FAIR Semantic Artefacts Catalogues

The FAIR-Impact project has made an contribution in advancing Semantic Artefacts and their catalogues. Across various communities, existing catalogues are being consolidated to strengthen their use, while new catalogues are being deployed to support emerging projects and initiatives. Central to this effort is the development of a "FAIR-by-design" methodology, ensuring that Semantic Artefacts are inherently aligned with FAIR principles from the outset. To facilitate broader adoption, FAIR-enabling tools and methods are being transferred across different communities. A deep review of both current and retired catalogues has been conducted, focusing on their adherence to FAIR-enabling criteria. These catalogues are already being actively utilized in data repositories, with nine compelling use cases showcasing their potential. FAIR-Impact has also introduced a metadata standard for Semantic Artefacts, known as MOD, alongside a standardized API (MOD-API) for catalogues, enabling greater interoperability and accessibility. Early progress has been made toward federating four catalogues, laying the groundwork for a unified approach. Additionally, three governance models for Semantic Artefacts are being explored to ensure sustainable management and oversight. As part of its forward-looking vision, FAIR-Impact is working on specifications for FAIR mappings, aiming to enhance the integration and usability of Semantic Artefacts within and across catalogues. Together, these efforts pave the way for a robust and FAIR-aligned ecosystem of Semantic Artefacts and their catalogues.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-17
DOI
https://doi.org/10.5281/zenodo.14899537
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

FAIR Semantic Artefacts Catalogues

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

FAIR Semantic Artefacts Catalogues

article en

Abstract

The FAIR-Impact project has made an contribution in advancing Semantic Artefacts and their catalogues. Across various communities, existing catalogues are being consolidated to strengthen their use, while new catalogues are being deployed to support emerging projects and initiatives. Central to this effort is the development of a "FAIR-by-design" methodology, ensuring that Semantic Artefacts are inherently aligned with FAIR principles from the outset. To facilitate broader adoption, FAIR-enabling tools and methods are being transferred across different communities. A deep review of both current and retired catalogues has been conducted, focusing on their adherence to FAIR-enabling criteria. These catalogues are already being actively utilized in data repositories, with nine compelling use cases showcasing their potential. FAIR-Impact has also introduced a metadata standard for Semantic Artefacts, known as MOD, alongside a standardized API (MOD-API) for catalogues, enabling greater interoperability and accessibility. Early progress has been made toward federating four catalogues, laying the groundwork for a unified approach. Additionally, three governance models for Semantic Artefacts are being explored to ensure sustainable management and oversight. As part of its forward-looking vision, FAIR-Impact is working on specifications for FAIR mappings, aiming to enhance the integration and usability of Semantic Artefacts within and across catalogues. Together, these efforts pave the way for a robust and FAIR-aligned ecosystem of Semantic Artefacts and their catalogues.

Zenodo (CERN European Organization for Nuclear Research)
Royal Netherlands Academy of Arts and Sciences (NL), Université de Montpellier (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
Life in Land
Openalex Percentile: Top 39%
Research Data Management Practices
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FAIR Semantic Artefacts Catalogues · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS