||22 March 2019, 14:00 UTC - 15:00 CET
Maggie Hellström (GEDE, ICOS), Erik Schultes (GOFAIR), Mark Wilkinson (GOFAIR), Ingrid Dillo (FAIRsFAIR, CTS), Edit Herczog (GEDE, RDA)
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The FAIR principles are being accepted widely in the scientific community now as a pre-condition for making data driven science more efficient. Consequently, various initiatives are busy to identify what machine-actionable FAIRness functionally means and how levels of FAIRness can be objectively and reproducibly assessed. Given the huge amount of data it is also becoming obvious that tools are required that measure FAIRness automatically.
Assessing trustworthiness of repositories based on a set of requirements has also been widely accepted. Two years ago two catalogues of requirements, the Data Seal of Approval and the World Data System1, have been merged into the CoreTrustSeal. The success of the CoreTrustSeal acknowledges the fact that repositories are and will continue to be essential pillars in the evolving ecosystem of data infrastructures and thus users and depositors need to rely on the quality and sustainability of their services. While FAIR addresses the data and metadata characteristics of any Digital Object, CoreTrustSeal has its focus on the repositories as care takers of data and metadata. The foci of the two initiatives therefore are slightly different although when comparing both also quite some overlap can be identified.
Recent discussions in meetings demonstrated that many data scientists take a cautionary approach to automated FAIRness measurement. In particular they are, a) afraid that they are confronted with rule sets where they did not have a chance to influence them, b) afraid of institutions that declare themselves as assessment experts and make statements that may have effects on funding decisions without understanding data practices and c) do not understand the reason to have yet another set of rules. Discussions were partly emotional about terms such as FAIR “metrics” so that people now prefer to speak about FAIR Maturity Indicators. But does this now mean that people can go ahead as they did during the past years?
Many questions are still unclear to the many data professionals related with large research/data infrastructures such as the ESFRI ERICs and projects. This webinar therefore is an excellent opportunity to listen first to one of the designers behind the FAIR principles and first simple criteria for FAIRness (Erik Schultes), to a colleague who already is working on suggestions of how to automate measuring FAIRness (Mark Wilkinson) and of a colleague responsible involved in CoreTrustSeal and now also in the new FAIRsFAIR project of the EC (Ingrid Dillo). In addition, Edit Herczog will briefly explain what the task of the FAIR Maturity Working Group within RDA will be. We will leave sufficient time for questions and discussions and are happy that data practitioners from ICOS (Maggie Hellström) and VAMDC (Carlo Maria Zwölf), both also acting as GEDE co-chairs, will moderate the discussion.