9:00 FAIR, Data Quality Management and Research Metrics Assessment
FAIRness assessment of Digital Objects (including data and repositories) should be considered to be established as a concept with tools and metrics defined and repositories starting to work to ensure data is FAIR. Unfortunately the existing range of FAIR assessment tools often renders widely different results because of independent interpretations of the Metrics, metadata publishing paradigms, and even the intent of FAIR itself. Supplementary to FAIR assessments is a needed Data Quality framework to ensure trustworthiness and readiness for the re-use of data.
The operational use of semantic artefacts within the research sector is getting increasingly important and will form basic building blocks for cross-disciplinary use. The demand for reliable, sustainable, and trustworthy service of semantic components like ontologies, terminologies, schemes, mappings, etc., requires a precise statement on FAIR and quality management for targeted maintenance.
What are the existing guidelines and what are the gaps? What is the status of existing assessments and how a consistency roadmap for assessment services looks like? How can metrics be used to improve the discoverability, access, interoperability and reuse of semantic artefacts? What are the indicators of FAIR & Data Quality that could be used for semantic artefacts metrics?
Agenda
Chair: Chris Schubert, TU Wien Bibliothek
| Time | Topic | Speaker |
|---|---|---|
| 9:00-9:05 | Welcome, introduction to the landscape and the session | Chris Schubert (Head of Media Management and Library-IT, TU Wien Bibliothek) |
| 9:05-9.25 | What is the current state of FAIR assessment metrics and tools specifically for semantic artefacts? – A contextual presentation Talk “Why FAIR assessment is failing” (Mark Wilkinson) Showcase “FAIRness Evaluation for semantic artefacts” (Clement Jonquet) | Mark Wilkinson (UPM) Clement Jonquet (INRAE) |
| 9:25-9:55 | Activity: Collect indicators that can be used for FAIR semantic artefact metrics. | |
| 9:55-10:10 | Groups reporting back | |
| 10:10-10:15 | Wrap-up and closing |
