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In case of disagreement, the Freepik Terms of Use -will prevail. diff --git a/img/License premium.txt b/img/License premium.txt deleted file mode 100644 index c6cd87a..0000000 --- a/img/License premium.txt +++ /dev/null @@ -1,30 +0,0 @@ -IMPORTANT NOTICE: This license only applies if you downloaded this content as -a subscribed (or "premium") user. 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- - -Reproducible Definition - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Reproducible Definition2023-05-03CC-BY 4.0The Turing Wayscriberia, da5nsy, Richard J. Actonscriberia http://www.scriberia.co.uk/https://github.com/alan-turing-institute/the-turing-way/blob/main/book/website/figures/reproducible-definition-grid.svgEnglish (UK)reproducible; definition; replicable; generalisable; robust; data analysis; open science; open life science; the turing wayAlt Text: Grid with the characteristics of: Reproducible; same data, same analysis. Replicable; different data, same analysis. Robust; same data, different analysis. And generalisable; different data, different analysis; Research diff --git a/img/road-to-reproducibility.svg b/img/road-to-reproducibility.svg deleted file mode 100644 index 1aa5f14..0000000 --- a/img/road-to-reproducibility.svg +++ /dev/null @@ -1,676 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/img/rse_credit .jpg b/img/rse_credit .jpg deleted file mode 100644 index 7d98027..0000000 Binary files a/img/rse_credit .jpg and /dev/null differ diff --git a/img/rse_credit.jpg b/img/rse_credit.jpg deleted file mode 100644 index 0c540dc..0000000 Binary files a/img/rse_credit.jpg and /dev/null differ diff --git a/img/rse_funding_us.jpg b/img/rse_funding_us.jpg deleted file mode 100644 index d8bf8f7..0000000 Binary files a/img/rse_funding_us.jpg and /dev/null differ diff --git a/img/selecciona.png b/img/selecciona.png deleted file mode 100644 index 4e6a9dc..0000000 Binary files a/img/selecciona.png and /dev/null differ diff --git a/img/talking.png b/img/talking.png deleted file mode 100644 index ce13675..0000000 Binary files a/img/talking.png and /dev/null differ diff --git a/img/thecarpentries.png b/img/thecarpentries.png deleted file mode 100644 index d59432c..0000000 Binary files a/img/thecarpentries.png and /dev/null differ diff --git a/img/turing.png b/img/turing.png deleted file mode 100644 index 65a5d50..0000000 Binary files a/img/turing.png and /dev/null differ diff --git a/slides.html b/slides.html index 665266d..a10db96 100644 --- a/slides.html +++ b/slides.html @@ -389,7 +389,7 @@

@@ -415,12 +415,26 @@

Ramírez ML, Martinez SM, Bessone CV, Allemandi DA, Quinteros DA. COVID-19: Epidemiological situation of Argentina and its neighbor countries after three months of pandemic. Disaster Med Public Health Prep.

-
-

How do people move in the city?

+
+

Objectives 🎯

+

Create tools to map Facebook Mobility Data and monitor how decision-making affects the distribution of COVID-19 cases in the province of Buenos Aires, Argentina.

+
    +
  1. A software package to convert citizen mobility data to raster images.
    2. +
  2. A dashboard to provide a quick overview, enabling the monitoring of decisions while considering the spatial dynamics of data.
    3. +
+
+
+
+

What data can we use to analyze citizen mobility in the territory?

+ +
+
+

What data can we use to analyze citizen mobility in the territory?

+

Meta/Facebook Mobility Data is available to researchers through the Data4Good Partner Program

-
-

Meta/Facebook Mobility Data

-
+
+

+

@@ -434,12 +448,11 @@

How is the data obtained?

    -

  • Mobile devices with the Facebook app installed

    +
  • Mobile devices with a Meta app installed
      -
    • Meta/Facebook users location Latitude and Longitude at a given time.
      • +
    • Meta/Facebook users location ➡️ latitude and longitude at a given time.
    • -

  • The data is available to researchers (Data4Good Partner Program)

    • -

  • Measures applied to the data to ensure privacy and anonymity.

    • +
  • Measures applied to the data to ensure privacy and anonymity.

@@ -451,21 +464,14 @@

How is the data obtained?

Facebook Mobility Data

-

How do you convert user positions into a map?

+

What data do researchers receive?

-
    -
  • Mapped using a Bing tile architecture -
      -
    • Assigning users to individual tiles
      • -
    • -
  • Data is provided in 8-hour time periods. (Buenos Aires province (UTC-3)) -
      -
    • 0hs - 8hs.
      • -
    • 8hs - 16hs.
      • -
    • 16hs - 0hs.
      • -
    • -
+
    +

  1. Mapped using a Bing tile architecture ➡️ users are assigned to individual tiles.

    2. +

  2. Data is provided in 8-hour time periods ( 0hs - 8hs / 8hs - 16hs / 16hs - 0hs ).

    3. +

  3. Variable percent_change: relative change in mobility compared to a baseline period.

    4. +

@@ -494,47 +500,51 @@

From QuadKeys to raster images

Facebook Mobility Data

-

From QuadKeys to raster images

+

1. From a QuadKey to a simple features dataframe

-
-

Image source: quadkeyr documentation

+
+

Source: quadkeyr documentation - Conversion

-
-

COVID-19 data

-
    -
  • Historical archive of COVID-19 cases
    • -
  • Public dataset
    • -
-
-

National Directorate of Epidemiology and Health Situation Analysis

+
+

Facebook Mobility Data

+
2. Generating a Raster Image from Quadkey-Identified Data
+ +
+

Source: quadkeyr documentation - Raster creation

-
-

Objectives

-

Create tools to map Facebook Mobility Data and monitor how decision-making affects the distribution of COVID-19 cases in the province of Buenos Aires, Argentina.

-
    -
  1. A software package to convert Facebook Mobility data to raster images
    2. -
  2. A dashboard to provide a quick overview of the situation, enabling the monitoring of decisions while considering the spatial dynamics of data.
    3. -
-
+
+

Facebook Mobility Data

+

3. Converting Facebook Mobility QuadKey-identified Datasets into Raster Files

+ +
+

Source: quadkeyr documentation - Facebook Mobility Data

+
+
-
-

1. Software package

+
+

Why create a software package?

-
+

Why create a software package?

  • Makes it easier to reuse functions.
  • Improves code quality (i.g. tests, documentation).
  • Ensures computational reproducibility.
+ +
+

Image source: The Turing Way Handbook

+

-

:::footer

-

:::

+ +
+

The Turing Way Community, & Scriberia. (2020, March 3). Illustrations from the Turing Way book dashes.

+

R package: quadkeyr

@@ -545,7 +555,11 @@

R package: quadkeyr

  • GitHub repository
    • +
    +

    +
    +
    @@ -555,37 +569,45 @@

    R package: quadkeyr

    rOpenSci peer-review

    -
    -

    transparent, constructive, non adversarial and open review process

    +
    +

    Transparent, constructive, non adversarial and open review process

    -
    +
    +
    +

    +
    +

    -
    +

    JOSS article

    -
    -
    -

    Example

    -
      -
    • We were not going to see the consequences of decisions immediately.
      • -
    • Non-permitted behaviors would be possible to detect.
      • -
    -
    +
    +

    The Turing Way Community, & Scriberia. (2020, March 3). Illustrations from the Turing Way book dashes.

    +
    +
    +
    +

    + +
    +
    +

    + +

    Raster images produced with quadkeyr allow to visualize citizen mobility on a map

    @@ -598,27 +620,39 @@

    Dashboard

    GeoCovidAR

    +
    +

    Integrate city mobility information with daily reported COVID-19 cases

    +
    +
    +
    +

    +
    +
    +
    +

    Tab 1: General exploration

    -
    +

    Tab 2: Departments

    -
    +

    Tab 2

    You can download a report

    -
    -
    -

    Tab 3: Average of

    +
    +
    +

    Tab 3: Average percent change by department and COVID-19 cases

    + +
    +
    +
    +

    GeoCovidAR App integrates COVID-19 and Facebook Mobility Data

    -
    -
    -

    GeoCovidAR App integrates COVID-19 and Facebook Mobility Data

    Where lives the project data?

    @@ -629,7 +663,11 @@

    Website: GeoCovid Buenos Aires

  • WebPage
    • +
    +

    +
    +
    @@ -645,7 +683,7 @@

    Overview

    Website. - Quarto Website.

    Database. - PostgreSQL database.

    -
    +

    Conclusions

    The spatial distribution of cases and the human behavioral component are essential to understand the dynamics of transmission.

    -
    +

    Conclusions

    quadkeyr and GeoCovidAR are flexible tools adaptable to different scenarios

    -
    +

    Complete article here!

    Funding

    -
    +
    -
    +
    +
    +

    -
    -
    -

    +
    -
    -
    +
    +
    +

    +
    +
    -
    +
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +
    +

    +
    +
    -

    Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.

    +

    The contents are responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention.

    -
    -

    Who I am?

    -

    Contact

    +
    +

    Contact

    @@ -700,7 +753,7 @@

    Contact

    -

    🐦 Twitter
    +

    🐦 X/Twitter
    @cantoflor_87

    📢 Mastodon

    @florencia@techhub.social

    @@ -708,6 +761,9 @@

    Contact

    www.linkedin.com/in/florenciadandrea/

    +
    +

    Slides talk: From research software engineering to data science: how technology will impact the way we research

    +

    Thank you!

    diff --git a/slides.qmd b/slides.qmd index 13c93cf..4a0404f 100644 --- a/slides.qmd +++ b/slides.qmd @@ -81,7 +81,7 @@ that determines the emergence and persistence of zoonotic diseases. :::{.column width="60%" #vcenter} - Map how **human mobility changes in space** depending on -the decisions that were made and how that correlated with COVID-19 cases. +the quarantine and how that correlated with COVID-19 cases. - 🇦🇷 Argentina ➡️ Strict quarantine ::: @@ -116,21 +116,32 @@ Health Prep.](https://doi.org/10.1017/ dmp.2021.90.) ::: +## Objectives 🎯 +Create tools to **map Facebook Mobility Data** and monitor how decision-making +affects the **distribution of COVID-19 cases** in the province of Buenos Aires, Argentina. + +1. A **software package** to convert citizen mobility data to raster images. +2. A **dashboard** to provide a quick overview, +enabling the monitoring of decisions while considering the spatial dynamics of data. +# What data can we use to analyze citizen mobility in the territory? -## How do people move in the city? +## What data can we use to analyze citizen mobility in the territory? + +Meta/Facebook Mobility Data is available to researchers through the **Data4Good** Partner Program ::::{.columns} -:::{.column width="70%" #vcenter} -Meta/Facebook Mobility Data +:::{.column width="80%" #vcenter} + +![](img/meta_webpage.png) ::: -:::{.column width="30%" #vcenter} +:::{.column width="20%" #vcenter} ![](img/metalogo.png) ::: :::: @@ -145,13 +156,11 @@ Meta/Facebook Mobility Data ::::{.columns} :::{.column width="70%" #vcenter} -- Mobile devices with the Facebook app installed - - Meta/Facebook users location - **Latitude and Longitude at a given time**. +- Mobile devices with a Meta app installed + - Meta/Facebook users location ➡️ + **latitude and longitude at a given time**. -- The data is available to researchers (**Data4Good** Partner Program) - - Measures applied to the data to ensure **privacy and anonymity**. @@ -170,20 +179,17 @@ Meta/Facebook Mobility Data ::: ## Facebook Mobility Data -#### How do you convert user positions into a map? +#### What data do researchers receive? ::::{.columns} :::{.column width="60%" #vcenter} -- Mapped using a **Bing tile architecture** - - Assigning users to individual tiles +1. Mapped using a **Bing tile architecture** ➡️ users are assigned to individual tiles. + +2. Data is provided in **8-hour time periods** ( 0hs - 8hs / 8hs - 16hs / 16hs - 0hs ). -- Data is provided in 8-hour time periods. -(Buenos Aires province (UTC-3)) - - 0hs - 8hs. - - 8hs - 16hs. - - 16hs - 0hs. +3. Variable `percent_change`: relative change in mobility compared to a baseline period. ::: @@ -226,36 +232,32 @@ spatial position as a sequence of characters. [`quadkeyr` documentation](https://docs.ropensci.org/quadkeyr/) ::: - - ## Facebook Mobility Data -#### From QuadKeys to raster images -![](img/workflow_facebook.png){fig-align="center"} +#### 1. From a QuadKey to a `simple features` dataframe +![](img/workflow_quadkey.png){fig-align="center"} :::footer -Image source: [`quadkeyr` documentation](https://docs.ropensci.org/quadkeyr/) +Source: [`quadkeyr` documentation - Conversion](https://docs.ropensci.org/quadkeyr/articles/quadkey_to_sf_conversion.html) ::: -## COVID-19 data - +## Facebook Mobility Data +###### 2. Generating a Raster Image from Quadkey-Identified Data +![](img/workflow_raster.png){fig-align="center"} -- Historical archive of COVID-19 cases -- Public dataset :::footer -National Directorate of Epidemiology and Health Situation Analysis -::: - -## Objectives +Source: [`quadkeyr` documentation - Raster creation](https://docs.ropensci.org/quadkeyr/articles/quadkey_identified_data_to_raster.html) +::: -Create tools to **map Facebook Mobility Data** and monitor how decision-making -affects the **distribution of COVID-19 cases** in the province of Buenos Aires, Argentina. +## Facebook Mobility Data +#### 3. Converting Facebook Mobility QuadKey-identified Datasets into Raster Files +![](img/workflow_facebook.png){fig-align="center"} -1. A software package to convert Facebook Mobility data to raster images -2. A dashboard to provide a **quick overview of the situation**, -enabling the monitoring of decisions while considering the spatial dynamics of data. +:::footer +Source: [`quadkeyr` documentation - Facebook Mobility Data](https://docs.ropensci.org/quadkeyr/articles/facebook_mobility_csvs_to_raster_files.html) +::: -# 1. Software package +# Why create a software package? ## Why create a software package? @@ -263,11 +265,18 @@ enabling the monitoring of decisions while considering the spatial dynamics of d - Improves code quality (i.g. tests, documentation). - Ensures computational reproducibility. -## +![](img/reasons-reproducibility.png){fig-align="center"} -![](img/CultureShift.jpg) :::footer +Image source: [The Turing Way Handbook](https://book.the-turing-way.org/index.html) +::: +## + +![](img/openresearch.jpg){fig-align="center"} + +:::footer +[The Turing Way Community, & Scriberia. (2020, March 3). Illustrations from the Turing Way book dashes.](http://doi.org/10.5281/zenodo.3695300) ::: ## R package: `quadkeyr` @@ -281,7 +290,7 @@ enabling the monitoring of decisions while considering the spatial dynamics of d ::: :::{.column width="30%" #vcenter} -![](img/logo.png) +![](img/logo.png){fig-align="center"} ::: ::: @@ -293,8 +302,8 @@ D'Andrea F, Fernandez P (2024). quadkeyr: Tools for converting QuadKey-identifie ## rOpenSci peer-review ::::{.columns} -:::{.column width="70%"} -**transparent, constructive, non adversarial and open review process** +:::{.column width="60%"} +**Transparent, constructive, non adversarial and open review process** - [rOpenSci webpage](https://ropensci.org/software-review/) @@ -302,15 +311,15 @@ D'Andrea F, Fernandez P (2024). quadkeyr: Tools for converting QuadKey-identifie ::: -:::{.column width="30%"} -![](img/ropensci.svg) +:::{.column width="40%"} +![](img/ropensci.svg){fig-align="center"} ::: :::: ## -![](img/quadkeyr_joss.png) +![](img/quadkeyr_joss.png){fig-align="center"} ::: footer [`JOSS` article](https://joss.theoj.org/papers/10.21105/joss.06500) @@ -318,15 +327,21 @@ D'Andrea F, Fernandez P (2024). quadkeyr: Tools for converting QuadKey-identifie ## -![](img/recognition.png) +![](img/recognition.png){fig-align="center"} + +:::footer +[The Turing Way Community, & Scriberia. (2020, March 3). Illustrations from the Turing Way book dashes.](http://doi.org/10.5281/zenodo.3695300) +::: + +## +![](img/raster1.png){fig-align="center"} -## Example -- We were not going to see the consequences of decisions immediately. -- Non-permitted behaviors would be possible to detect. +## +![](img/raster2.png){fig-align="center"} # Raster images produced with `quadkeyr` allow to visualize citizen mobility on a map {background-color="#E5E4E2"} @@ -335,26 +350,39 @@ D'Andrea F, Fernandez P (2024). quadkeyr: Tools for converting QuadKey-identifie ## GeoCovidAR +:::: {.columns} +:::{.column width="70%" #vcenter} + Integrate city mobility information with daily reported COVID-19 cases + +::: + +:::{.column width="30%" #vcenter} +![](img/geocovid_logo.png){fig-align="center"} + + +::: +:::: + ## Tab 1: General exploration -![](img/tab1.png) +![](img/tab1.png){fig-align="center"} ## Tab 2: Departments -![](img/tab2.png) +![](img/tab2.png){fig-align="center"} ## Tab 2 You can download a report -![](img/report.png) +![](img/report.png){fig-align="center"} -## Tab 3: Average of +## Tab 3: Average percent change by department and COVID-19 cases ![](img/tab3.png) -## GeoCovidAR App integrates COVID-19 and Facebook Mobility Data {background-color="#E5E4E2"} +# `GeoCovidAR` App integrates COVID-19 and Facebook Mobility Data {background-color="#E5E4E2"} ## Where lives the project data? @@ -370,7 +398,7 @@ You can download a report ::: :::{.column width="30%" #vcenter} -![](img/geocovid_bsas_logo.png) +![](img/geocovid_bsas_logo.png){fig-align="center"} ::: ::: @@ -393,7 +421,7 @@ You can download a report -## Conclusions {background-image="img/first_slide.png" background-size="100px" background-position='right'} +## Conclusions {background-image="img/first_slide.png" background-size="80px" background-position='right'} The spatial distribution of cases and the human behavioral component are essential to understand the dynamics of transmission. @@ -403,11 +431,11 @@ are essential to understand the dynamics of transmission. with the complexity of human behavior. -## Conclusions {background-image="img/first_slide.png" background-size="100px" background-position='right'} +## Conclusions {background-image="img/first_slide.png" background-size="80px" background-position='right' } `quadkeyr` and `GeoCovidAR` are flexible tools adaptable to different scenarios -![](img/dengue.png) +![](img/dengue.png){fig-align="center"} :::footer @@ -418,28 +446,29 @@ with the complexity of human behavior. ## Funding -:::{layout-ncol=2} +:::{layout-ncol=2 #vcenter} -![](img/midas.jpg){width=200} +![](img/midas.jpg){width=200 fig-align="center"} -![](img/wsu-logo.png){width=300} -![](img/cdc.jpg){width=250} +![](img/cdc.jpg){width=250 fig-align="center"} -![](img/foresite.jpg){width=300} + +![](img/foresite.jpg){width=300 fig-align="center"} + +![](img/wsu-logo.png){width=300 fig-align="center"} + ::: :::footer -Its contents are solely the responsibility of the authors +The contents are responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. ::: -## Who I am? - -#### Contact +## Contact :::: {.columns} :::{.column width="40%" #vcenter} @@ -450,7 +479,7 @@ knitr::include_graphics("https://res.cloudinary.com/flor/image/upload/w_1000,ar_ ::: :::{.column width="60%" #vcenter} -🐦 **Twitter** +🐦 **X/Twitter** [@cantoflor_87](http://twitter.com/cantoflor_87)
    📢 **Mastodon** @@ -464,6 +493,10 @@ knitr::include_graphics("https://res.cloudinary.com/flor/image/upload/w_1000,ar_ ::: :::: +:::footer +Slides talk: [From research software engineering to data science: how technology will impact the way we research](https://flor14.github.io/wsu-dandrea/slides.html#/title-slide) +::: + # Thank you! :::footer