What is Fostering Fair Data Practices (FAIRsFAIR)?
FAIRsFAIR- Fostering Fair Data Practices in Europe- supports the board of the European Open Science Cloud (EOSC) with good (data) management of its services. EOSC was launched in 2016 to support the EU’s policy of Open Science. It aims to advance research data management by uniting existing and emerging European data infrastructures. Bundling data infrastructures ensures that European scientists harvest the full benefits of data-driven science. Within EOSC, FAIRsFAIR will make all knowledge, expertise, guidelines, implementations, new pathways, learning paths and training accessible. All of which are necessary to realize the FAIR principles. In this way, this long-term project will contribute to a cultural change which is urgently needed to achieve a wide acceptance of the FAIR methods within and outside the EOSC.
What is the involvement of DTL and ELIXIR-NL in FAIRsFAIR?
DTL/ELIXIR-NL focuses on the implementation of the FAIR data principles in life sciences. This is also the view that we bring into this long-term project. Within FAIRsFAIR, we therefore concentrate on:
- FAIR practices: semantics, interoperability, and services
The goal of this task is examining how the FAIR principles are used in practice. This task recently described the use of persistent identifiers (PIDs), semantics and metadata, for both life science researchers and data stewards.
- FAIR Semantics and Semantics for FAIR
This task creates best practice recommendations to improve the global FAIRness of ontologies, controlled vocabularies, subject headings, thesauri, and classifications. The output of this task are continuously updated support documents for the EOSC governance with recommendations on making semantic artefacts FAIR. Semantic artefacts are the tools which allow humans and machines to locate, access and understand (meta)data. The first version of its recommendations can be found here.
- FAIR Repositories
This task group works with existing repositories to clarify what is needed to make such repositories FAIR. In parallel they work on a prototype FAIR metadata repository system based on FAIR data points.
- FAIR Services
This task group investigates how software can fulfill the FAIR criteria and what data services (repositories and more) can do to support FAIR data.
- FAIR Data Science and Professionalisation
This task group focuses on FAIR data competences, training and education. The recently published report “Briefing on FAIR Competences and Synergies” provides an overview and analysis of different existing competence frameworks, resources and training initiatives in the field of research data management (RDM), Open Science and FAIR data. The project “Towards FAIR data steward as profession for the lifesciences” in which we worked with ZonMw and ELIXIR is also featured in this report, as are other ELIXIR training efforts. The ‘Briefing on FAIR Competences and Synergies’ report summarizes several key projects reflecting the importance and endorsement of such projects and programs within the EU.
Overall, the FAIRsFAIR outcomes lay a solid foundation on which follow-up projects can build on, to advance the implementation of the FAIR principles in all fields, including the life sciences.
