GitHub for FAIR Data and Beyond

Description

FAIR is the first part of data management, but what comes next? To get the most value from our research data, our data should be alive, which means that the research community can contribute back with improvements. That means that we can accept contributions from others easily, and others can use and modify the data without making diverging copies. Thus, this talk proposes a “C” (for “collaborative contributions”) beyond the normal FAIR acronym. 

After some thought, in our view, the best solution to achieving the above is GitHub, which has a tagline of “Social Coding”.  What if it wasn’t limited to “coding”?

While GitHub is normally used for software or computational work, it has the potential to solve other needs of RDM: version history, attribution for each change, and, most importantly, a way for anyone to make and comment on change proposals without needing to ask for special permission first (and use their own versions, without making it impossible to merge versions again later on). Could GitHub be used also in non-computational research, in order to improve the FAIRness of academic projects in general?

This event will

• Introduce the background to the above and why GitHub could be appropriate for different kinds of non-code academic projects 
• Discuss how and what barriers there would be to using GitHub for these projects (e.g. is there a user interface that is simple and usable enough for broad use?) 
• Discussion and future planning (e.g. does anyone want to begin setting something up?) 

Who can participate?

The webinar is aimed at university staff and students who are interested in the topic. No prior knowledge of RDM is required. Some information covered in the session, such as details of Aalto’s RDM services, is relevant only to those working at Aalto. The webinar is free and open to all.

Format

A one-hour webinar including a Q&A discussion.

Schedule and location

The training will be held online via Zoom on May 9, at 2–3 PM Eastern European Time (EET).

Instructor(s)

Dr. Richard Darst, Data Agent, Staff Scientist, School of Science, Aalto University
& the Aalto Scientific Computing team (Aalto SciComp)

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