Relevance
The report on FAIR Evaluation community survey underscores the importance of harmonizing FAIR (Findable, Accessible, Interoperable, and Reusable) assessments across diverse research communities and settings, highlighting challenges and exploring the need for community-driven governance. It lays foundational insights for enhancing FAIR practices, instrumental for advancing the European Open Science Cloud’s mission to create a web of FAIR data and services.
Scope
This deliverable provides an analysis of the current state of FAIR assessments, aimed at developers and users of FAIR assessment tools. Targeting the academic community and stakeholders involved in the European Open Science Cloud (EOSC), it seeks to support the harmonization of FAIR assessments and foster community-driven governance approaches for enhancing FAIR adoption.
Main highlights
The “Report on FAIR Evaluation Community Survey” presents a detailed analysis of responses concerning the application, challenges, and governance of FAIR assessments. Conducted by the EOSC Association Task Force on FAIR Metrics and Data Quality, the survey garnered insights from 78 participants, predominantly from academia, reflecting a wide spectrum of disciplines and roles. A significant outcome is the community’s active engagement with FAIR principles, primarily through self-assessments, highlighting the diverse tools employed and the need for transparent interpretations of FAIR Metrics.
Challenges identified include the variability in tool results and the interpretation of FAIR principles across domains, underpinning a moderate level of trust in FAIR assessment outcomes.
Furthermore, the survey underscores a community inclination towards establishing a FAIR Assessment Governance Body to ensure consistency in assessments and foster community involvement and best practice development. This governance body is envisaged to inform the harmonization of FAIR assessments, enhance transparency, and build trust in tools and processes.
Additionally, the report explores the community’s awareness and adoption of CARE (Collectable, Accessible, Reusable, Expendable) and TRUST (Transparency, Responsibility, User focus, Sustainability, and Technology) principles, indicating a nascent but growing interest that complements FAIR principles. Overall, the findings advocate for a collaborative, community-driven approach to refining FAIR assessment tools and methodologies, essential for advancing the FAIRness of research outputs within the EOSC and beyond.
Key recommendations
The “Report on FAIR Evaluation Community Survey” offers several key recommendations aimed at enhancing the effectiveness, harmonization, and governance of FAIR assessments across the research landscape:
- Promote Community Engagement and Transparency: Encourage active community involvement in the development of FAIR assessment tools and methods. This includes fostering open dialogue, co-developing and sharing best practices, and making FAIR assessment processes more transparent.
- Develop and Share Best Practices: Compile and disseminate best practices for FAIR assessments, focusing on addressing common challenges such as the interpretation of FAIR principles and the validation of assessment results.
- Enhance Training and Support: Provide comprehensive training resources and support mechanisms to equip researchers and other stakeholders with the knowledge and skills required for effective FAIR assessments.
- Establish Clear Governance Structures: There’s a general favour for the creation of a FAIR Assessment Governance Body. This entity would standardize FAIR assessments, ensuring consistent interpretation and application of FAIR principles across different domains and tools, thereby increasing trust in FAIR assessment outcomes.
- Explore Integration with CARE and TRUST Principles: Investigate opportunities for advancing CARE and TRUST principles adoption through assessments, supporting ethical considerations and responsible data stewardship.
- Facilitate Interoperability Among FAIR Assessment Tools: Encourage the development and adoption of interoperable standards among FAIR assessment tools to enable more consistent and comparable assessments across various research outputs and digital objects.
These recommendations aim to strengthen the FAIR ecosystem, promoting a more cohesive, transparent, and effective approach to managing and assessing the FAIRness of research data and outputs.