FAIRsFAIR at the Virtual SciDataCon 2021
27 October 2021

Following the postponement of International Data Week to June 2022 (hybrid and onsite in Seoul, Republic of Korea), it was decided to retain some of the most significant and time sensitive session proposals and to run them in a Virtual SciDataCon.

Virtual SciDataCon 2021 comprises sessions covering the following themes:

  • FAIR: interoperability and reusability
  • Implementing and Assessing FAIR
  • Policy Implementation (Open Science and FAIR)
  • Data Skills
  • Data Stewardship
  • Data Centres and Repositories
  • Research Infrastructures
  • Global Open Science Clouds, Platforms and Commons
  • Data for the Sustainable Development Goals and Disaster Risk Reduction
  • Data in Cross-Domain Research
  • Data in the Earth Sciences
  • Strategic Discussions about CODATA and WDS Initiatives

The event will start with a keynote and discussion on Monday 18 October (11:00-12:30 UTC) and will close with a panel discussion on Thursday 28 October (13:00-14:30) covering the themes of the conference and the role of CODATA and WDS in relation to current developments, including the UNESCO Recommendation on Open Science, the International Science Council’s Action Plan.

FAIRsFAIR at the Virtual SciDataCon 2021: FAIRsFAIR workshop "Tools and Support to foster FAIR Data practices in Europe" - 27 October 2021 | 13:00 - 14:30 UTC (15:00-16:30 CEST)

This 90min practice session will showcase practical solutions for the use of the FAIR data principles throughout the research data life cycle, namely fostering FAIR data culture and the uptake of good practices in making data FAIR. The session will have presentations from different FAIRsFAIR tools and support programs to repository managers, research data managers, service providers, data stewards and higher education institutes. Some implementation stories will be showcased of how FAIRsFAIR is supporting the improvement of data FAIRness and interoperability, across disciplines dealing with data. There will be opportunity for interaction and discussion with the audience.

Who should join this session?

  • Repository Managers interested in long-term data preservation and improving the interoperability levels of their repository;
  • Research Data Managers looking forward to implementing efficient and secure procedures for data management and analysis with attention to FAIR aspects;
  • Service Providers aiming to provide services that support the implementation of the FAIR data principles;
  • Higher Education Institutes interested in providing better training of researchers and students in Open Science and in the development of research data management skills and competencies.



15:00 - 15.05 Welcome and overview of FAIRsFAIR (Ingrid Dillo – DANS-KNAW Data Archiving and Networked Services) (Presentation)
15:05 - 15:13 FAIR Semantics, Interoperability, and Services (Jessica Parland-von Essen – CSC ICT Solutions for Brilliant Minds) (Presentation)
15:13 - 15:21 FAIR-Aware (Linas Cepinskas - DANS-KNAW Data Archiving and Networked Services) (Presentation)
15:21 - 15:31 FAIRsFAIR Data Object Assessment Metrics and  F-UJI Automated FAIR Data Assessment Tool (Robert Huber - MARUM) (Video)
15:31 - 15.41 Questions and Answers
15:41 - 15:49 FAIRsFAIR Repositories Certification Support (Linas Cepinskas - DANS-KNAW Data Archiving and Networked Services) (Presentation)
15:49 - 15:57 FAIRsFAIR Competence Centre (Gabin - Science and Technology Facilities Council) (Presentation)
15:57 - 16:05 FAIR for Higher Education Institutions (Federica Garbuglia – European University Association) (Presentation)
16:05 - 16:15 Questions and Answers
16:15 - 16:25 Quizz about presentations
16:25 - 16:30 What's next & Closing Remarks (Ingrid Dillo – DANS-KNAW Data Archiving and Networked Services)


What will be presented?


FAIR-Aware is an online tool which helps researchers and data managers assess how much they know about the requirements for making datasets findable, accessible, interoperable, and reusable before uploading them into a data repository. The FAIR Data Object Assessment Metrics evaluates the FAIRness of data objects within trustworthy repositories. These metrics are based on prior and existing global work, such as funders, the RDA Maturity model work as well as the FAIR Working Group (WG) from the European Open Science Cloud. The F-UJI Automated FAIR Data Assessment Tool runs practical tests against these metrics to support repositories in evaluating the FAIRness of the data they hold. F-UJI adheres to existing web standards and utilises external registries and resources and aims to be a FAIR data assessment tool in the EOSC. Practical examples about how the F-UJI tool is being used and adapted by a number of initiatives will be provided during the session.

FAIRsFAIR Support Programmes

The FAIRsFAIR Competence team in partnership with the CODATA-RDA schools are delivering customised curriculum training to Data Steward Instructors and to Early Career Researchers (ECR) in the appropriate data skills to make use of the resources of the European Open Science Cloud (EOSC). The instructor training combines a discussion of pedagogy with an introduction to topics such as FAIR, Data Management Plans and building up Research Data Management services within institutions. The ECR training provides a broad foundation in a variety of technical and social skills. These trainings allow the development of communities of instructors and researchers, strengthening their confidence in terms of having a support network in research environments that are themselves adapting to the realities of the Data Revolution. The successful implementation of EOSC is dependent on having enough researchers with the relevant data skills to make use of EOSC resources and a sufficient number of data stewards to support researchers and to make and keep data FAIR.

The FAIRsFAIR Certification Support towards more trustworthy and FAIR-enabling repositories, which helps them make and keep their data FAIR and prepare them for the CoreTrustSeal certification. In return, the repositories share their invaluable knowledge on how trustworthy repository practices best enable FAIR data. Their common issues in the certification process help create better guidance and support material for the wider repository community, developing recommendations for integrating FAIR into the CoreTrustSeal requirements.

FAIRsFAIR is also working on a FAIR Competence Framework for Higher Education Institutes (HEIs) which will help HEIs to implement FAIR data competences in their curricula (at Bachelor, Master and Doctoral levels), along with a FAIR Competences Adoption Handbook for Universities to Translate the competence framework into usable materials and a “Good practices in FAIR competence training” report with good practices from universities across Europe. A Book Sprint in June was organised to examine and review the materials which are available to date and working together to develop model curricula, courses and learning units for different levels and from different perspectives. 

All these FAIRsFAIR efforts represent a leading role in the implementation of FAIR for the EOSC, since its contributions have been a key contributor to the ongoing development of global standards for FAIR data and repository certification (e.g. FAIRsFAIR is working with the CoreTrustSeal to include a FAIR-enabling assessment in the certification process). This is possible thanks to FAIRsFAIR continuous engagement with different EOSC Working Groups (WG), projects and initiatives in FAIR and open data, as well as various other stakeholders.

FAIRsFAIR at the Virtual SciDataCon 2021: "Earth and Environmental vocabularies and ontologies today: how are they managed? How are they used by scientists?" - 21 October 2021 | 11:00 - 12:30 UTC (13:00-14:30 CEST)

Yann le Franc (e-Science Data Factory and member of FAIRsFAIR) was invited to this session to do a presentation, entitled "FAIR Semantics Laying out the foundations for harmonizing practices across domains". Yann was invited as an expert of vocabulary implementation, plus the challenges encountered in real-world use.

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