, Vincent discussed the application of R in developing solutions for industrial problems. He emphasized the importance of helping people become fluent in R and leveraging the language to add value to their work. ThinkR is dedicated to enhancing R proficiency in various industries. The R Addicts Paris, one of France’s oldest and largest R user groups with 1,800 members, continues to foster a strong R community under Vincent’s leadership.\nPlease share your background and involvement with the RUGS group.\nMy name is Vincent, and I have been using R since my student days. During my studies, I took on freelance R projects for various companies. Currently, I head a company called ThinkR, where we have a team of over 10 experts specializing in everything related to R. Our services include training, consulting, developing Shiny applications, creating R packages, and more. We also collaborate with Posit and handle hardware installations for clients, primarily in France but also in Switzerland, Belgium, and other parts of Europe.\nSince 2018, I have been managing the R user group in Paris, known as the R Addicts Paris. It’s one of the oldest and possibly the largest R user groups, with 1,800 members. I aimed to organize meetups every three months, but the next one has been delayed due to internal organizational issues. I genuinely enjoy helping people become fluent in R and use the language to add value to their work.\nWhat challenges do you face in organizing the R Addict Paris group and how do you overcome those challenges?\nOne of the main challenges is that our users are not professional programmers or developers; they are specialists in fields like biology and finance. They have to shift their mindset to use programming languages. My daily job involves helping these individuals embrace software development. Coming from a genetics and biochemistry background, I understand how challenging this can be for non-developers. However, I love doing this, and I have a dedicated, competent team to assist.\nBased on your work with ThinkR, which industries in France do you see using R?\nWe have clients in various fields across France, including finance, retail, and research. The health sector is particularly prominent. For instance, a company that used SAS a few years ago now uses R & Python. About half of our clients currently use Python. While we provide Python installation on hardware, we don’t offer Python training yet.\nWe are committed to being the sole organization in France that can certify R users and developers. The French government has authorized us to issue an official certification akin to a diploma. Our goal is to elevate R proficiency across various fields in France. Our clients include businesses and individuals, with many investing their resources to learn proper software and programming skills.\nDo you host online or in-person events?\nI chose not to host online events. It’s a very opinionated choice because most meetups switched to online formats during the pandemic. At ThinkR, we are a fully remote company, and I spend my day on Zoom. While remote training is effective, I’ve found that in-person events work better for our user group.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people who are unable to attend physical events in the future?\nOne of the main challenges we face as a group is finding female speakers. I try to avoid having only male speakers, but I only get female speakers every fifth or sixth event, which is not enough. I encourage other R user group organizers to recognize our power to give a voice to different kinds of people. I push myself to include more female speakers. Sometimes, I encounter highly qualified women who hesitate to speak, while less experienced men are more willing. It’s challenging, but I strive to maintain a balanced representation.\nI consciously avoid engaging with speakers who lack substance, ensuring I have time to encourage qualified women to share their knowledge. Despite my efforts, female representation remains below 20%. A few years ago, my colleague Diane and I tried to connect with the R-Ladies Paris group. Many men are actively engaged there, and I wonder why that is.\nThere are many skilled women in the R community, which includes biologists and geneticists. There’s no excuse for the lack of female representation. We must remember our influence and endorse individuals who truly represent our values.\nWhat are some trending topics in R in your R User Group?\nI’ve noticed a decline in interest in statistics over the past two to five years. During meetups, we rarely discuss statistics. The machine learning and AI fields aren’t well-represented in R, possibly because most people in these fields use Python. It could also be due to regional differences or my network.\nYou had a Meetup “Raddicts x RTE – {webr} – Shinyproxy and return of the Reconteres 2024” on 19th June, can you share more on the topic covered? Why this topic?\nFor this event, we had two male speakers. Colin Fay discussed {webr}, a new JavaScript capability for launching user insights in the browser. This is powerful for deploying Shiny applications. Valentin Cadoret talked about new Shinyproxy functionalities, and tools that enhance the deployment of Shiny applications. So we focused heavily on Shiny once again." }, { - "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html", - "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html", - "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", + "objectID": "posts/r-addicts-paris-promoting-diversity-in-r/index.html#how-do-i-join", + "href": "posts/r-addicts-paris-promoting-diversity-in-r/index.html#how-do-i-join", + "title": "R Addicts Paris: Promoting Diversity in R", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + }, + { + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", "section": "", - "text": "The R Consortium is excited to announce the opening of our call for proposals for the 2024 Infrastructure Steering Committee (ISC) Grant Program on March 1st, 2024. This initiative is a cornerstone of our commitment to bolstering and enhancing the R Ecosystem. We fund projects contributing to the R community’s technical and social infrastructures.\nSubmit your proposal here!" + "text": "Dive into the world of validation at the first R Validation Hub community meeting of the year! What defines a validated R package? Is it ensuring reproducibility across systems? Prioritizing bug-free and well-maintained packages? We want to hear YOUR take!" }, { - "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#enhancing-the-r-ecosystem-technical-and-social-infrastructures", - "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#enhancing-the-r-ecosystem-technical-and-social-infrastructures", - "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", - "section": "Enhancing the R Ecosystem: Technical and Social Infrastructures", - "text": "Enhancing the R Ecosystem: Technical and Social Infrastructures\nOur past funding endeavors have spanned a variety of projects, illustrating our dedication to comprehensive ecosystem support:\n\nTechnical Infrastructure: Examples include R-hub, a centralized tool for R package checking, enhancements in popular packages like mapview and sf, and ongoing infrastructural development for R on Windows and macOS.\nSocial Infrastructure: Initiatives such as SatRDays, which facilitates local R conferences, and projects for data-driven tracking of R Consortium activities." + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-community-call-microsoft-teams-meeting", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-community-call-microsoft-teams-meeting", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", + "section": "Join the community call! (Microsoft Teams meeting) ", + "text": "Join the community call! (Microsoft Teams meeting)" }, { - "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#focused-funding-areas", - "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#focused-funding-areas", - "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", - "section": "Focused Funding Areas", - "text": "Focused Funding Areas\nThe ISC is particularly interested in projects that align with technical or software development that aids social infrastructure. It’s important to note that conferences, training sessions, and user groups are supported through the RUGS program, not the ISC grants." + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#meeting-details", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#meeting-details", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", + "section": "Meeting Details", + "text": "Meeting Details\n\nWhen: February 20, 12:00 EST\nWhere: Virtual meeting" }, { - "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#ideal-isc-projects", - "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#ideal-isc-projects", - "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", - "section": "Ideal ISC Projects", - "text": "Ideal ISC Projects\nWe look for proposals that:\n\nHave a broad impact on the R community.\nPossess a clear, focused scope. Larger projects should be broken down into manageable stages.\nRepresent low-to-medium risk and reward. High-risk, high-reward projects are generally not within our funding scope.\n\nProjects unlikely to receive funding are those that:\n\nOnly impact a small segment of the R community.\nSeek sponsorship for conferences, workshops, or meetups.\nAre highly exploratory." + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#why-attend", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#why-attend", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", + "section": "Why Attend?", + "text": "Why Attend?\nThis is your chance to share your perspective, learn from diverse viewpoints, and help shape the future of validation in the R ecosystem. Whether you’re a developer, user, or enthusiast, your insights are valuable." }, { - "objectID": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#important-dates", - "href": "posts/r-consortium-infrastructure-steering-committee-isc-grant-program-accepting-proposals-starting-march 1st/index.html#important-dates", - "title": "R Consortium Infrastructure Steering Committee (ISC) Grant Program Accepting Proposals starting March 1st!", - "section": "Important Dates", - "text": "Important Dates\n\nFirst Grant Cycle: Opens March 1, 2024, and closes April 1, 2024.\nSecond Grant Cycle: Opens September 1, 2024, and closes October 1, 2024.\n\nYou can learn more about submitting a proposal here.\nWe eagerly await your proposals and are excited to see how your ideas will propel the R community forward. Let’s build R together!" + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#lets-discuss", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#lets-discuss", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", + "section": "Let’s Discuss", + "text": "Let’s Discuss\nWhat does validation mean in the R world to you? Join us to debate, learn, and network. Mark your calendars and prepare to contribute to shaping the standards of R package validation." }, { - "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html", - "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html", - "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", - "section": "", - "text": "Join the R Consortium for an enlightening webinar on March 20th, 2024, at 4:00 PM ET, featuring Mine Cetinkaya-Rundel, Professor of the Practice of Statistical Science at Duke University. Discover the innovative Quarto tool to streamline the creation of reproducible, publication-ready manuscripts." + "objectID": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-call-here", + "href": "posts/unraveling-the-term-validation-join-the-discussion/index.html#join-the-call-here", + "title": "Unraveling the term “Validation”: Join the Discussion at the R Validation Hub Community Meeting on February 20, 2024", + "section": "Join the call here!", + "text": "Join the call here!" }, { - "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#key-highlights", - "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#key-highlights", - "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", - "section": "Key Highlights:", - "text": "Key Highlights:\n\nQuarto Manuscripts Introduction: Learn how to easily integrate reproducibility into your research with Quarto’s user-friendly features, creating comprehensive bundled outputs ready for journal submission.\nInteractive Demo: Witness a live demonstration of Quarto in action, showcasing how to enhance your current manuscript preparation process and address common challenges.\nExpert Guidance: Gain insights from Mine Cetinkaya-Rundel’s extensive experience in statistical science and reproducible research, offering valuable tips for improving your workflow." + "objectID": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html", + "href": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html", + "title": "R4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions", + "section": "", + "text": "Marcela Victoria Soto, co-organizer of the R4HR -Club de R para RRHH, Buenos Aires, Argentina, recently updated the R Consortium about the group’s recent activities. Last year, Sergio García Mora, the group’s founder, discussed the adoption and expansion of R in human resources in Argentina. Marcela emphasized the importance of data analysis for informed and agile decision-making for companies in Argentina. She also shared details of some of her budgeting, accounting, and annual income tax projects.\nR4HR is holding an online event called “Data Visualization in HR” on June 1, 2024, for Spanish-speaking R users. The meetup will be conducted via Google Meet.\nPlease share your background and involvement with the RUGS group.\nI earned a bachelor’s degree in labor relations and received training as a labor relations teacher at the University of Buenos Aires (UBA). Additionally, I completed a postgraduate course in Human Resources Management from the Pontifical Catholic University of Argentina (UCA) and a Diploma in Computational Social Sciences from the National University of General San Martín (UNSAM). I also attended the Argentina Program at the University of Salta, completing all three program modules.\nWhat industry are you currently in? How do you use R in your work?\nI currently work in the textile industry as the Head of Human Resources. At Yagmour, I use R to present reports on employee turnover, salary reports, accounting entries, etc. Additionally, I use R to consolidate the annual Human Resources budget according to the company’s accounts.\nCan you share what the R community is like in Buenos Aires?\nThe R4HR community is a collaborative space comprising individuals interested in data and human resources. We hold various meetups within the community where projects, R packages, etc., are shared. It is a Spanish-speaking community. The R Club is a meeting space for professionals in the field, where we can share tools, new ways of addressing issues, and novel approaches to similar problems. People who attend and are familiar with R sometimes need to be made aware of everything this programming language offers for simple and complex issues—the benefit of attending lies in sharing and creating spaces for knowledge exchange.\nYou have a Meetup on “Data Visualization in HR” on June 1st, 2024. Can you share more about the topic covered? Why this topic?\nIn June, we will hold a meetup to address Data Visualization in HR using the ggplot2 package, adding interactivity and context with plotly. This topic is not just interesting but also highly practical. Visualization is a great way to interpret data and graphically identify behavior patterns, which can also prompt questions about the presented information. The plotly package can add insights that are not apparent in the graphs. Additionally, plotly allows for creating interactive visualizations, enabling users to explore and manipulate the charts directly within the visualization. It can include zooming, data selection, and more, providing a richer and more dynamic user experience.\nThis meetup’s target audience is individuals interested in understanding the benefits of working with R‌ and people in the human resources field who are interested in the topic.\nFor this event, we conducted the invitation through Meetup and provided a Google Meet link. After the event, we will upload it to YouTube and communicate to the community through social media.\nWould you like to tell us about an interesting recent Meetup from the group?\nI recently presented at a group event titled Annual Income Tax with R to showcase the various problems one can address using R beyond data visualization or analysis. In Argentina, to carry out this development, one must consider the guidelines provided by the Federal Administration of Public Revenues (AFIP), which, at the national level, determines the parameters to be used for presentations; payroll software interprets these parameters. Those who do not have a payroll system can use the development done in R to carry out this presentation.\nIn Argentina, the frequent changes and calculation methods have made everything related to this tax quite complex. They impose this tax on salaries that are considered high-value. It is a tax withheld by the company, and due to inflation and various modifications, the analysis and handling of this tax end up being one of the most complex issues for employees in the country. I made this process easier in this meetup by using R.\n.png\nWhat trends do you currently see in R language and your industry? Are there any trends you see developing in the near future?\nTrends in R are about its growing popularity and its transformative impact. It allows more people to join and enhances its application to various problems. There is also ongoing work on clustering applied to Human Resources to understand how each group functions, their relationships, common characteristics, etc. In Argentina, due to the current economic situation, data analysis not only at the salary level but also at the soft skills level is an urgent necessity for companies aiming to use data for agile decision-making. Business data is vital for analyzing the rest of the decisions that need to be made by Human Resources and the entire company. To use data for agile decision-making, companies must consider salary levels, understand which soft skills are needed and what the context requires, and make decisions accordingly.\nA trend that will continue to develop in the future relates to Artificial Intelligence and how it complements everyday tasks or serves as a support tool.\nPlease share about a project you are working on or have worked on using the R language. What is the goal/reason, result, or anything interesting related to your industry?\nI have worked on several projects in R, starting with the basics related to data visualization of absenteeism, turnover, and salary analysis.\nSomething different that I worked on with R was creating the annual Income Tax presentation. The objective was to consolidate the yearly information of each employee covered by the regulations according to the parameters provided by the Federal Administration of Public Revenues. It required interpreting each requirement at the programming level. This file had to be submitted in TXT format, which meant working with rare extensions in Human Resources areas.\nAnother different project in R was creating accounting entries. It allows for systematizing a large amount of information and grouping it according to the accounts.\nI have also used R to prepare information presented to the Ministry of Labor, which required extensive cross-referencing. For example, it involved cross-referencing gender with absences, working hours, days, leaves, and paid leaves, among other variables. The complexity of this was the relationship between the data, where any incorrect data would ultimately lead to inconsistencies in the information.\nLastly, before applying R, the Budgeting process in our company involved transferring information across different Excel sheets, using pivot tables, and copying and pasting it into a summarized form. It took a significant amount of time, and whenever a variable needed to be changed, the entire process had to be redone, which implied errors due to the large amount of information transfer. Today, people work on this process dynamically in Excel and then process it in a script that consolidates all the information in minutes, sometimes less. It allows for the creation of multiple scenarios dynamically in a time of significant volatility and limited time. This process using R has achieved a substantial reduction in time, in addition to ensuring data consistency." }, { - "objectID": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#event-details", - "href": "posts/join-our-r-medicine-webinar-quarto-for-reproducible-medical-manuscripts/index.html#event-details", - "title": "Join our R/Medicine Webinar: Quarto for Reproducible Medical Manuscripts", - "section": "Event Details:", - "text": "Event Details:\nWhen: March 20th, 2024, at 4:00 PM ET\nDon’t miss this opportunity to refine your manuscript preparation process with the latest advancements in reproducibility technology.\n\nRegister now!" + "objectID": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html#how-do-i-join", + "href": "posts/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solution/index.html#how-do-i-join", + "title": "R4HR in Buenos Aires: Leveraging R for Dynamic HR Solutions", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html", - "href": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html", - "title": "Ann Arbor R User Group: Harnessing the Power of R and GitHub", + "objectID": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html", + "href": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html", + "title": "Collaborative Growth: The Botswana R User Group and Regional Partnerships", "section": "", - "text": "The R Consortium talked to Barry Decicco, founder, and organizer of the Ann Arbor R User Group, based in Ann Arbor, Michigan. Barry shared his experience working with R as a statistician and highlighted the current trends in the R language in his industry. He also emphasized the significance of organizing regular events and effective communication for managing an R User Group (RUG).\nPlease share about your background and involvement with the RUGS group.\nThroughout my professional career, I have gained extensive experience in various industries as a statistician. Statisticians are often thought of as either staying in one industry for their entire career or frequently transitioning between them. I have followed the latter path, having held positions at Ford Motor Company, their spinoff Visteon, the University of Michigan School of Nursing, the University of Michigan Health System, Nissan Motor Company, Volkswagen Credit (as a contractor), Michigan State University, and currently Quality Insights.\nI have been using the R programming language consistently for several years now. I have extensively worked with R during my tenure at Michigan State University as a member of the Center for Statistical Training and Research (CSTAT). CSTAT serves as the university’s statistical laboratory. Our team heavily relied on R as our preferred software for statistical analysis.\nOur reporting process involved using R Markdown reports. Steven Pierce, the assistant director, developed a highly complex and upgradeable system using R Markdown to process data. This system allowed us to initiate a report and then trigger the R Markdown file to process the data and generate the final datasets for each report. Another R Markdown file was then called to render the report. This streamlined process enabled us to produce about 40 PDF reports within 45 minutes. The process remained relatively straightforward when we needed to make modifications, such as changing the reporting period from fiscal years to calendar years or adding or subtracting individuals, units, or departments.\nI have recently started a new job primarily working with the SAS programming language. Initially, I will focus on gaining proficiency in this area. After that, I will transition to performing more in-depth analysis and ad hoc reporting, requiring me to use additional tools and resources. I have also moved to a new system where we use Hive or Hadoop through Databricks. As part of my role, I am responsible for taking over the current reporting system and identifying future reporting needs. This will require me to use R extensively.\nBefore the COVID pandemic, the R users group met in Ann Arbor. However, the pandemic dealt a major blow to the group, and we are still recovering from its impact. In our efforts to revive the group, we continued with the same theme as before: a mix of programming and statistics. However, we have been focusing more on programming and simpler analysis to make it easier to get the group restarted. We have also introduced some new presenters covering topics such as machine learning pipelines in their presentations.\nCan you share what the R community is like in Ann Arbor?\nR has become a popular programming language in academia and will likely remain relevant in this field. However, general coding and applications are more prevalent in the industrial sector. Python is gaining popularity because it attracts a broader range of programmers, including those who are not data or analytics specialists. Therefore, R will continue to be a significant but specialized tool.\nCurrently, I have noticed a significant decrease in the usage of SAS. This trend is driven by the dislike of license fees among individual and corporate users. The matter is further complicated by corporate accounting practices, where different funding sources may have varying spending restrictions. As a result, organizations may end up incurring higher salary expenses because of the complexity of corporate accounting processes.\nIf a company spends a fixed amount, say $10,000, on SAS licenses yearly, it might not like it. But then, it may hire additional staff to do the same work SAS did earlier. The salary of these people, and other associated costs, may come from a different funding source. As a result, the company may spend a significant amount of money, ranging from $120,000 to $150,000 annually, to replace a smaller amount of $10,000 to $20,000 annually. However, whether this arrangement is acceptable would depend on the funding source.\nDo you have an upcoming meeting planned? What are your plans for the RUG for this year?\nOur next presenter, Brittany Buggs, Staff Data Analyst at Rocket Mortgage, will demonstrate the usage of the GT package for generating tables. Additionally, we are striving to establish closer integration with the Ann Arbor chapter of the American Statistical Association to foster mutual support and collaboration between the groups. We have been conducting hybrid meetings catering to in-person and virtual attendees. Ann Arbor Spark, a local startup business development organization, has generously provided us with a physical meeting space. Our meetings follow a hybrid format, recognizing the convenience and accessibility it offers to many individuals.\nThis year, I aim to have more presenters as I have been doing all the presentations by myself. I plan to raise awareness about R, R Markdown, and Quarto and show people how these tools can be useful. I will promote these tools at the University of Michigan and other companies.\nWhat trends do you currently see in the R language?\nWhen it comes to data analysis, R has a clear advantage. The tidyverse syntax is easy to understand, even for those unfamiliar with data tables or Pandas-like programming paradigms.\nWhen working with data tables, both base R and Pandas use programming languages that differ significantly from English, which can make understanding them difficult. On the other hand, R Markdown has a notable advantage in that it makes it easy and quick to generate HTML documents. For instance, my former supervisor at C-STAT spent much time creating visually appealing PDF documents because his reports were highly customized. However, if your main goal is to produce polished reports relatively quickly, R Markdown is the better option.\nI understand that my main focus is the transition to Quarto. As someone who used to work with R Markdown, I have been learning more about Quarto and adjusting to its features. However, I am concerned about how new users may react to Quarto. I plan to give presentations throughout the year to gauge their responses and better understand any potential issues that may arise.\nMoreover, I’ve noticed that many people are unaware of R Markdown’s capabilities. To address this, I conducted an introductory session on R Markdown for a group at the University of Michigan. During my thirty-minute presentation, the participants were surprised by the diverse functionalities of R Markdown, as they were used to working with JavaScript and basic R. Although I had inferior knowledge compared to some of the individuals in the group, my ability to perform certain tasks using R Markdown impressed them.\nOne of the benefits of R Markdown is its ability to run multiple languages, with each language being executed chunk by chunk. I hope Quarto will also support this feature.\nIn the past, I have presented on calling R from SAS and SAS from R. During these presentations, I demonstrated how to run a SAS job within an R chunk. However, this approach has a limitation. For it to work, SAS must be accessible from the computer running the R code. This means the SAS installation must be on the computer or a network drive that the computer recognizes as a local drive. On a certain occasion, while using Enterprise Guide on a Linux machine, I faced a problem. I couldn’t locate the executable file (EXE) for SAS from my computer, which obstructed me from executing a SAS job.\nIt is now possible for individuals to use R Markdown with their preferred programming languages. For instance, R Markdown can be used with Pandas for most cases, which can help individuals produce visually appealing reports quickly. With this approach, all the work can be done within Pandas, and users need only basic knowledge of R. Therefore, Quarto can be seen as a language for report writing only. I will keep an eye on this situation and evaluate its effectiveness.\nI want to highlight the smooth combination of Git and GitHub with R. I use GitHub frequently in my work, though I am not very skilled because RStudio IDE fulfills most of my requirements. I rarely face conflicts due to my carelessness; I must interact with Git and GitHub manually.\nI highly recommend the book “Happy Git with R” as an essential resource for beginners. This comprehensive guide provides a step-by-step approach to setting up and using Git and GitHub effectively in R.\nWhen using Git in conjunction with R, you can access a detailed transaction history that can be reviewed anytime. I have found this feature incredibly useful and have been able to recover important work using this method. As a data management instructor at MSU, I have also taught my students how to execute this process manually. However, having R Studio automatically handle this task is much more convenient.\nIn fact, I used SPSS to conduct a project and leveraged GitHub as an experiment. I utilized the data management capabilities of RStudio and found the results satisfactory.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nI suggest that RUG organizers should arrange regular monthly meetings. It would be advantageous to fix these meetings on the same day and time every month, as it will help attendees get accustomed to the routine and know when to expect them.\nIn my years of working with different groups, I have noticed that if we don’t consciously communicate regularly, our communication will become less effective over time. This can lead to a lack of new ideas and engagement, and we may unintentionally exclude potential participants.\nFor almost 20 years, I have been part of a group that communicated through a university mailing list. However, we faced difficulties as the list was not easily discoverable through search engines like Google. This made it challenging for new individuals to find or contact us. We have taken steps to tackle this problem by introducing Meetup as a new tool that can be used alongside or instead of our traditional mailing list. The main benefit of Meetup is that it is easily searchable on Google, which makes it simple for anyone to locate and get in touch with our group.\nI want to emphasize the importance of effective communication. Neglecting communication efforts can cause a decline in communication quality. I have personally witnessed this happening in different groups, and I have seen others experiencing similar challenges." + "text": "In 2022, Edson Kambeu, founder and organizer of the Botswana R User Group, shared his plans with the R Consortium how the “New R Community in Botswana Wants to Implement Data Into Local Businesses. In this new interview, Edson updated the R Consortium about the group’s growth and recent activities. The Botswana R User Group has attracted a global audience through its online events and actively collaborates with R User Groups in the region.\nThe Botswana R User Group is seeking speakers for their upcoming online events. If you are an R expert interested in sharing your experience with R users in Botswana, please contact Edson at botswanarusers@gmail.com\nPlease share about your background and involvement with the RUGS group.\nMy educational background is in finance. I pursued finance and investments for my master’s degree but also studied economics during my undergraduate years. Mathematics has been my strongest subject since primary school, and I’m passionate about it. This passion led me to develop an interest in Statistics and statistical software.\nIn the past, I mainly used SPSS, Stata, and EViews for my statistical analysis projects. Then, someone introduced me to data science. During my research on data science, I discovered that two popular programming languages are used for it. I installed Python for the first time, but I could not use it as I didn’t have a computer science background. So, I switched to R and started watching a few YouTube videos. From there, I continued to learn and improve my skills in R.\nR was my first language of choice for Data Science. Currently, I use both R and Python for my work.\nI am pursuing a Master’s in Computer Science with Data Science from the University of Sunderland. Our different modules use R and Python, and knowing both languages is helping me in my studies.\nAs I was learning R around 2019 and beginning to follow several R Users on Twitter, I discovered that small R communities gathered together to learn and share knowledge about it. R Ladies Johannesburg in South Africa inspired me the most, as they held events more frequently during that time. I then became interested in starting an R User community in Botswana.\nIn February 2020, I reached out to Heather Turner, who was scheduled to visit Botswana and other Southern African countries to conduct Introduction to R workshops. During our conversation, Heather provided me with all the information needed to start a community. As a result, in March 2020, Botswana R Users was established during Heather Turner’s Introduction to R workshop.\nHow has your group been doing since we last talked?\nOur meetup group had about 100 members when we last talked to you. We now have almost 400 members. However, I have observed that people from different countries are joining us. We are now a global meetup group rather than a Botswana User group. This is because we mostly hold online meetups, which allow people from other countries to join.\nParticipants attending an online meetup hosted by Botswana R users in collaboration with Estwatini R Users and Bulawayo R\nWe are, however, still committed to growing the local community. We want to see more local participation in our meetup group. Last year, we collaborated with R Ladies Gaborone to organize an introduction to R workshop to increase our local membership. We are pleased to announce that this year, we plan to hold another workshop as a pre-conference event in the upcoming Botswana Deep Learning Indaba conference in July 2024. This workshop will help us to increase our local membership further and create more awareness about our group.\nParticipant at the Introduction to R Workshop held in collaboration between Botswana R users and R Ladies Gaborone\nWe value collaborations with our partner R User meetup groups in Southern Africa. In recent years, we have had regular meetups involving collaborative efforts with the Bulawayo R User Group from Zimbabwe, the Eswatini R User Group from Swaziland, and the Namibia R User Group from Namibia. We have established a routine of holding joint meetups almost every two months, depending on the availability of speakers. The idea is to grow our communities by increasing the frequency of activities.\nVebash Naidoo of RLadies Jozi presenting in an online meetup for Botswana R Users\nYou have a Meetup titled “GIS and Creating Dashboards in R. A case study of conflicts events in Kenya,” can you share more on the topic covered? Why this topic?\nI had an opportunity to attend a series of workshops and webinars organized by the United Nations for their Datathon. I realized the importance of GIS in advancing sustainable development. In January 2024, I invited Godwin Murithi, a GIS specialist, to present a topic on GIS. The topic was “GIS and Creating Dashboards in R. A case study of conflict events in Kenya.” We wanted to expose our members to the rising field of GIS and show them how the R language and various packages can help solve GIS problems. It was a fascinating topic for our participants, and they loved it.\nHow has the use of R evolved in the industry since we last talked?\nWe are observing an increasing acceptance of the R programming language, particularly in universities. Some universities have adopted R as their primary language for statistics and quantitative programs. This trend indicates academic institutions’ growing preference for open source programming languages.\nAny techniques you recommend using for planning for or during the event? (Github, zoom, other) Can these techniques be used to make your group more inclusive to people that are unable to attend physical events in the future?\nOrganizing is one of the most challenging tasks. To get speakers, I have primarily used Twitter (now called X) and LinkedIn to communicate with people who might want to speak at our meetup groups. Lately, there has been a problem with sending direct messages on Twitter. The reason is that Twitter has changed its messaging system. Now, to send a direct message, you need to be verified. I have been affected by the fact that my usual way of talking to people has been disrupted. Therefore, I have resorted to using LinkedIn to search for people interested in R and reach out to them. Sometimes, they are too busy or cancel, which can be challenging. However, I have been successful in finding potential speakers through these platforms.\nOccasionally, we use different video conferencing tools like Zoom and Google Meet. We usually rely on these two platforms. However, sometimes a speaker may prefer using Google Meet over Zoom, so we try to be flexible and accommodate their preferences.\nWe also use GitHub. We have our account, and if the speaker has their material on GitHub, they can share the link with us. Alternatively, they can provide us with the material directly, and we will upload it onto our own GitHub account for the community to access. Ultimately, it all depends on the speaker’s preference.\nPlease share about a project you are working on or have worked on using the R language. What is the goal/reason, result, or anything interesting, especially related to the industry you work in?\nOne of my recent school projects was to create a dashboard about UK imports and exports, which I completed towards the end of last year. I developed this project using Shiny and R packages such as Shiny Dashboard, ggplot2, and dplyr.\nI’m currently working on another project that is still in its early stages. The goal of this project is to identify areas in Botswana that require greater financial inclusion. I am currently gathering data and plan to utilize R and Python to apply geospatial techniques.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nI have observed that people find Quarto and GIS techniques interesting. The community is gaining increasing interest in these areas, and I foresee the increasing use of R in GIS applications." }, { - "objectID": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html#how-do-i-join", - "href": "posts/ann-arbor-r-user-group-harnessing-the-power-of-r/index.html#how-do-i-join", - "title": "Ann Arbor R User Group: Harnessing the Power of R and GitHub", + "objectID": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html#how-do-i-join", + "href": "posts/collaborative-growth-the-botswana-r-user-group-and-regional-partnerships/index.html#how-do-i-join", + "title": "Collaborative Growth: The Botswana R User Group and Regional Partnerships", "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, { - "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html", - "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html", - "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", + "objectID": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html", + "href": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html", + "title": "The Impact of R on Academic Excellence in Manchester, UK", "section": "", - "text": "R/Pharma 2024 is coming up Oct 29-Nov 1, 2024. This is a free event, fully virtual. R users in Pharma around the world are encouraged to attend, ask questions, and contribute their opinions!" + "text": "The R Consortium recently spoke with the organizing team of the R User Group at the University of Manchester (R.U.M.). R.U.M. aims to bring together R users of all levels to share R best practices, expertise and knowledge. The group is open to all staff and postgraduate researchers at the University of Manchester, UK.\nDuring the discussion, the team shared details about their recent events and their plans for this year. They also discussed the latest trends in the R programming language and how they are utilizing it in their work.\nMartín Herrerías Azcué\nResearch Software Engineer\nUniversity of Manchester\nAnthony Evans\nResearch Software Engineer\nUniversity of Manchester\nLana Bojanić\nResearcher PhD Candidate\nUniversity of Manchester\nRowan Green\nPhD Student in Evolutionary Microbiology \nThe University of Manchester\nPlease share about your background and involvement with the RUGS group.\nMartin: My name is Martin, and I joined the University of Manchester a year ago. They assigned me to manage the R user group, which was previously under Camila’s leadership. Although I am officially in charge, this is a collaborative effort between all of us who are present in this meeting, along with some others who couldn’t join. I work in Research IT and mainly use R for projects assigned to me by other people.\nAnthony: My name is Anthony and I work at Research IT with Martin at the University of Manchester. I first came into contact with R when I was a student. Later, I became a helper at many of the university’s R training courses based on the Carpentries training courses. Camila, who was Martin’s predecessor, was also a trainer at R and she formed the R Users Manchester group. I volunteered to help her with the group a year ago, and it just turned a year old. After that, I continued to be a part of the group.\nLana: Hi there, my name is Lana. I am a PhD student and research assistant at the Division of Psychology and Mental Health at the University of Manchester. I have been using R for the past six years, ever since my Master’s degree. I have been a part of the group since its inception and have been running R introduction sessions for beginners within my division for a couple of years now. When I learned the group was being formed, I contacted Camila a year ago. This makes us founding members of the group.\nRowan: Hello, my name is Rowan Green. I am currently a PhD student in the Department of Earth and Environmental Sciences. For my research work, I use R extensively for simulation modeling bacteria, analyzing lab data, and creating visualizations. The best thing about using R is that it produces much prettier visualizations than other options available to us as biologists. We have a lot of master’s and undergraduate students coming through the lab. I often give them pre-written scripts they can tweak to create their plots. It’s exciting to see them working hard to produce their plots.\nCamilla mentioned starting a group to share knowledge about R on a university-wide level. I found this a great opportunity to participate and learn from others’ presentations during the meetings. It has been an enriching experience so far.\nCan you share what the R community is like in Manchester?\nAnthony: In industries such as banking and finance, R is frequently used to create graphs to showcase econometric data in an easy-to-understand manner. The graphical capabilities of this programming language make it a popular choice in these fields. The university we’re in has access to the Financial Times, which is known for producing visually stunning graphs. Interestingly, they also use an R package called FT plot tools, which is a specialized package solely for their use. So, it’s safe to say that R has a significant presence in the banking and finance sectors.\nAre your meetups virtual or in-person? What topics have you covered recently? What are your plans for the group in the future?\nMartin: Our events are a mix of in-person and online meetings. There have been talks about developing packages, data visualization, automating reports, and working with tables. We usually cover topics we are confident about or know people from the university are working on. However, we are also trying to get external speakers to come and talk. It’s challenging, but we are doing our best to make it happen. We are currently accepting proposals from potential speakers.\nOur book club has mostly or completely taken place online.\nLana:  Bookclub was mostly online. During the summer book club, we were reading R for Data Science. We covered a chapter or two chapters each time. We had the book’s second edition, and people from all over the university joined the club.\nWe were discussing the possibility of changing the format of Tidy Tuesdays. We received feedback that people don’t have enough time to come up with something extra creative every month. Additionally, there has been a need for more practice. Therefore, we plan to redesign Tidy Tuesdays to be more practice-oriented than creativity-oriented. We will be implementing these changes this year.\nAnthony: We’ve recently had several discussions on useful packages, particularly in R. Some packages that were developed and published were custom-made. We also had presentations on the cosinor and cosinor2 packages, which are used for fitting curves, and an R update package for validating clinical prediction models.\nThere are two other R groups in Manchester. Our aim for this year is to establish communication with them and collaborate in a coordinated manner. (Editor’s Note: We recently talked with the Manchester R User Group.) Currently, our group solely focuses on the internal R community at the University of Manchester.\nAny techniques you recommend using for planning for or during the event?\nRowan: I’m not sure if everyone would agree with me, but I think we did well in the format of our meetings. We started with brief, brief talks – within an hour – followed by questions and discussions, which worked well.\nHowever, the harder part has been promoting and informing people about the meetings. Sometimes, word of mouth has been more effective than emails and posters. I noticed that they were interested in attending when I encouraged my lab group, who all use R. But without any scheduled reminders and someone to encourage them, it may be difficult to get people to come.\nLana: It’s important to identify everyone’s strengths or specialties within the organizing group, as they will probably be useful in the first few events. After that, you can expand your network within the community, which is easy to do since people are easily reachable. This will allow you to find interesting topic ideas and strengths to draw from.\nWhat trends do you currently see in R language?\nMartin: I’ve noticed a growing interest in Shiny lately, as I manage a pilot server for the university and have seen an increase in users over time. There have also been several inquiries about using R within our high-performance computer cluster, which may be something we can offer to the university. This interest is not surprising, given the current hype around machine learning.\nA trending area that applies to multiple platforms, not just R, is towards reproducible research and compatibility between different programming languages. This means that R can be integrated with Python and other languages to create a documented and integrated pipeline. I’ve been experimenting with SnakeMake, which works well with R, but it would be great to see more integration from the R side, perhaps through the common workflow language or another similar tool.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nRowen: Recently, I wrote a preprint of a paper where we simulated the growth and mutation of bacteria using differential equations and R programming language. To perform the simulation, we utilized high-performance computing, which enabled us to simulate various ways the bacteria could grow by adjusting the rates of reactions occurring within the cells. This simulation required high-performance computing to be feasible for running multiple simulations.\nAfter running simulations, we came up with some ideas to test in the lab. Our focus was on measuring mutation rates, and we used statistical analysis to estimate them through R. We have been striving to ensure reproducibility, and as a result, we have annotated all the data tables and R scripts with the paper.\nIt has been an interesting journey for me. I had to tidy up my messy scripts and think about how someone else would perceive them. I had to ensure they made sense. However, the project was fascinating as I generated hypotheses using R, tested them, and analyzed and visualized them with the same tool. R is a complete tool that can handle all aspects of the process, making it a brilliant choice." }, { - "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free", - "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free", - "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", - "section": "Register now for free!", - "text": "Register now for free!\nFor the first time, R/Pharma will be including a dedicated Asia-Pacific (APAC) track which better aligns with Asian time zones and includes 2 pre-conference workshops, 3 keynotes that will be recorded from the global track and then streamed with live discussion sessions thereafter, and 2 live panels, one focusing on Japan, and one on China. In addition, there are 20 contributed talks.\n\n\nThe R Consortium talked with Daniel Sabanés Bové, R/Pharma organizer, co-chair of openstatsware.org, co-founder of RCONIS, a biostatistics consulting and software engineering firm, (co-)author of multiple R packages published on CRAN and Bioconductor, and author of the book “Likelihood and Bayesian Inference: With Applications in Biology and Medicine.” Daniel is giving a 3-hour workshop on October 27 with Joe Zhu (Roche) on “Good Software Engineering Practice for R Packages,” and introducing openstatsware in a talk on 31 October.\nWe talked to Daniel to find out more about the new APAC track.\n\n\nWhy is R/Pharma adding an APAC track now?\nLast year, I was on an extended business trip for Roche for 6 weeks in Shanghai. I was fortunate to attend the first China Pharma R User Group (RUG) Meeting in March 2023, so I have seen how active the community is. I also found out how tough it can be to be based in Asia - you just don’t get enough sleep working with colleagues in Europe and North America!\nSo when the R/Pharma program committee reported that they have been approached by colleagues in Asia about organizing events in their time zone or region, I used the opportunity of my upcoming move to Taipei mid 2024 to propose organizing a dedicated track in the Asia-Pacific timezones.\nThe R/Pharma APAC track is designed specifically to help avoid time zone burnout, as well as to foster the APAC regional community.\n\n\nHow does adoption of R in Pharma in APAC differ from other parts of the world?\nThis is not based on robust data, but from a personal perspective I have noticed one key feature is that biotech and Pharma companies in Asia are concentrated in a few hubs, there is Shanghai, Tokyo, and not too many more. Having said that, I have noticed the rise of Contract Research Organizations (CROs) e.g. in India that are starting to use R - the CROs are catching up. Compare that to Europe and the United States, with a wide range of Pharma companies and organizations spread around many different locations. This also influences the adoption of R and open source technologies in general.\n\n\nWhat are some of the key topics being covered in the APAC track?\nI was pleasantly surprised at the amount and variety of proposals submitted. We have organized the APAC track’s topics into 6 types of sessions:\n\nChange management (moving from proprietary software to R)\nSessional clinical reporting (producing tables and reports)\nShiny\nBest practices\nAI/ML\nHigh dimensional data\n\nWe have quite an exciting APAC Track program that includes:\n\n2 pre conference workshops\n3 keynote streams, which are recorded keynotes that are slightly delayed to stream during convenient APAC times, plus we have added some discussion after\n2 live panel discussion (China, Japan)\n20 contributed talks in total\n\n\n\nFull Agenda\nA full list of workshops, keynotes, talks and panels is available here.\nIf you use the filter button you can get just the APAC Track information." + "objectID": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html#how-do-i-join", + "href": "posts/the-impact-of-r-on-academic-excellence-in-manchester-uk/index.html#how-do-i-join", + "title": "The Impact of R on Academic Excellence in Manchester, UK", + "section": "How do I Join?", + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute." }, { - "objectID": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free-1", - "href": "posts/rpharma-2024-virtual-oct29-nov1-apac-track/index.html#register-now-for-free-1", - "title": "R/Pharma 2024, Virtual, October 29-November 1, Includes New Dedicated Asia-Pacific (APAC) Track", - "section": "Register now for free!", - "text": "Register now for free!\nIf you, or your organization, would like to support R/Pharma you can do so following this link. Be sure to follow the R/Pharma blog, LinkedIn and Twitter/X." + "objectID": "posts/unlocking-the-power-of-r-for-insurance-and-actuarial/index.html", + "href": "posts/unlocking-the-power-of-r-for-insurance-and-actuarial/index.html", + "title": "Unlocking the Power of R for Insurance and Actuarial Science: Webinar Series Recap", + "section": "", + "text": "The R Consortium recently hosted a webinar series tailored specifically for insurance and actuarial science professionals. This series, called the R/Insurance webinar series, led by experts Georgios Bakoloukas and Benedikt Schamberger, was crafted to guide attendees from transitioning from Excel to R to implementing R in production environments, fostering a performance culture with R, and mastering high-performance programming techniques. \nWhether new to R or looking to deepen your expertise, these webinars offer valuable insights into leveraging R’s capabilities in your field. All sessions are now accessible on YouTube, providing a fantastic resource for ongoing learning and development. \nFor further details and to watch the webinars, visit the R Consortium’s website." }, { - "objectID": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html", - "href": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html", - "title": "Keith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R", + "objectID": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html", + "href": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html", + "title": "ConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers", "section": "", - "text": "Keith Karani Wachira, the Dekut R Communityorganizer based in Nyeri, Kenya, was recently interviewed by the R Consortium and shared his journey in the R community, which began in 2019 during his university years. Sparked by a tech meetup, Keith’s interest grew through the pandemic sessions. Now in academia, he uses R to address business automation challenges, attracting industry professionals to his practical sessions. Excited by trends like AI integration and tools like Quarto, Keith foresees increased automation and efficiency. Outside work, he enjoys baseball, graphic design, web development, and teaching R, finding great reward in his students’ success.\nPlease share about your background and your involvement in the R Community. What is your level of experience with the R language?\nI began my journey with R in early 2019 while studying at university. In May 2019, I learned about a tech community through a friend who posted in one of our school’s WhatsApp groups, inviting us to join a meetup. Curious, I decided to attend.\nI remember the meetup was on a Saturday, and it turned out to be the launch of a new club. My friend invited me and was part of the Microsoft Learn Students’ Ambassadors. His classmates used R for their engineering projects, which sparked my interest.\nDuring the first lesson, I found it challenging as there were about 30 students, most of whom were first-year students pursuing various degrees, including Business Information Technology, which I was majoring in, along with a minor in Communication. My first programming language that year was C, which I found interesting.\nOver time, I found the R language interesting, especially its syntax. What fascinated me the most was how data could be used to create visualizations. This curiosity led me to explore data from my local sewerage and water company, using R to create informative visualizations and derive insights that can be used in decision making.\nI continued attending the sessions in 2020 during the pandemic. Although we no longer had in-person classes, we adapted using Microsoft Teams for our meetings. Eric organized the meetups and arranged tech talks with speakers from Posit (formerly RStudio) and NairobiR. I remember attending these sessions and understanding how powerful R is.\nThroughout 2020, I attended regularly but still lacked confidence in the language. However, in 2022, I made significant progress. Under Eric’s leadership, we expanded the community to involve more people, especially students from the department of Actuarial Science, Telecommunication Engineering and electrical engineering. We set up a structured learning environment based on materials from Hadley Wickham’s books and resources from the R website and blogs.\nEric’s leadership greatly influenced me. He taught us how to write blogs using Markdown and publish on RPubs. This is a bit about my background. Today, we continue to teach R, following a structured approach to help others intermediate in using the language.\nWhat industry are you currently in? How do you use R in your work?\nI’m currently in academia, primarily focusing on various technical challenges. We hold sessions where we demonstrate the use of R in robotics for members in Electrical Engineering and Telecommunication Engineering. For those in Actuarial Science, we show how to create time series models using R.\nComing from a background in business and information technology, I focus on solving business challenges, particularly automating business processes and addressing issues in banking, logistics, retail using opensource datasets. Our efforts are not limited to academia; we concentrate on applying R across different disciplines within academia to tackle these challenges.\nWhy do industry professionals come to your user group? What is the benefit of attending?\nAn interesting scenario arose when I became interested in EMS (Engineering and Management Systems). We started organizing hybrid sessions after the COVID period and it caught interest of students from another university in Kenya ,Egerton University. Through, statistical analysis bureau of Egerton University they joined our sessions to learn how to leverage tidy models packages to create machine learning models and also collaborate with the community members.\nThey were very interested, and as future economists, we demonstrated how to build and appreciate these models. In previous meetups, we also introduced participants to Shiny apps, teaching them how to host their models and create interfaces to display their work.\nAnother valuable skill we taught was generating reports using R Markdown. This allows users to write code, format text, add videos, images, and emojis, and present their work in a professional and engaging manner. Attendees found this particularly useful as it enhanced their ability to write, structure, and report code effectively.\nParticipants learned to leverage the R ecosystem for coding, structuring their work, and reporting their findings by attending our sessions.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nA trend I’ve noticed is the widespread effort to include everyone in learning programming languages like R. This is evident in the emergence of specialized groups such as R for Medicine and R for Pharma. Two of our alumni even demonstrated how R can be used in robotics through a talk at Posit Conference 2022, demonstrating its applicability in specific industries. This specialization fascinates me, and I am eager to see how R will be used across various fields.\nAnother trend is using tools like Quarto, which facilitates the implementation of such specializations. Additionally, I am excited about the incorporation of AI in building R applications, such as using Gemini for Shiny apps. Although materials on this are currently limited, I see this as a growing trend.\nThe integration of AI will likely lead to the automation of many manual processes, further enhancing R’s utility and efficiency in various industries.\nWe would like to get to know you more personally. Can you please tell me about yourself? For example, your hobbies/interests or anything else you want to share.\nWhen not in front of my laptop, I enjoy playing baseball and softball, especially as a catcher. Catching allows me to see the entire game command the play, and I enjoy throwing the ball from home to second base and picking off a runner. It’s a challenging position that helps me focus and improve my aim.\nOn the side, I also do some graphic design using Canva which I use to create posters and newsletters for our community meetups. Additionally, I have web development skills using MERN stack.\nAnother passion of mine is teaching R to others. I love seeing people learn and apply the concepts and then go on to teach others. One of my students from his first year has now taken over as a lead in our community, which is incredibly encouraging. He even competed in hackathons and finished fourth, showing how much he has grown.\nTeaching and seeing others succeed is something I find very rewarding and motivating." + "text": "Frans van Dunné, the organizer of the San Carlos R User Group, recently discussed with the R Consortium the development of the R community in Costa Rica and the broader Latin American (LATAM) region. He also talked about the growth of events such as the ConectaR conference and the success of the Data Latam podcast, which he co-hosts to delve into data science in Latin America. Additionally, Frans highlighted the challenges of building a data-driven community in a rural area and the creative methods they’ve employed to connect people through R.\nPlease share your background and involvement with the RUGS group.\nI have a background in biology, and during my PhD in tropical ecology, I encountered some statistical questions that I needed to solve through programming. That’s when I started learning to program, initially with Perl. Eventually, I discovered that I enjoyed solving data-related problems through programming, and that led me to R. It was around 2001 when I first started programming in R.\nEventually, I married and emigrated to Costa Rica (my wife is Tica). Knowing no one in the area, I started an R User Group to connect with people and navigate the area.\nVery soon after arriving in Costa Rica, I established my town’s San Carlos R user group. Initially, we held our meetings in-person, but I soon discovered that some attendees traveled for hours by bus to reach San Carlos. Realizing the impracticality, I decided to move our meetings online, and to my surprise, it worked out well. This change occurred even before the pandemic, and we began to see people from Peru and other distant locations joining our group. San Carlos is a small rural area with a population of around 50,000, so having individuals from different parts of Latin America join us was truly amazing.\nOne of the first San Carlos R User Group meetings - February 2016, Ciudad Quesada, Costa Rica\nWe had to stop our online meetings because Meetup informed us that, according to their policy before the pandemic, we wouldn’t be able to use their platform if we didn’t hold physical meetings. The world is different now, but that was the situation back then.\nCan you share what the local R community is like in San Carlos?\nParticipants of ConectaR 2019 - January 2019, San José Costa Rica\nWe collaborated with the University of Costa Rica to organize an event that brought together industry, academia, and citizen science professionals for a conference focused on R. The event is called Conecta R. We started in 2019 and held the latest edition this year, Conecta R 2024. When we started, we wanted to understand R’s current status and usage in the LATAM region. It only confirmed that R is widely used in academia. Most statistics courses have transitioned from licensed software to R. R is also used widely in industry.\nParticipants of the Tidymodels workshop during ConectaR 2024, March 2024, San José, Costa Rica\nAt ixpantia, the company I co-founded, we work with clients in various industries, such as consumer packaged goods, retail, oil and gas, and energy production. Additionally, a significant number of clients utilize our financial services.\nWould you like to tell us about your recent events?\nWe’ve resumed our monthly online meetings for the San Carlos R user group. The meetings now take place on the first Saturday of the month in the morning, and anyone is welcome to join through Meetup.com. Our last meeting was held recently, and it was great to see familiar faces returning.\nAdditionally, we have a podcast called Data Latam, which covers topics related to data science, not just R. We aim to release a new episode every month. We run this podcast in parallel with meetings, serving a similar purpose. It’s about providing examples and even role models of professionals working with data to show that you don’t need to be an IT professional or a programmer to work with data.\nPlease share more about the Data Latam podcast. How did you come up with the idea of starting it? Would you like to highlight a few of your favorite podcasts from this series?\nThe story behind the Data Latam podcast is funny. The co-host, Diego May, and I met through an R Package I wrote to access data from an open-data platform he had developed. We shared an interest in using data and data science to help the development of LATAM and agreed to start a podcast to get to know each other better. Within two months, we had the first opportunity to start a project, and that is when we founded ixpantia, which brings best practices in data science, data engineering, and data strategy to LATAM.\nWe have done 110 podcasts to date! It seems like a lot, but we learn so much from every conversation that it hardly feels like an effort. Some of my personal favorites that are related to R include Episode 109 with Noam Ross, where we talked about rOpenSci, episode 98 with Sherly Tarazona about her work and R-Ladies Lima, episode 85 with Tareef Kawaf from Posit and episode 75 with Jorge Ahumada about the work they do at Wildlife Insights. I could go on, but pointing to the complete list at www.datalatam.com makes more sense. I’m sure there is something for everyone interested in data there.\nDo you recommend any techniques for planning for or during the event? (Github, Zoom, other.) Can these techniques be used to make your group more inclusive to people who cannot attend physical events in the future?\nOnline events are great. I live in a rural area, and attending a physical event, even here in Costa Rica, requires a long three-hour drive to the capital. We have done that and will do it again, but having the option to go online is much more practical and has a broader reach.\nWhen we started our first online meetings, we used Google Hangouts, which would fry my laptop after one hour. These tools have improved so much over the last few years, largely pushed by the boom in remote work during the pandemic. We still like Zoom and its functionality for setting up and executing events, including registration.\nParticipants of the Datathon 2019 in San Carlos, August 2019, Santa Clara, Costa Rica\nWe have organized two datathons (similar to a hackathon but focused on data) that were incredibly enjoyable and well-attended. The key to their success was our partnerships. One datathon was organized in collaboration with the Costa Rican government, and the other involved two local universities: The University of Costa Rica (UCR) and the Costa Rica Institute of Technology (TEC). I still meet people who attended these events and have fond memories of them." }, { - "objectID": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html#how-do-i-join", - "href": "posts/keith-karani-wachira-leading-the-dekut-r-community-in-kenya-and-innovating-with-r/index.html#how-do-i-join", - "title": "Keith Karani Wachira: Leading the Dekut R Community in Kenya and Innovating with R", + "objectID": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html#how-do-i-join", + "href": "posts/conectaR-podcasts-and-datathons-san-carlos-r-user-group-in-costa-rica/index.html#how-do-i-join", + "title": "ConectaR, Podcasts, and Datathons: How the San Carlos R User Group in Costa Rica is Connecting Latin America’s Data Lovers", "section": "How do I Join?", - "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more\n\n\n\ngd2md-html: xyzzy Mon Jul 29 2024" - }, - { - "objectID": "posts/the-2024-isc-grant-program-will-begin/index.html", - "href": "posts/the-2024-isc-grant-program-will-begin/index.html", - "title": "The 2024 ISC Grant Program will begin Accepting Applications Soon!", - "section": "", - "text": "The R Consortium is excited to announce the second cycle of the 2024 Infrastructure Steering Committee (ISC) Grants Program. The Call for Proposals will open soon. This initiative aims to support projects that strengthen the R ecosystem’s technical and social infrastructure. \nHere is a list of projects that received grants from the R Consortium in the First Cycle in 2024. \nFrom the Call for Proposals page:\nThe ISC is interested in projects that:\n\nAre likely to have a broad impact on the R community.\nHave a focused scope (a good example is the Simple Features for R project). If you have a larger project, consider breaking it up into smaller chunks (a good example of this done is with the DBI/DBItest project submission, where multiple proposals came in over time to address the various needs).\nHave a low-to-medium risk with a low-to-medium reward. The ISC tends not fund high-risk, high-reward projects.\n\nWhether you’re working on groundbreaking tools or organizing community-driven events, this is your chance to secure funding and make a significant impact on the R community!\nKey Dates:\n\nSeptember 1, 2024: Grant Application Period Opens\nOctober 1, 2024: Grant Application Period Closes\nNovember 1, 2024: Notification of Accepted Grantees\nDecember 1:  Deadline for acceptance of grant and contract. Public notification of grantees occurs shortly thereafter.\n\nSubmit your proposal by October 1, 2024, and contribute to the ongoing growth of the R ecosystem. Visit the R Consortium website for detailed guidelines and submission instructions. Don’t miss this opportunity to bring your innovative ideas to life!" + "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 75,492 members in 39 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nhttps://r-consortium.org/all-projects/rugsprogram.html" }, { - "objectID": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html", - "href": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html", - "title": "Full-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks", + "objectID": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html", + "href": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html", + "title": "Kolkata R User Group: A Rich History with Statistics", "section": "", - "text": "The R Consortium recently interviewed Victor Lee, organizer of the Korea R User Group, about his role establishing and expanding the Korean R community. Victor shared his journey, beginning with an introduction to R and open source programming languages while working at the Hyundai Motor Company, and later, his efforts in establishing the tidyverse community in Korea. He highlighted his extensive experience with R, including writing blog posts, publishing Quarto books, and building websites for the Korea R User Group. Victor will be a Software Carpentry instructor at the Software Carpentry Workshops at Sejong University.\nPlease share about your background and your involvement in the R Community.\nMy first introduction to our community was about 10 years ago, and it wasn’t a good experience. I used to work at the Hyundai Motor Company at that time and was intrigued by the software carpentry led by Greg Wilson. I also delved into statistics and open-source programming languages, particularly S and R programming. I was heavily involved in posting about tidyverse, which was my entry point into the community environment. In Korea, I sought out the Korean community, which mainly focused on the basics. This made me realize the need for a community in Korea based on tidyverse principles, and that’s why I started the tidyverse community in Korea 10 years ago.\nI was first introduced to S-PLUS during my undergraduate years as a statistics major, and I was fascinated by its superior graphics compared to SAS/SPSS. After majoring in computer engineering and working at Hyundai Motor Company for 10 years, I obtained a Software Carpentry Instructor certification and translated “Python for Informatics” into a Korean book. I became captivated by the Hadleyverse, and Since 2016, I have been co-organizing the Seoul R Meetup, sponsored by Kyobo DPLANEX (a continuous sponsor and is currently the largest sponsor of the Seoul R Meetup, representing one of South Korea’s leading insurance companies) alongside Choonghyun Ryu, the founder of the Korea R User Group. In 2021, we hosted the Korea R Conference, and in 2021, we established the Korea R User Group as a non-profit organization, transitioning from a community to an official organization.\nWhat is your level of experience with the R language?\nWith the support of the R community, ChatGPT, and Copilot AI, I now confidently tackle any data science problem using R. For about 10 years, I’ve consistently written blog posts using R Markdown and now Quarto. Upgrading my e-books with Bookdown led to the publication of five Quarto books on data science. Using the Quarto framework, I also built the Korea R User Group and R Conference websites. As a civic data journalist, I’ve written around 100 articles utilizing R’s visualization capabilities. Reflecting on my journey, I see how effectively I’ve applied the R language in various fields.\nWhat industry are you currently in? How do you use R in your work?\nI originally set up the Korean R community 10 years ago and am a founding member of the nonprofit Korea R User Group, established three years ago. I left KPMG to dedicate my time to running the Korea R User Group. This year, I have been fully involved in managing the organization and leading several projects, including two major abandoned projects, focusing on them for the past few months.\nCurrently, I am focusing on publishing and developing open statistical packages at a non-profit public interest corporation. In 2020, with good intentions, I started the “Open Statistical Package” project to independently develop statistical packages like SAS, SPSS, and Minitab. However, some Shiny developers without a strong background in statistics took the project in their direction, causing it to lose steam. It felt as though they had hijacked the project and the hard work the Korea R User Group put in, leaving us frustrated and disappointed.\nTo prevent this kind of thing from happening again, we’re beefing up our license policy, including trademark registration for BitStat[1]. We’re also switching up our development engines to webr and shinylive and are in the process of creating BitStat2[2].\n[1]: https://github.com/bit2r/BitStat [2]: https://github.com/bit2r/BitStat2\nWe also established a publishing company named “BitStat” as the Korea R User Group promoted Quarto digital writing as a new open source project. Recently, we have published and released five data science books, expanding the base of R users. While writing the sixth book on probability and statistics, I restarted the development of open statistical packages using Web-R and Shinylive.\nR has evolved from a simple data analysis and statistical language to a tool that can replace office software. I now use Quarto to create almost all documents, and R is the first language I use in developing the open statistical package that I am currently working on.\nWhy do industry professionals come to your user group? What is the benefit for attending?\nIn Korea, about 20 to 30 years ago, R was the number one programming language for data science and statistics, particularly in areas like machine learning. However, with the rise of Python, many R users transitioned to Python due to its increasing popularity. Despite this shift, R remains significant in Korea, with many people continuing to use both R and Python.\nFor my day-to-day work, I find R quite convenient and easy to use, especially for therapeutic data and open-source case studies. This year, I’ve noticed that users who join the Korea R User Group come from diverse backgrounds, including drug discovery, regulatory agency, and real estate.\nOver the past decade, many users joined the group to determine whether Python or R was better suited for their work. However, the recent trend clearly leans towards artificial intelligence development, such as LLM (Large Language Model) development. Participants from various industries with an interest in quantitative analysis are now attending the user group.\nTheir motivation for attending, apart from AI fields represented by LLM, is to acquire the latest technology in other data science areas and to gain knowledge from diverse, in-depth analysis experiences and model development. Additionally, many people come to obtain information about Quarto, ggplot, gt, and shiny, seeking business opportunities related to these tools.\nWhat trends do you currently see in R language and your industry? Any trends you see developing in the near future?\nThis year, our community in Korea is focusing on Quarto due to upcoming government policy changes. Analog methods are expected to disappear within five years, so the government is funding the development of AI digital textbooks. I believe Quarto technology, the next generation of R Markdown, is perfect for this purpose.\nAs generative artificial intelligence (AI) has gained significant attention in Korea, there is growing interest in using R and Python together with generative AI to solve data science problems and increase productivity, rather than focusing on the languages themselves. When using generative AI with languages such as R, Python, and SQL, it becomes necessary to find tools that can automate and store the outputs, inevitably leading to increased interest in Quarto.\nThis perspective has been reinforced by my experience using Quarto in various ways, starting from R Markdown. I have come to realize that Quarto is truly well-suited for generative AI and data science. If other countries are developing AI texts using Quarto or R Markdown, we could introduce this technology to the Korean market and the Korean government.\nHaving written five books – plus a sixth on probability and statistics – I’ve experimented with various features of Quarto books. I’ve realized we no longer need older statistical packages like SAS and SPSS. My current project involves implementing statistical software using WebAssembly (WASM) technology.\nWe would like to get to know you more personally. Can you please tell me about yourself? For example, your hobbies/interests or anything else you want to share.\nInitially, I wasn’t sure if I would succeed, but I became involved in election campaigns and grew passionate about analyzing political and election data. My interest lies in using data to uncover trends and insights from various social datasets.\nNext month, we will have a data journalism meetup, and I have friends who will join because of the articles I wrote. They will showcase some of their analyses on TV, including summaries of data related to election campaigns.\nI first developed a connection with data while majoring in statistics and then pursued computer engineering in graduate school. Although this combination of backgrounds is common now, it was unusual in Korea at the time, giving me a unique career path. My passion for open-source software and faith in the community have driven me to where I am today.\nI enjoy analyzing data, and whenever I come across interesting datasets, I analyze them and document my experiences on my blog. This hobby, along with the copyright-free nature of data, led me to develop an interest in predicting election winners using data from annual elections in South Korea. Since 2016, I have experienced three general elections, presidential elections, and local elections. Although there won’t be an election next year, I am very much looking forward to the next one." + "text": "The R Consortium recently spoke with Samrit Pramanik of the Kolkata R User Group about his experience starting a new R User Group in India. Samrit highlighted Kolkata’s rich history with statistics and talked about the diverse local R community.\nThe Kolkata R User group is organizing its second online event titled “A New Approach for Teaching Data Analytics with R” on July 13th. R users from around the world are invited to join this event.\nPlease share your background and involvement with the RUGS group.\nMy name is Samrit Pramanik. I work as a data scientist at a US-based private firm and have a post-graduate degree in statistics from the University of Calcutta. I have been using R since my post-graduate days in 2018 and used it extensively in various projects during my studies. Since 2022, I have also been an R instructor for a non-profit organization. Additionally, I have been involved in several short projects working with R. Since April 2024, I have managed the Kolkata R User group.\nThis is the third city-based R user group in India that is affiliated with the R Consortium. I plan to arrange virtual meetups monthly and in-person meetups annually. I enjoy helping and teaching people from diverse backgrounds, not only in statistics, mathematics, and data science but also in other areas. I want to teach them to use R language to add value to their professional and personal projects.\nCan you share what the R community is like in Kolkata?\nThe Kolkata User Group has been formed with a broader perspective that I would like to share with you. Kolkata is known for its reputation in statistical research and education. The city is recognized as the birthplace of modern statistics in India, with the establishment of the Indian Statistical Institute (ISI) in 1931 by a prominent figure in statistics. The University of Calcutta, where I graduated, was the first in Asia to offer a post-graduate degree in statistics in 1941. This rich history made the formation of the Kolkata R User Group inevitable. Our community consists of academics and professionals from diverse fields such as life sciences, healthcare, the public sector, physics, astrophysics, and other industries. This diverse background facilitates robust exchanges of ideas and techniques related to R and data, making our R community in Kolkata truly unique.\nPlease tell us about your recent and upcoming events?\nI would like to highlight a recent event. Last month, in June, we had our inaugural session where we introduced Quarto, a recently released reporting tool by Posit. Our goal was to make the participants aware of this tool and its outstanding features, such as website building, ebook writing, creating thesis papers, manuscripts, and blogging sites. We aimed to show participants, including early graduate students, professionals in the industry, and researchers from academia, that they can use Quarto in their projects and studies for reporting. This was our first organized session.\nThe upcoming session is scheduled for July 13th. It will focus on a new approach to teaching R to students with non-technical backgrounds such as business students. Dr. Abhimanyu Gupta from Saint Louis University will be the speaker at this event.\nWe have received very positive feedback and responses from the participants who are showing interest in the upcoming events. They want us to organize such events frequently. People are very much aware of these events and this community. They are very responsive, and we have received positive responses. Two esteemed Economics professors have expressed interest in joining our organizing team and working with us.\nPlease share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in?\nCurrently, I am working on two projects. The first project involves cricket analytics, where I extensively use R for cleaning up messy raw data and conducting exploratory data analysis at both the team and individual player levels and published a shiny dashboard on performance analysis of T20I players. I’m also building a statistical model to predict the total score of an innings, the winner of the match, and the tournament. Lastly, I aim to compile all the findings into an ebook format.\nCricket Performance Analysis Shiny Dashboard\nThe second project revolves around converting the functions and features of AstroPy, an open source software package for astronomy and astrophysics, into R. Our goal is to enhance its popularity among researchers and scientists in the astronomy, astrophysics, and cosmology domains. I am collaborating with another individual from a physics background on this open source project, and we plan to publish it on GitHub soon for public access." }, { - "objectID": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html#how-do-i-join", - "href": "posts/Full-time-Korea-R-User-Group-Founder-Victor-Lee-Sees-AI-Future-for-R-and-Quarto-Textbooks-R-Consortium/index.html#how-do-i-join", - "title": "Full-time Korea R User Group Founder Victor Lee Sees AI Future for R and Quarto Textbooks", + "objectID": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html#how-do-i-join", + "href": "posts/kolkata-r-user-group-a-rich-history-with-statistics/index.html#how-do-i-join", + "title": "Kolkata R User Group: A Rich History with Statistics", "section": "How do I Join?", "text": "How do I Join?\nR Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups organize, share information, and support each other worldwide. We have given grants over the past four years, encompassing over 68,000 members in 33 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute.\nLearn more" }, + { + "objectID": "posts/recap-r-validation-hub-community-meeting/index.html#key-insights", + "href": "posts/recap-r-validation-hub-community-meeting/index.html#key-insights", + "title": "Recap: R Validation Hub Community Meeting", + "section": "Key Insights:", + "text": "Key Insights:\n\nValidation Perspectives: The meeting underscored the need for each organization to define “validation” in a way that suits its context, while the R Validation Hub offers a baseline for common understanding.\nStatistical Methodology Challenges: Discussions acknowledged the challenges in achieving exact results across different programming languages due to inherent differences in statistical methodologies.\nOpen Source Contributions: The importance of returning testing code to package developers was highlighted, reinforcing the open-source ethos of collaboration and quality enhancement.\nResource Availability: The slides from the meeting are accessible on GitHub here. Although the meeting wasn’t recorded, the community is encouraged to join the R Validation Hub mailing list for future updates and meeting invites here." + }, + { + "objectID": "posts/recap-r-validation-hub-community-meeting/index.html#looking-forward", + "href": "posts/recap-r-validation-hub-community-meeting/index.html#looking-forward", + "title": "Recap: R Validation Hub Community Meeting", + "section": "Looking Forward:", + "text": "Looking Forward:\nThe meeting reiterated the significance of the R Validation Hub as a central point for validation discussions and resources. Future community meetings are tentatively scheduled for May 21, August 20, and November 19, offering opportunities for further engagement and contribution to the evolving conversation around R validation.\n\nJoin the R Validation Hub mailing list!" + }, { "objectID": "posts/r-ladies-goiania-promoting-diversity-and-inconclusion-in-local-r-community/index.html", "href": "posts/r-ladies-goiania-promoting-diversity-and-inconclusion-in-local-r-community/index.html", diff --git a/sitemap.xml b/sitemap.xml index ab5acbc..7515b5c 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -2,490 +2,494 @@ https://r-consortium.org/news/cal.html - 2024-10-30T17:17:29.538Z + 2024-11-01T18:56:45.346Z https://r-consortium.org/governance/isc-charter.html - 2024-10-30T17:17:29.526Z + 2024-11-01T18:56:45.334Z https://r-consortium.org/posts/r-ladies-bariloche-in-argentina-fostering-a-different-approach/index.html - 2024-10-30T17:17:29.722Z + 2024-11-01T18:56:45.526Z https://r-consortium.org/posts/building-data-highways-kirill-mullers-journey-in-enhancing-rs-database/index.html - 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