The FAIR4RS team: Working together to make research software FAIR

Daniel S. Katz, Michelle Barker, Neil P Chue Hong, Leyla Jael Garcia Castro, Paula Andrea Martinez

Research output: Contribution to conferencePaperpeer-review

Abstract / Description of output

The FAIR For Research Software Working Group (FAIR4RS WG) is leading the research software community in the crucial step of agreeing how to apply the FAIR principles to research software, including defining the principles and adoption guidelines. This group was convened under the Research Software Alliance (ReSA), the Research Data Alliance (RDA), and FORCE11 (the Future of Research Communication and Escholarship). This paper explains how the community collaboration to enable this has been built, as an example of a model for teamwork across the research software community, and which could potentially be used in other fields and domains as well, as this is an interdisciplinary and global effort
Original languageEnglish
Number of pages4
DOIs
Publication statusPublished - 8 Jun 2021
Event2021 Collegeville Workshop on Scientific Software Teams - Virtual
Duration: 20 Jul 202122 Jul 2022
https://collegeville.github.io/Workshops/Collegeville2021/

Workshop

Workshop2021 Collegeville Workshop on Scientific Software Teams
Period20/07/2122/07/22
Internet address

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  • Introducing the FAIR Principles for research software

    Barker, M., Chue Hong, N. P., Katz, D. S., Lamprecht, A-L., Martinez Ortiz, C., Psomopoulos, F., Harrow, J., Garcia Castro, L. J., Gruenpeter, M., Martinez, P. A. & Honeyman, T., 14 Oct 2022, In: Scientific Data. 9, 1, 6 p., 622.

    Research output: Contribution to journalArticlepeer-review

    Open Access
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  • FAIR Principles for Research Software (FAIR4RS Principles) 1.0

    Chue Hong, N. P., Katz, D. S. & Barker, M., 24 May 2022, Research Data Alliance Recommendations and Outputs 30 p.

    Research output: Contribution to specialist publicationArticle

    Open Access
    File
  • Towards FAIR principles for research software

    Lamprecht, A-L., Garcia, L., Kuzak, M., Martinez, C., Arcila, R., Martin, E., Dominguez De Angel, V., van de Sandt, S., Ison, J., Martinez, P. A., McQuilton, P., Valencia, A., Harrow, J., Psomopoulos, F., Gelpi, J. L., Chue Hong, N., Goble, C. & Capella-Gutierrez, S., 12 Jun 2020, In: Data Science. 3, 1, p. 37-59

    Research output: Contribution to journalArticlepeer-review

    Open Access
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