FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards
Abstract The current rise of Open Science and Reproducibility in the Life Sciences requires the creation of rich, machine-actionable metadata in order to better share and reuse biological digital resources such as datasets, bioinformatics tools, training materials, etc. For this purpose, FAIR princi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-07-01
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| Series: | Journal of Biomedical Semantics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13326-023-00289-5 |
| _version_ | 1797789505469546496 |
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| author | Alban Gaignard Thomas Rosnet Frédéric De Lamotte Vincent Lefort Marie-Dominique Devignes |
| author_facet | Alban Gaignard Thomas Rosnet Frédéric De Lamotte Vincent Lefort Marie-Dominique Devignes |
| author_sort | Alban Gaignard |
| collection | DOAJ |
| description | Abstract The current rise of Open Science and Reproducibility in the Life Sciences requires the creation of rich, machine-actionable metadata in order to better share and reuse biological digital resources such as datasets, bioinformatics tools, training materials, etc. For this purpose, FAIR principles have been defined for both data and metadata and adopted by large communities, leading to the definition of specific metrics. However, automatic FAIRness assessment is still difficult because computational evaluations frequently require technical expertise and can be time-consuming. As a first step to address these issues, we propose FAIR-Checker, a web-based tool to assess the FAIRness of metadata presented by digital resources. FAIR-Checker offers two main facets: a “Check” module providing a thorough metadata evaluation and recommendations, and an “Inspect” module which assists users in improving metadata quality and therefore the FAIRness of their resource. FAIR-Checker leverages Semantic Web standards and technologies such as SPARQL queries and SHACL constraints to automatically assess FAIR metrics. Users are notified of missing, necessary, or recommended metadata for various resource categories. We evaluate FAIR-Checker in the context of improving the FAIRification of individual resources, through better metadata, as well as analyzing the FAIRness of more than 25 thousand bioinformatics software descriptions. |
| first_indexed | 2024-03-13T01:51:41Z |
| format | Article |
| id | doaj.art-86fa386a2759464abcb746ed9f730caa |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-03-13T01:51:41Z |
| publishDate | 2023-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-86fa386a2759464abcb746ed9f730caa2023-07-02T11:30:01ZengBMCJournal of Biomedical Semantics2041-14802023-07-0114111410.1186/s13326-023-00289-5FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standardsAlban Gaignard0Thomas Rosnet1Frédéric De Lamotte2Vincent Lefort3Marie-Dominique Devignes4Nantes Université, CNRS, INSERM, l’institut du thoraxTAGC/INSERM U1090, Univ Aix-MarseilleUMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroLIRMM, Univ Montpellier, CNRSUniversité de Lorraine, CNRS, Inria, LORIAAbstract The current rise of Open Science and Reproducibility in the Life Sciences requires the creation of rich, machine-actionable metadata in order to better share and reuse biological digital resources such as datasets, bioinformatics tools, training materials, etc. For this purpose, FAIR principles have been defined for both data and metadata and adopted by large communities, leading to the definition of specific metrics. However, automatic FAIRness assessment is still difficult because computational evaluations frequently require technical expertise and can be time-consuming. As a first step to address these issues, we propose FAIR-Checker, a web-based tool to assess the FAIRness of metadata presented by digital resources. FAIR-Checker offers two main facets: a “Check” module providing a thorough metadata evaluation and recommendations, and an “Inspect” module which assists users in improving metadata quality and therefore the FAIRness of their resource. FAIR-Checker leverages Semantic Web standards and technologies such as SPARQL queries and SHACL constraints to automatically assess FAIR metrics. Users are notified of missing, necessary, or recommended metadata for various resource categories. We evaluate FAIR-Checker in the context of improving the FAIRification of individual resources, through better metadata, as well as analyzing the FAIRness of more than 25 thousand bioinformatics software descriptions.https://doi.org/10.1186/s13326-023-00289-5FAIRSchema.orgBioschemasSPARQLSHACL |
| spellingShingle | Alban Gaignard Thomas Rosnet Frédéric De Lamotte Vincent Lefort Marie-Dominique Devignes FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards Journal of Biomedical Semantics FAIR Schema.org Bioschemas SPARQL SHACL |
| title | FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards |
| title_full | FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards |
| title_fullStr | FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards |
| title_full_unstemmed | FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards |
| title_short | FAIR-Checker: supporting digital resource findability and reuse with Knowledge Graphs and Semantic Web standards |
| title_sort | fair checker supporting digital resource findability and reuse with knowledge graphs and semantic web standards |
| topic | FAIR Schema.org Bioschemas SPARQL SHACL |
| url | https://doi.org/10.1186/s13326-023-00289-5 |
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