Resources

This page will bring together resources produced by the project. These will be added throughout the project, when each has been completed. Here are some of the expected resources and when they are due:

June 2019

  • Draft BYOD guidelines (alpha version)

December 2019

  • Draft FAIR cookbook (alpha version)
  • FAIRplus handbook
  • Selection criteria and guidelines for data sources
  • Report on IMI projects for data types

December 2020

  • Annual update of the FAIRplus Handbook including KPIs
  • IMI FAIR data catalogue
  • Sustainability plan

December 2021

  • FAIR Cookbook
  • Annual update of the FAIRplus Handbook including KPIs
  • BYOD guidelines
  • Technical feasibility report
  • FAIRification guidance tool for IMI
  • Use case dissemination package

For more information about the project and the context of these resources, see About the project.

FAIR data in life science research: Essential reading

The FAIRplus Squad teams have compiled a list of publications and papers on FAIR data in biomedical domains. The list includes the recent developments in implementing FAIR principles in biomedical research as well as case studies on the impact and benefits of FAIR data.

  • Madduri R, Chard K, D'Arcy M, et al. Reproducible big data science: A case study in continuous FAIRness. PLoS One. 2019;14(4) e0213013. Published 2019 Apr 11. doi:10.1371/journal.pone.0213013
  • Babic Z, Capes-Davis A, Martone ME, et al. Incidences of problematic cell lines are lower in papers that use RRIDs to identify cell lines. Elife. 2019;8:e41676. Published 2019 Jan 29. doi:10.7554/eLife.41676
  • Wise J, Grebe de Barron A, Splendiani A, et al. Implementation and relevance of FAIR data principles in biopharmaceutical R&D. Drug Discovery Today. 2019;4:933-938. Published 2019 Jan 25. doi:10.1016/j.drudis.2019.01.008
  • Jansen P, van den Berg L, van Overveld P, et al. Research Data Stewardship for Healthcare Professionals. 2018 Dec 22. In: Kubben P, Dumontier M, Dekker A, editors. Fundamentals of Clinical Data Science. Cham (CH): Springer; 2019. Chapter 4. doi:10.1007/978-3-319-99713-1_4
  • Holub P, Kohlmayer F, Prasser F, et al. Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health. Biopreservation and Biobanking. 2018;16(2). Published 2018 Apr 1. doi:10.1089/bio.2017.0110
  • Corpas M, Kovalevskaya NV, McMurray A, et al. A FAIR guide for data providers to maximise sharing of human genomic data. PLoS Comput Biol. 2018;14(3):e1005873. doi:10.1371/journal.pcbi.1005873
  • Wilkinson MD, Sansone SA, Schultes E, et al. A design framework and exemplar metrics for FAIRness. Scientific Data. 2018;5:180118. Published 2018 Jun 26. doi:10.1038/sdata.2018.118
  • Figueiredo AS, Data Sharing: Convert Challenges into Opportunities. Front. Public Health. 2017;5:327. Published 2017 Dec 4. doi:10.3389/fpubh.2017.00327
  • Wilkinson MD, Verborgh R, Bonino da Silva Santos LO, et al. Interoperability and FAIRness through a novel combination of Web technologies. PeerJ Computer Science 2017;3:e110. Published 2017 Apr 24. doi:10.7717/peerj-cs.110
  • Wolstencroft K, Krebs O, Snoep JL, et al. FAIRDOMHub: a repository and collaboration environment for sharing systems biology research Nucleic Acids Research. 2017;45(D1):D404–D407. Published 2016 Nov 24, doi:10.1093/nar/gkw1032
  • Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 2016;3:160018. Published 2016 Mar 15. doi:10.1038/sdata.2016.18