FAIR assessment and data objects

The sessions will explore the evolving landscape of FAIR data, addressing current limitations and highlighting opportunities created by emerging standards and improved data quality to enhance reuse and preservation.

These sessions will focus on FAIR assessment, metrics, data quality and the uptake of AI-ready FAIR research data within the EOSC Federation, aligning efforts across projects to improve FAIRness and streamline practices for digital objects.


The sessions focus on advancing the application of FAIR principles through the exploration of assessment tools, methods, and their role in ensuring the quality and preservation of digital objects. Participants will engage in hands-on activities and collaborative discussions to gain practical guidance on implementing FAIR assessments. Interactive discussions will provide practical guidance, technical insights, and avenues for collaboration, supporting the advancement of research data management practices within the EOSC Federation.

  • Develop a feedback matrix to enhance EOSC resources by aligning diverse approaches, sharing knowledge, and addressing common challenges.
  • Support consistent FAIR assessment across projects and communities by fostering a unified and transparent framework.
  • Provide guidance for the implementation of FAIR assessments across projects and communities within and outside of the EOSC community through hands-on activities, and collaborative discussions.

TUESDAY AFTERNOON

Room: TRIANA

WEDNESDAY MORNING

Room: TRIANA

TimeslotTitleFormatModeratorRapporteurContentProject
9:30 -10:00Recap of outcomes of preceding sessionTalkMark WilkinsonChris Schubert
10:00-11:00Opportunities FAIR for AIRound TableDaniel GarijoChris SchubertFAIR data to be ready for AI-Productivity, is there a data quality benchmark for training data, can FAIR Metrics support the production chain. Are there approaches of AI for the implementation of FAIR or to check data quality? How incentives looks like to make you capture metadata to support AI, FAIR4ML, the croissant standard, model cards, etc.and the role of EOSC in it.AI4EOSC, FAIR Impact, OSCARS, OSTrails, FAIR EASE, FAIR2ADAPT, DataGems, etc.
11:00 – 11:15Coffee Break
11:15-12:00Opportunities FAIR for AIRound TableDaniel GarijoChris SchubertCan EOSC take the opportunity about standards for reporting data quality, to represent provenance and further models to improve Trust in Data Productivity?AI4EOSC, FAIR Impact, OSCARS, OSTrails, FAIR EASE, FAIR2ADAPT, DataGems, etc.
Sufficient metadata to support discovery for AI generated data.
12:00 – 13:00Reporting Plenary
WEDNESDAY AFTERNOON

Room: TRIANA

TimeslotTitleFormatModeratorRapporteurContentProject
14:00 -14:10Recap of outcomes of preceding sessionDaniel GarijoChris Schubert
14:10 – 15:30Interoperability with other spaces, FAIR governanceRound TableMark WilkinsonChris SchubertOS Trails and interoperabilityOSTrails, Skils4EOSC (EOSC Data Spaces), etc.
Interpretations of FAIR Assesments
Governance of FAIR? Governance of assessments?
15:30 – 16:00Coffee Break
16:00 – 17:00Towards a network of European Data SpacesOpen Pitch TalksMatthias LoebeChris SchubertInsight of the European Health Data Space (EHDS) and other research domainsOSTrails, Skils4EOSC (EOSC Data Spaces), SciLake, Lumen, etc.
Open Discussion & Cross Domain ProgressMatthias LoebeChris SchubertData Spaces and domain specific appoaches: categories of data and data bodies. Access, provenance and quality. Data holder and execution enviroments (SP4).
17:00 – 18:00Reporting Plenary

Sub-committee members

  • OAEG3: Chris Schubert, Daniel Garijo Verdejo, Munazah Andrabi, Yusnelkis Guisado, Anca Hienola, Francesca Spataro, Cinzia Cappiello
  • TF2: Mark Wilkinson, Elli Papadopoulou, Richard Dennis
  • TF4: Jacques Flores, Herve L’Hours
  • EOSC-A Board Liaison: Klaus Tochtermann, Sara Garavelli

Support team

  • EOSC-A: Paola Ronzino