2025-05-20 –, Joost den Draaijer
This workshop is for data stewards and anyone who wishes to improve a community’s knowledge of the FAIR principles as applied to data and other digital object types.
FAIR-Aware is an open-source online tool aimed at assessing and aiding researchers and others in their understanding of the FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles.
The new version of FAIR-Aware has been designed to be adaptable and can be used to create and adapt support and guidance in improving FAIRness for various digital object types important to research, such as research software and semantic artefacts, as well as for the needs of a discipline or specifically for your research performing organisation (RPO). It is also possible for the interface, questions, supporting guidance and glossary to be translated into different languages.
FAIR-Aware is an open-source online tool with a simple installation process allowing you to run a local version targeted for a specific research infrastructure or RPO for self-directed study or to be used by data stewards and trainers.
This will be a hands-on workshop where you will have the opportunity to learn how to create your own, or adapt, questions and guidance on the FAIR principles for different digital object types and how to modify these for a discipline-specific community. Additionally, the support for trainers to utilise FAIR-Aware with cohorts of learners will be discussed. How to access existing question and guidance modules, and how to share your guidance with the wider research support community will also be covered.
FAIR-Aware 2.0 was developed as part of the European Union funded project FAIR-IMPACT.
Mike is a member of the Data Expert team at Data Archiving and Networked Services (DANS), an institute of the KNAW & NWO. He has been involved in specifying and creating research infrastructures since 2004 in the Social Sciences, Arts & Humanities. He is currently co-leading the work package developing FAIR metrics and assessment tools across research outputs, such as data, semantic artefacts and software, in the FAIR-IMPACT project.