The OSTrails project recently took center stage at a webinar of the Pistoia Alliance, a nonprofit alliance working to lower barriers to innovation in life science and healthcare R&D through pre-competitive collaboration.  Led by Dr. Mark D. Wilkinson from the Universidad Politécnica de Madrid and Prof. Susanna-Assunta Sansone from the University of Oxford, the presentation highlighted OSTrails' pivotal role in addressing the growing challenges of ensuring consistent, accurate, and scalable FAIR data assessment and assistance.

At the core of OSTrails' mission is the creation of standardized APIs and assessment frameworks that will enable FAIR evaluations across a wide spectrum of digital objects. The team is actively working to harmonize the fragmented landscape of FAIR assessment tools by proposing discipline-specific metrics and developing a governance model to ensure that new metrics and methodologies are trusted, transparent, and widely adopted.

OSTrails also aims to reduce confusion and the burden on researchers and data providers by shifting the focus from mere assessment to assistance. Through its innovative tools, OSTrails will provide actionable feedback to help users improve their data's FAIRness, rather than treating assessments as punitive or cumbersome. This shift will also be supported by FAIRsharing, a core component of OSTrails that serves as a look-up service for community data and metadata standards, their relations and use, and plays a key role in the validation and governance of FAIR metrics.

Looking ahead, OSTrails will play a significant role in implementing the decisions of the EOSC FAIR Metrics and Data Quality Task Force and the FAIR Metrics and Digital Objects Task Force. Their work will focus on expanding the range of digital objects covered by FAIR assessments, refining metadata structures, and tackling the complexities of private and sensitive data. By professionalizing the FAIR assessment ecosystem, OSTrails is set to establish a more consistent, efficient, and trusted approach to FAIR data evaluation, benefiting researchers, repositories, and broader scientific communities alike.

Resources

• The presentation is available here.

• The recording can be accessed here.