MS2.4 - Final recommendations on FAIR-by-Design training resources

The FAIR-by-Design Methodology provides a comprehensive framework for the development of learning materials. It offers clear, structured guidance on how to create FAIR training resources while allowing flexibility in the choice of tools, platforms, and content formats.This milestone presents the final recommendations on FAIR-by-Design training resources, summarizing insights gained through the iterative co-creation and continuous improvement process implemented up to January 2025. The recommendations are focusing on the commonly identified challenges thus far and build upon extensive stakeholder engagement, feedback mechanisms, and hands-on implementation experiences.The identified common challenges that users may face when applying the methodology include handling closed materials, managing version control, ensuring proper attribution, structuring content for maximum usability, and maintaining the sustainability of published training resources. For each challenge, the document presents practical solutions and recommendations, helping users overcome obstacles and maintain compliance with FAIR principles.The document also includes key takeaways, summarizing the most important insights for implementing the methodology effectively. It reinforces the idea that FAIR-by-Design is not just a set of rules but a flexible, evolving approach that supports better knowledge sharing and reuse in Open Science.Future refinements to the methodology will be made as new needs and challenges arise. The methodology is designed to grow and evolve, ensuring that learning materials remain relevant, high-quality, and aligned with the changing landscape of Open Science education.By following the guidance outlined in this document, instructors, trainers, and learning material developers can create robust, reusable, and widely accessible training content that aligns with best practices in Open Science and digital education.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-27
DOI
https://doi.org/10.5281/zenodo.14930617
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

MS2.4 - Final recommendations on FAIR-by-Design training resources

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

MS2.4 - Final recommendations on FAIR-by-Design training resources

article en

Abstract

The FAIR-by-Design Methodology provides a comprehensive framework for the development of learning materials. It offers clear, structured guidance on how to create FAIR training resources while allowing flexibility in the choice of tools, platforms, and content formats.This milestone presents the final recommendations on FAIR-by-Design training resources, summarizing insights gained through the iterative co-creation and continuous improvement process implemented up to January 2025. The recommendations are focusing on the commonly identified challenges thus far and build upon extensive stakeholder engagement, feedback mechanisms, and hands-on implementation experiences.The identified common challenges that users may face when applying the methodology include handling closed materials, managing version control, ensuring proper attribution, structuring content for maximum usability, and maintaining the sustainability of published training resources. For each challenge, the document presents practical solutions and recommendations, helping users overcome obstacles and maintain compliance with FAIR principles.The document also includes key takeaways, summarizing the most important insights for implementing the methodology effectively. It reinforces the idea that FAIR-by-Design is not just a set of rules but a flexible, evolving approach that supports better knowledge sharing and reuse in Open Science.Future refinements to the methodology will be made as new needs and challenges arise. The methodology is designed to grow and evolve, ensuring that learning materials remain relevant, high-quality, and aligned with the changing landscape of Open Science education.By following the guidance outlined in this document, instructors, trainers, and learning material developers can create robust, reusable, and widely accessible training content that aligns with best practices in Open Science and digital education.

Zenodo (CERN European Organization for Nuclear Research)
Karlsruhe Institute of Technology (DE), Centre National de la Recherche Scientifique (FR), Digital Curation Centre (GB), Aix-Marseille Université (FR), Education and Research Network (IN), Délégation Paris 6 (FR), Consortium GARR (IT), Ministry of Culture (PE), University of Ss. Cyril and Methodius in Trnava (SK), KU Leuven (BE)
Quality Education
Openalex Percentile: Top 43%
Research Data Management Practices
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