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News:

May 24th, 2022. The RDA Council have endorsed the FAIR4RS Principles as an official output!

Citation and download: Chue Hong, N. P., Katz, D. S., Barker, M., Lamprecht, A-L, Martinez, C., Psomopoulos, F. E., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., Honeyman, T., et al. (2022). FAIR Principles for Research Software version 1.0. (FAIR4RS Principles v1.0). Research Data Alliance. DOI: https://doi.org/10.15497/RDA00068


This Working Group is complete! Thanks for your contributions!!!

The RDA Software Source Code Interest Group is the maintenance home for the principles. Concerns or queries about the principles can be raised at RDA plenary events organised by the SSC IG, where there may be opportunities for adopters to report back on progress.


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All this information is detailed on the community engagement channels page

 


Webinar - FAIR Principles for Research Software (FAIR4RS WG) - 23 September 2021

 

One of the major challenges of data-driven research is to facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of data and their associated research objects, e.g., algorithms, software, and workflows. To address this, an initial effort to define a "DATA FAIRPORT" [1] began in 2014 at the Lorentz workshop and transitioned into developing a set of FAIR data Guiding Principles in 2016. The details of the FAIR data principles [2] strongly contribute to addressing this challenge with regard to research data, and the principles, at a high level, are intended to apply to all research objects; both those used in research and that form the outputs of research. Here we focus on the adaptation and adoption of the FAIR principles for the case of research software.

 

Software has become essential for research. To improve the findability, accessibility, interoperability, and reuse of research software [3] , it is desirable to develop and apply a set of  FAIR Guiding Principles for software. Many of the high-level FAIR data principles can be directly applied to research software by treating software and data as similar digital research objects. However, specific characteristics of software — such as its executability, composite nature, and continuous evolution and versioning — make it necessary to revise and extend the original data principles.

 

Application of the FAIR principles to software will continue to advance the aims of the open science movement. The FAIR For Research Software Working Group (FAIR4RS WG) will be jointly convened as an RDA Working Group, FORCE11 Working Group, and Research Software Alliance (ReSA) Taskforce, in recognition of the importance of this work for the advancement of the research sector. FAIR4RS WG will enable coordination of a range of existing community-led discussions on how to define and effectively apply FAIR principles to research software, to achieve adoption of these principles.

 

The working group will deliver:

  • A document developed with community support defining FAIR principles for research software
  • A document providing guidelines on how to apply the FAIR principles for research software (based on existing frameworks)
  • A document summarising the definition of the FAIR principles for research software, implementation guidelines and adoption examples.

Current and upcoming activities:

  • Our first recommendation outcome is currently under review.

  • Three new subgroups focused on adoption will run from September - December 2021
  • Finalizing Working Group Outputs from January- March 2022

Past subgroup activities from 2020-2021

  1. 1 See also DTL, 2014; and Kok, 2014.
  2. 2 See also Wilkinson et al., 2016.
  3. 3 For further information refer to Clément-Fontaine et al., 2019.

The time and work of co-chairs MB and PAM is partially supported by the Alfred P. Sloan Foundation grant G-2021-14116 and Wellcome Trust grant 222436/Z/21/Z. NCH’s time is supported by the UKRI research councils through grant EP/S021779/1.