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Data is Foundational

In this brief workshop we will be discussing the basics of research data, in terms of material, transformation, and presentation. We will also be focusing on the ethics of data cleaning and representation. If the rest of the course is practical, then this is a small detour to allow us to sit and think about what we are doing. Because everyone has a different approach to data and ethics, this workshop will also include multiple sites for discussions to help us think together as a group.

What Constitutes Research Data?

"Material or information on which an argument, theory, test or hypothesis, or another research output is based." Queensland University of Technology. Manual of Procedures and Policies. Section 2.8.3. http://www.mopp.qut.edu.au/D/D_02_08.jsp

"What constitutes such data will be determined by the community of interest through the process of peer review and program management. This may include, but is not limited to: data, publications, samples, physical collections, software and models" Marieke Guy. http://www.slideshare.net/MariekeGuy/bridging-the-gap-between-researchers-and-research-data-management , #2

"Units of information created in the course of research" https://www.nsf.gov/bfa/dias/policy/dmpfaqs.jsp

"(i) Research data is defined as the recorded factual material commonly accepted in the scientific community as necessary to validate research findings, but not any of the following: preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues." OMB-110, Subpart C, section 36, (d) (i), http://www.whitehouse.gov/omb/circulars_a110/

"The short answer is that we can’t always trust empirical measures at face value: data is always biased, measurements always contain errors, systems always have confounders, and people always make assumptions." Angela Bassa. https://medium.com/@angebassa/data-alone-isnt-ground-truth-9e733079dfd4

In summary, research data is: Material or information necessary to come to your conclusion.

Forms of Data

There are many ways to represent data, just as there are many sources of data. After processing our data, we turn it into a number of products. For example:

  • Non-digital text (lab books, field notebooks)

  • Digital texts or digital copies of text

  • Spreadsheets

  • Audio

  • Video

  • Computer Aided Design/CAD

  • Statistical analysis (SPSS, SAS)

  • Databases

  • Geographic Information Systems (GIS) and spatial data

  • Digital copies of images

  • Web files

  • Scientific sample collections

  • Matlab files & 3D Models

  • Metadata & Paradata

  • Data visualizations

  • Computer code

  • Standard operating procedures and protocols

  • Protein or genetic sequences

  • Artistic products

  • Curriculum materials

  • Collection of digital objects acquired and generated during research

Adapted from: Georgia Tech–http://libguides.gatech.edu/content.php?pid=123776&sid=3067221

Discussion: Forms of Data

These are some (most!) of the shapes your research data might transform into. What are some forms of data you use in your work? What about forms of data that you produce as your output? Perhaps there are some forms that are typical of your field? Where do you usually get your data from?

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