How FAIR are European data resources?

ELIXIR Netherlands, together with ELIXIR groups from the UK, Italy and Sweden, as well as the European Bioinformatics Institute in the UK (EMBL-EBI), have recently finished an implementation study investigating how FAIR European Core Data Resources are.

European data resources are fundamentally important to the field of life sciences. Core Data resources you might be familiar with as a scientist in life sciences are Array Express (genomics database), ChEMBL (a database of bioactive drug-like small molecules) and Ensembl (a genome browser), to name a few. ELIXIR is committed to Open Access as a core principle and adherence to the FAIR guidelines for these resources. The implementation study therefore investigated if and how these Core Data Resources (CDRs) follow the FAIR principles and how the FAIRness of these CDRs could be further improved.

Who is ELIXIR? ELIXIR is a community of researchers within European life science organizations who work together to improve managing and safeguarding the increasing volume of data within their own discipline. The goal is to coordinate, integrate and sustain bioinformatics resources across its member states and enable users in academia and industry to access services that are vital for their research.

What are implementation studies? Implementation Studies are short technical projects that guide future service development, drive standards adoption and connect different groups within the European-wide ELIXIR community.

Recent findings from this implementation study now confirm that the investigated CDRs have already implemented the FAIR principles to a large extent. In addition, the study formulated suggestions to further improve FAIRness of these core data resources. Subsequently, it described different evaluating approaches to measure FAIRness and created tools such as fairshake,, and

The FAIR principles are formulated as “guiding principles”, so that it can guide, rather than dictate how data is managed. And thus leaves room for the implementation of FAIR and will therefore vary between different data resources. Previously defined FAIR ‘maturity indicators’, as further matured by this study, can therefore serve as the foundation for different scientific communities to define best practices. This serves the ultimate goal of accelerating scientific discovery through data reuse.

A final report of this study in form of a research article is currently under preparation and will highlight best practices as well as challenges, when implementing the FAIR principles in data resources. Through this article the participants hope to improve the current and future data resources and possibly data repositories in general.

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