The RDA FAIR for Research Software (FAIR4RS) WG recognized the importance of software as a scholarly output and the necessity to review and adapt the FAIR data guiding principles (Wilkinson et al.) to research software. This webinar will present the history of how the Working Group evolved, an overview of the recently published group output FAIR principles for Research Software, and the challenges and limitations identified when creating the principles for FAIR Research Software.
Attendees will learn about Research Software and the differences between software and data that lead the community to develop a separate set of FAIR guiding principles for Software. The webinar will be of interest to anyone using, creating, or studying software in a research context. Attendees should be familiar with the FAIR principles concept.
This webinar will start with an overview of the current activities related to software in the RDA community and in the scholarly ecosystem. An in-depth analysis of the recently published recommendations of the FAIR principles for Research Software made by the FAIR4RS WG will follow. We will also present challenges identified when creating the principles and the limitations of FAIR for Research Software. Finally, we will share our current activities and next steps, where we will invite webinar attendees to join the WG’s newly formed subgroups aimed at supporting adoption and governance.
Research software is a significant and vital component of research. It is integral to all stages of research and can play the role of a tool, a research result, or a research object. In RDA, software issues and challenges were formalized at a Birds of Feathers session at the 8th Plenary in 2017, resulting in the Software Source Code Interest Group (SSC IG). In July 2020, a new FAIR For Research Software Working Group (FAIR4RS WG) was jointly convened as a Research Data Alliance (RDA) Working Group, a FORCE11 Working Group, and a Research Software Alliance (ReSA) Taskforce, in recognition of the importance of software as a scholarly output and the necessity to review and adapt the FAIR data guiding principles (Wilikinson et al.) to research software.