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What is FAIR?

By: Sandra Gesing

In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data [1]. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. Referred to as the FAIR principles, the publication has created an energetic uptake in the research community from research domains to computational sciences and led to many projects and initiatives such as the GO FAIR initiatives all over the world in different countries.

Furthermore, people started to work on defining FAIR guidelines in more detail for different digital assets: data, software, workflows, hardware, to name a few.  While there is a large agreement in the community that FAIR is important, how to start to make the different digital assets FAIR, needs a lot of more discussions and work (see examples of around 10 interest and working groups at the Research Data Alliance (RDA) concerned with FAIR). The working group FAIR for Virtual Research Environments (FAIR for VREs) discusses the aspects for VREs aka science gateways and addresses that the different levels of science gateways make FAIR measures complex: there is the science gateway framework itself that can be FAIR, then data and tools, thus software, embedded in science gateways, can be FAIR. Science gateways instances for a community can be FAIR and they can include components such as workflow engines and external data sources. FAIR is an approach that cannot be solved with a one-fits-all approach and researchers and educators might not want all aspects of their data FAIR before publication, for example.

Good starts are some guidelines developed by GO FAIR initiatives, FAIR working groups and FAIR evaluation services such as FAIRsharing.org and FAIRshake.cloud. See here for updates on the next steps of the FAIR for VREs working group. This podcast discusses the beginning of the working group, challenges and refers to partners like SGX3 to inform the community.

We will have a series of blog posts discussing steps for making science gateways FAIR. You can read more in this series at:

 

References:

[1] Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.W., da Silva Santos, L.B., Bourne, P.E. and Bouwman, J., 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3(1), pp.1-9.