Building federated FAIR Data Spaces

Yann Le Franc

eScience Data Factory, France

Bio

Dr. Yann Le Franc is the CEO and Scientific Director of e‐Science Data Factory S.A.SU. Created in 2014, e-Science Data Factory is a French R&D company aiming at proposing innovative solutions for data management to accelerate growth and progress. The company leverages its participation into European Research Infrastructure projects to provide cutting-edge services and develop innovative data management tools and architectures.

Yann Le Franc has a PhD in Neurosciences and Pharmacology in 2004. After a postdoctoral experience in the US, he worked on data management projects for Neurosciences in the context of the International Neuroinformatics Coordinating Facility (INCF) where he developed a strong expertise in ontology design and semantic web technologies. He then contributed to several Research Infrastructure projects (EUDAT, EOSC-Hub,…) as an expert on Semantic Web and ontology design.

He is the co‐chairman of the Research Data Alliance Vocabulary and Semantic Service Interest Group and is now actively involved in the FAIRification and standardization of semantic artefacts in the context of FAIRsFAIR and OntoCommons projects. In parallel, he is the technical manager of the EOSC‐Pillar project as contractor for the French National Computing Center for Higher Education (CINES).

Abstract

Building federated FAIR Data Spaces

FAIR principles (Wilkinson et al., 2016) are offering a set of generic principles supporting better research data management and data stewardship to improve Findability, Accessibility, Interoperability and Reusability of research data. Despite the international consensus around these principles a lot of practical questions still remain regarding their implementation in practice. This presentation introduces innovations proposed by EOSC related projects mainly EOSC-Pillar[1] and FAIRsFAIR[2]. These two projects are addressing the following specific questions: how can we build a service architecture that would support the aggregation and FAIRification of distributed and heterogeneous data resources? How can we make semantic artefacts FAIR to leverage the wealth of existing semantic artefacts to improve FAIRness of data?

In particular, we will present the federated FAIR Data Space service architecture currently developed in the context of EOSC Pillar. This architecture leverages and integrates existing services supporting FAIRification developed in the context of other project such as FAIRsFAIR, EOSC-Hub[3] or proposed by the GOFAIR initiative[4]. We will briefly discuss the ongoing effort in FAIRsFAIR to build recommendations for FAIR Semantics which aims at providing a common framework to build a harmonized semantic space available to enrich data content and how it will be integrated in the context of the federated FAIR Data Space.

[1] https://www.eosc-pillar.eu/

[2] https://www.fairsfair.eu/

[3] https://www.eosc-hub.eu/

[4] https://www.go-fair.org/

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