FAIR4Software reading materials

FAIR Research Software

In preparation for P15, we collected FAIR Research Software material on this deidcated page.

The session was prepared by SSC iG participants and the authors of:

Lamprecht, A.-L., Garcia, L., Kuzak, M., Martinez, C., Arcila, R., Pico, E.M.D., Angel, V.D.D., Sandt, S. van de, Ison, J., Martinez, P.A., McQuilton, P., Valencia, A., Harrow, J., Psomopoulos, F., Gelpi, J.L., Hong, N.C., Goble, C., Capella-Gutierrez, S., Groth, P., 2019. Towards FAIR principles for research software. Data Science. https://doi.org/10.3233/DS-190026

Useful links:

• The SSC IG wiki page prepared for p13 (the list is also available at the end of this page).

• The answers from the P13 activity by group on FAIR principles applied to Software Source Code.

• Anna-Lena has prepared slides that we can adapt (Nov 2019) https://drive.google.com/file/d/1sggbc67Sp6R3zbDe5fDq8x6oDqjoiUr8/view

• RDA proposal public https://www.rd-alliance.org/fair-principles-research-software

• RDA programme: https://www.rd-alliance.org/rda-15th-plenary-programme

• https://fair-software.eu/ might also be worth mentioning

• FAIR workflows (a special kind of software) are being discussed in two forthcoming workshops

  • Lorentz Workshop 9-13 March 2020 (Automated Workflow Composition in the Life Sciences), 

  • BDRI NAS Washington 16-17 March 2020. 

Related papers:

• Hettrick, S., Antonioletti, M., Carr, L., Chue Hong, N., Crouch, S., De Roure, D., Emsley, I., Goble, C., Hay, A., Inupakutika, D., Jackson, M., Nenadic, A., Parkinson, T., Parsons, M.I., Pawlik, A., Peru, G., Proeme, A., Robinson, J., Sufi, S., 2014. UK Research Software Survey 2014. https://doi.org/10.5281/zenodo.14809
• The Committee for Open Science’s Free Software, Open Source Project Group, 2019. Opportunity Note: Encouraging a wider usage of software derived from research. URL https://www.ouvrirlascience.fr/opportunity-note-encouraging-a-wider-usage-of-software-derived-from-research (accessed 2.28.20).
• Mons, B., Neylon, C., Velterop, J., Dumontier, M., da Silva Santos, L.O.B., Wilkinson, M.D., 2017. Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud. Information Services & Use 37, 49–56. https://doi.org/10.3233/ISU-170824
• Katz, D.S., Niemeyer, K.E., Smith, A.M., Anderson, W.L., Boettiger, C., Hinsen, K., Hooft, R., Hucka, M., Lee, A., Löffler, F., Pollard, T., Rios, F., 2016. Software vs. data in the context of citation (No. e2630v1). PeerJ Inc. https://doi.org/10.7287/peerj.preprints.2630v1

• From FAIR research data toward FAIR and open research software https://doi.org/10.1515/itit-2019-0040 Shared by Anna-Lena (Feb 14, 2020). Note needs to be added to workshop materials ~ abstract

• Software Citation Principles https://peerj.com/articles/cs-86/ From Dan.

• There are also FAIR discussions about special kinds of software, notably workflows. 

  • Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes, Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters and Daniel Schober, FAIR Computational Workflows, Data Intelligence, https://doi.org/10.1162/dint_a_00033

  • Tobias Weigel, Ulrich Schwardmann, Jens Klump, Sofiane Bendoukha, Robert Quick,  Making Data and Workflows Findable for Machines, Data Intelligence, Posted Online November 01, 2019, https://doi.org/10.1162/dint_a_00026

• Evaluation of the OntoSoft Ontology for describing metadata for legacy hydrologic modeling software https://www.sciencedirect.com/science/article/pii/S1364815216309999

• Pierre Alliez, Roberto Di Cosmo, Benjamin Guedj, Alain Girault, Mohand-Said Hacid, Arnaud Legrand, Nicolas Rougier. Attributing and Referencing (Research) Software: Best Practices and Outlook From Inria. Computing in Science Engineering, 22 (1), pp. 39-52, 2020, ISSN: 1558-366X. https://dx.doi.org/10.1109/MCSE.2019.2949413

• Roberto Di Cosmo, Morane Gruenpeter, Stefano Zacchiroli. Referencing Source Code Artifacts: a Separate Concern in Software Citation. Computing in Science & Engineering, 2020, ISSN:1521-9615. https://dx.doi.org/10.1109/MCSE.2019.2963148

The references and links below were collected for the Software Source Code IG P13 session on FAIR Software Source Code:

• Sustainable Software Sustainability Workshop, 2017. Does it make sense to apply the FAIR Data Principles to Software?
• At the 2017 Dealing with Data Workshop:
  • FAIR Software? How can we make easier to find, access, deposit and reuse software? Neil Chue Hong's slides
• Concrete Advice for FAIR Software by Katrin Leinweber
  • Library Carpentry report about TIB's "FAIR Data & Software" workshop (materials linked therein)
• At the 2018 Fall AGU meeting:
  • Data Fair: Sharing Your Software—What Is FAIR? session
  • FAIR enough? Can we (already) benefit from applying the FAIR Data Principles to software?
    • session
    • Neil Chue Hong's slides
  • FAIR Data Is Not Enough: Communicating Data Quality and Making Analytical Code FAIR I
    • session
    • Daniel Katz's slides

• Research Software sprint, November 2018. Translate FAIR principles to applicable actions for scientific software