In the year 2016 the FAIR principles for scientific data management and stewardship were published.((Wilkinson et al., 2016.)) For some time now, there have been efforts not only to apply these principles to research data, but also to use them for software. This shows that FAIR is not only relevant for data, but is a cross-cutting issue within many fields of science.
FAIR4RS
As central, worldwide initiative, a working group “FAIR for Research Software (FAIR4RS)“ came together for this purpose in 2021. This group is at the same time a RDA Working Group, FORCE11 working group, and Research Software Alliance (ReSA) task force.((Hong et al., 2021, p. 2.))
In June 2021 the members of this group published a first draft of FAIR principles for research software.((Hong et al., 2021. See also Katz et al., 2021.)) This document was particularly concerned with which principles can be adopted directly and which in turn require adaptation or extension in terms of software. In particular, this concerns the aspects of executability, continuous evolution and the versioning of research software.
All publications by the working group are accessible via Zenodo Community. And their forthcoming events plus an event archive is available via their working group website.
Get your Research Software FAIR
If you like to start right away, these five recommendations by the Netherland eScience Center and DANS to make your software FAIR can help you very much: https://fair-software.nl.
You Need Help?
As an MPG scientist, it is always best to contact your local IT team first, if you have any questions. Their colleagues are competent and can give you helpful advice on software . If you have any further questions about the FAIR principles for research software, please do not hesitate to contact our RDM support team.
Further Reading
Hasselbring, W., Carr, L., Hettrick, S., Packer, H., & Tiropanis, T. (2019). FAIR and Open Computer Science Research Software. http://arxiv.org/abs/1908.05986.
Hasselbring, W., Carr, L., Hettrick, S., Packer, H., & Tiropanis, T. (2020). From FAIR research data toward FAIR and open research software. It – Information Technology, 62(1), 39–47. https://doi.org/10.1515/itit-2019-0040.
Hong, N. P. C. et al. (2021). FAIR Principles for Research Software (FAIR4RS Principles). https://www.rd-alliance.org/system/files/FAIR4RS_Principles_v0.3_RDA-RFC.pdf.
Katz, D. S., Barker, M., Chue Hong, N. P., Castro, L. J., & Martinez, P. A. (2021, June 28). The FAIR4RS team: Working together to make research software FAIR. 2021 Collegeville Workshop on Scientific Software. https://doi.org/10.5281/zenodo.5037157.
Katz, D. S., Gruenpeter, M., & Honeyman, T. (2021). Taking a fresh look at FAIR for research software. Patterns, 2(3), 100222. https://doi.org/10.1016/j.patter.2021.100222.
Wilkinson, M. D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 160018. https://doi.org/10.1038/sdata.2016.18.