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Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST) Cover

Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)

Open Access
|Sep 2023

References

  1. AAAI Conference. 2022. Reproducibility Checklist, 22 February–1 March 2022. Available at https://aaai.org/Conferences/AAAI-22/reproducibility-checklist/ [Last accessed 9 December 2022].
  2. Argos. Plan and follow your data. Available at https://argos.openaire.eu/ [Last accessed 9 December 2022].
  3. Beck, K, Beedle, M, Van Bennekum, A, Cockburn, A, Cunningham, W, Fowler, M, Grenning, J, Highsmith, J, Hunt, A, Jeffries, R and Kern, J. 2001. Manifesto for agile software development.
  4. Bloemers, M and Montesanti, A. 2020. The FAIR funding model: providing a framework for research funders to drive the transition toward FAIR data management and stewardship practices. Data Intelligence, 2(1–2): 171180. DOI: 10.1162/dint_a_00039
  5. Carroll, SR, et al. 2020. The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1): 43. DOI: 10.5334/dsj-2020-043
  6. Coakley, K. 2022. FAIR Matrix Survey API. Available at https://github.com/kevincoakley/fair-matrix-survey-api [Last accessed 15 December 2022].
  7. CODATA-RDA-DataScienceSchools/Materials. Available at https://github.com/CODATA-RDA-DataScienceSchools/Materials/blob/master/docs/DataAtlanta2022/index.md [Last accessed 9 December 2022].
  8. CODATA-RDA Schools of Research Data Science. Available at https://www.datascienceschools.org/ [Last accessed 9 December 2022].
  9. Council of Data Facilities: Geoscience Research. Available at https://www.earthcube.org/council-of-data-facilities [Last accessed 9 December 2022].
  10. De Lima, RA, Phillips, OL, Duque, A, Tello, JS, Davies, SJ, de Oliveira, AA, Muller, S, Honorio Coronado, EN, Vilanova, E, Cuni-Sanchez, A and Baker, TR. 2022. Making forest data fair and open. Nature Ecology & Evolution, 6(6): 656658. DOI: 10.1038/s41559-022-01738-7
  11. De Smedt, K, Koureas, D and Wittenburg, P. 2020. FAIR digital objects for science: From data pieces to actionable knowledge units. Publications, 8(2): 21. DOI: 10.3390/publications8020021
  12. FAIR Connect. Available at https://fairconnect.pro/ [Last accessed 9 December 2022].
  13. Fecher, B and Friesike, S. 2014. Open science: one term, five schools of thought. Opening science, 1747. DOI: 10.1007/978-3-319-00026-8_2
  14. FIP Wizard. Available at https://fip-wizard.ds-wizard.org/ [Last accessed 9 December 2022].
  15. FIP Wizard Documentation. Available at https://fip-wizard.readthedocs.io/en/latest/ [Last accessed 9 December 2022].
  16. Gundersen, OE and Kjensmo, S. 2018. State of the Art: Reproducibility in Artificial Intelligence. Thirty-Second AAAI Conference on Artificial Intelligence, 32(1). DOI: 10.1609/aaai.v32i1.11503
  17. Gundersen, OE, Coakley, K and Kirkpatrick, C. 2022. Sources of Irreproducibility in Machine Learning: A Review. arXiv preprint arXiv:2204.07610.
  18. Jablonka, KM, Patiny, L and Smit, B. 2022. Making the collective knowledge of chemistry open and machine actionable. Nature Chemistry, 14(4): 365376. DOI: 10.1038/s41557-022-00910-7
  19. Kirkpatrick, CR, Coakley, K, Schreiber, L, Christopher, J, Katz, D, Stocks, K and Rao, YD. 2022. FARR: FAIR in ML, AI Readiness, & Reproducibility Network Postcard. Available in San Diego Supercomputer Center (SDSC) Research Data Services Materials Collection. UC San Diego Library Digital Collections. DOI: 10.6075/J0X92BG3
  20. Law, A. 2022. Fair Implementation Profiles (FIPs) In WorldFAIR: What Have We Learnt? Available at https://worldfair-project.eu/2022/09/30/fips-in-worldfair-what-have-we-learnt-public-workshop-tue-25-october/ [Last accessed 9 December 2022].
  21. LibGuides: Research Data Management: FAIR data. Available at https://ufs.libguides.com/rdm/fair [Last accessed 9 December 2022].
  22. Magnetics Information Consortium (MagIC). Available at https://www2.earthref.org/MagIC/about [Last accessed 9 December 2022].
  23. McCormick, M. 2012. Waterfall vs. Agile methodology. MPCS, N/A, 3.
  24. Miksa, T, Walk, P and Neish, P. 2020. RDA DMP Common Standard for Machine-actionable Data Management Plans (Version 1.1) [Computer software]. DOI: 10.15497/rda00039
  25. National Institutes of Health. 2020. Final NIH Policy for Data Management and Sharing, 29 October 2020. Available at https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html [Last accessed 9 December 2022].
  26. Nicholson, C, Kansa, S, Gupta, N and Fernandez, R. 2023. Will It Ever Be FAIR?: Making Archaeological Data Findable, Accessible, Interoperable, and Reusable. Advances in Archaeological Practice, 11(1): 6375. DOI: 10.1017/aap.2022.40
  27. NSF HSI National STEM Resource Hub: Grantsmanship – Training and Resources. Available at https://hsistemhub.org/grantsmanship/ [Last accessed 9 December 2022].
  28. Praetzellis, M and Riley, B. 2019. California Digital Library: DMPTool, 8 November 2019. https://cdlib.org/services/uc3/dmptool/ [Last accessed 9 December 2022].
  29. Qualtrics XM – Experience Management Software. Available at https://www.qualtrics.com/ [Last accessed 9 December 2022].
  30. Schultes, E and Wittenburg, P. 2019. FAIR Principles and Digital Objects: Accelerating convergence on a data infrastructure. Data Analytics and Management in Data Intensive Domains: 20th International Conference, DAMDID/RCDL 2018, Moscow, Russia, October 9–12, 2018, Revised Selected Papers 20 (pp. 316). DOI: 10.1007/978-3-030-23584-0_1
  31. Sureshchandra, K and Shrinivasavadhani, J. 2008 Moving from waterfall to agile. Agile 2008 conference: 97101. IEEE. DOI: 10.1109/Agile.2008.49
  32. Vita, R, Overton, JA, Mungall, CJ, Sette, A and Peters, B. 2018. FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability. Database, 2018. DOI: 10.1093/database/bax105
  33. Wallis, JC and Borgman, CL. 2011. Who is responsible for data? An exploratory study of data authorship, ownership, and responsibility. Proceedings of the American Society for Information Science and Technology, 48(1): 110. DOI: 10.1002/meet.2011.14504801188
  34. Wilkinson, MD, et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1): 160018. DOI: 10.1038/sdata.2016.18
  35. WorldFAIR. Available at https://worldfair-project.eu/ [Last accessed 9 December 2022].
Language: English
Submitted on: Dec 16, 2022
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Accepted on: May 25, 2023
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Published on: Sep 6, 2023
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Christine R. Kirkpatrick, Kevin Coakley, Julianne Christopher, Inês Dutra, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.