D7.4 How to be FAIR with your data. A teaching and training handbook for higher education institutions

Engelhardt, Claudia; Biernacka, Katarzyna; Coffey, Aoife; Cornet, Ronald; Danciu, Alina; Demchenko, Yuri; Downes, Stephen; Erdmann, Christopher; Garbuglia, Federica; Germer, Kerstin; Helbig, Kerstin; Hellström, M.; Hettne, Kristina; Hibbert, Dawn; Jetten, Mijke; Karimova, Yulia; Hansen, Karsten Kryger; Kuusniemi, Mari Elisa; Letizia, Viviana; McCutcheon, Valerie; McGillivray, Barbara; Ostrop, Jenny; Petersen, Britta; Petrus, Ana; Reichmann, Stefan; Rettberg, Najla; Reverté, Carmen; Rochlin, Nick; Saenen, Bregt; Schmidt, Birgit; Scholten, Jolien; Shanahan, H. P.; Straube, Armin; Eynden, Veerle Van den; Vandendorpe, Justine; Venkataram, Shanmugasundaram; Wiljes, Cord; Wuttke, Ulrike; Yeomans, Joanne; Zhou, Biru

doi:10.5281/zenodo.6674301

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“…This means that FAIR is not the destination, but it is a continuum, a journey 4 , and each path to FAIRness can follow a different route. Also, there is a large body of generic FAIR guidance, which is high level and domain agnostic 5 , 6 , but lacking practical examples on “how to” for different data types and scenarios. Coupled with a digital skills shortage and talent gap to be filled, in all sectors, especially around research data stewardship, these factors make it difficult to confidently devise methods that will ensure data will be FAIR.…”

Section: Introductionmentioning

confidence: 99%

The FAIR Cookbook - the essential resource for and by FAIR doers

Rocca-Serra,

Gu,

Ioannidis

et al. 2023

Sci Data

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The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for “FAIR doers” in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes.

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Section: Introductionmentioning

confidence: 99%