Establishment of good practices for the usage of machine-actionable core metrological terminology
With progressing digitalisation of scientific research and metrological services, the exchange and reuse of data benefits from the usage of standard metadata schemas and controlled terminologies as a “common language” to describe, search and filter data. However, no framework yet unifies metrology-related endeavours to rigorously deal with machine-actionable data. Normative terminology documents often lack machine-readability, while community-driven machine-readable terminologies lack both metrological rigour and comprehensiveness. The resulting fragmented landscape makes it difficult for end users to adopt a good practice in registering data. Our contribution takes a step to cover this gap, by providing a unified overview of all relevant recommendations in a comprehensive and accessible way, in agreement with authoritative regulation bodies, current good practices, and existing digital-object validation platforms. Our activity will focus on a machine-readable version of the International Vocabulary of Metrology (VIM).
Authors
- Mark Kuster
- Maximilian Gruber (ORCID: https://orcid.org/0000-0002-3718-7919)
- Jean-Laurent Hippolyte (ORCID: https://orcid.org/0000-0002-5263-2881)
- Giacomo Lanza (ORCID: https://orcid.org/0000-0002-2239-3955)
- Federico Grasso Toro (ORCID: https://orcid.org/0000-0002-9041-0868)
- Maitane Iturrate‐Garcia (ORCID: https://orcid.org/0000-0002-1517-3305)
- Diego Nahuel Coppa
- Luca Mari (ORCID: https://orcid.org/0000-0002-7128-3453)
- Hugo Gasca-Aragon (ORCID: https://orcid.org/0000-0002-5384-2530)
- Martin Koval
- Michaela Küpferling
Institutions
- University of Bern (CH)
- Physikalisch-Technische Bundesanstalt (DE)
- National Nuclear Laboratory (GB)
- State Duma (RU)
- University Carlo Cattaneo (IT)
- National Institute of Industrial Technology (AR)
- Swiss Federal Institute of Metrology (CH)
- Český metrologický institut (CZ)
- Istituto Nazionale di Ricerca Metrologica (IT)
- National Metrology Center
Publication Details
- Journal
- Measurement Sensors
- Published
- 2024-12-22
- DOI
- https://doi.org/10.1016/j.measen.2024.101456
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00