References
- Abou-Zahra, S. (ed.) (2017) ‘Evaluation and Report Language (EARL) 1.0 Schema -W3C Working Group Note’, The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/EARL10-Schema/ - Albertoni, R., Browning, D., Cox, S.J.D., Gonzalez Beltran, A., Perego, A. and Winstanley, P. (eds.) (2024) ‘Data Catalog Vocabulary (DCAT) – Version 3- W3C Recommendation’, The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/vocab-dcat-3/ - Amdouni, E., Bouazzouni, S. and Jonquet, S. (2022) ‘O’FAIRe makes you an offer: metadata-based automatic FAIRness assessment for ontologies and semantic resources’, International Journal of Metadata, Semantics and Ontologies, 16(1), pp. 16–46. Available at: 10.1504/IJMSO.2022.131133
- Arnhold, L., Miksa, T. and Staudinger, M. (2025) ‘Quality dimensions and evaluation framework for machine-actionable DMPs’, Journal of Data and Information Quality, 17(4), pp. 1–26. Available at: 10.1145/3776555
- Barker, M., Chue Hong, N.P., Katz, D.S., Lamprecht, A.L., Martinez-Ortiz, C., Psomopoulos, F., Harrow, J., Castro, L.J., Gruenpeter, M., Martinez, P.A. and Honeyman, T. (2022) ‘Introducing the FAIR principles for research software’, Scientific Data, 9(1), p. 622. Available at: 10.1038/s41597-022-01710-x
- Clarke, D.J.B., Wang, L., Jones, A., Wojciechowicz, M.L., Torre, D., Jagodnik, K.M., et al. (2019) ‘FAIRshake: toolkit to evaluate the FAIRness of research digital resources’, Cell Systems, 9(5), pp. 417–421. Available at: 10.1016/j.cels.2019.09.011
- Curran, P. and Duborst, K. (eds.) (2005) ‘Test Metadata- W3C Working Group Note’, The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/test-metadata/ - Devaraju, A. and Huber, R. (2021) ‘An automated solution for measuring the progress toward FAIR research data’, Patterns, 2(11), p. 100370. Available at: 10.1016/j.patter.2021.100370
- Devaraju, A., Huber, R., Mokrane, M., Herterich, P., Cepinskas, L., de Vries, J., L’Hours, H., Davidson, J. and White, A. (2020) ‘FAIRsFAIR data object assessment metrics’, Zenodo. Available at: 10.5281/zenodo.3775793
- European Commission: Directorate-General for Research and Innovation. (2018) ‘Turning FAIR into reality – final report and action plan from the European Commission expert group on FAIR data’, Publications Office. Available at: 10.2777/1524
- European Commission: Directorate-General for Research and Innovation and EOSC Executive Board. (2020) ‘Six Recommendations for implementation of FAIR practice by the FAIR in practice task force of the European open science cloud FAIR working group’, Publications Office. Available at: 10.2777/986252
- European Commission: Directorate-General for Research and Innovation and EOSC Executive Board. (2021) ‘Recommendations on FAIR metrics for EOSC’, Publications Office. Available at: 10.2777/70791
- FAIR Data Maturity Model Working Group. (2020) ‘FAIR Data Maturity Model. Specification and Guidelines (1.0)’, Zenodo. Available at: 10.15497/rda00050
- Gaignard, A., Rosnet, T., De Lamotte, F., Lefort, V. and Devignes, M.-D. (2023) ‘FAIR-Checker: supporting digital resource findability and reuse with knowledge graphs and semantic web standards’, Journal of Biomedical Semantics, 14(1), p. 7. Available at: 10.1186/s13326-023-00289-5
- Garijo, D., Corcho, O. and Poveda-Villalón, M. (2021) ‘FOOPS!: an ontology pitfall scanner for the FAIR principles’, CEUR Workshop Proceedings, Posters, Demos, and Industry Tracks. ISWC 2021, Virtual Conference. Available at:
https://ceur-ws.org/Vol-2980/paper321.pdf - Hernandez Serrano, P. and Emonet, V. (2022) ‘The FAIR extension: a web browser extension to evaluate digital object FAIRness’, Research Ideas and Outcomes, 8, p.
e95006 . Available at: 10.3897/rio.8.e95006 - International Science Council. (2021)
‘Opening the record of science: making scholarly publishing work for science in the digital era’ , International Science Council, Paris, France. Available at: 10.24948/2021.01 - Jung, J.D. and Martini, D. (2025)
‘Entwicklung eines automatisierten Systems zur FAIR-Bewertung von Datensätzen in der Land-, Forst- und Ernährungswirtschaft’ , 45. GIL-Jahrestagung, Digitale Infrastrukturen für eine nachhaltige Land-, Forst- und Ernährungswirtschaft, Wieselburg, Austria. Available at: 10.18420/giljt2025_05 - Knublauch, H., Kontokostas, D. and the W3C SHACL Working Group. (eds.) (2020) ‘Shapes constraint language (SHACL). W3C recommendation’, The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/shacl/ - Lamarre, P., Andersen, J., Gaignard, A. and Cazalens, S. (2024)
‘A generic framework to better understand and compare FAIRness measures’ , Knowledge Engineering and Knowledge Management, EKAW 2024, Amsterdam, Netherlands. Available at:https://hal.science/hal-04830524/document - Lóscio, B.F., Burle, C. and Calegari, N. (eds.) (2017) ‘Data on the Web Best Practices. W3C Recommendation’, The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/dwbp - Moreau, L., Missier, P. and W3C Provenance Working Group. (eds.) (2013) ‘PROV-ontology (PROV-O): an OWL2 ontology for PROV data model. W3C recommendation’. The World Wide Web Consortium (W3C). Available at:
https://www.w3.org/TR/prov-o/ - Poveda-Villalón, M., Espinoza-Arias, P., Garijo, D. and Corcho, O. (2020) ‘Coming to terms with FAIR ontologies’, in C. M. Keet and M. Dumontier (eds.) Knowledge Engineering and Knowledge Management: 22nd International Conference, EKAW 2020, Bolzano, Italy,
Springer International Publishing, Lecture notes in computer science . pp. 255–270. Available at: 10.1007/978-3-030-61244-3_18 - Radulovic, F. and García Castro, R. (2015) The quality model ontology. Available at:
https://purl.org/net/QualityModel (Accessed: 22 January 2026). - Radulovic, F. and García Castro, R. (2017) The evaluation result ontology. Available at:
https://purl.org/net/EvaluationResult (Accessed: 22 January 2026). - Radulovic, F., Mihindukulasooriya, N., García Castro, R. and Gomez-Perez, A. (2017). ‘A comprehensive quality model for linked data’, Semantic Web, 9, pp. 1–22. Available at: 10.3233/SW-170267
- RDA FAIR Data Maturity Model Working Group. (2020) ‘FAIR data maturity model: specification and guidelines’, Research Data Alliance. Available at: 10.15497/rda00045
- Rijgersberg, H., van Assem, M. and Top, J. (2013) ‘Ontology of units of measure and related concepts’. Semantic Web: – Interoperability, Usability, Applicability, 4(1), pp. 3–13. Available at: 10.3233/SW-2012-0069
- Strong, D., Lee, Y. and Wang, R. (2002) ‘Data Quality in Context’, Communications of the ACM, 40. Available at: 10.1145/253769.253804
- Sun, C., Emonet, V. and Dumontier, M. (2022) ‘A comprehensive comparison of automated FAIRness evaluation tools’, Semantic Web Applications and Tools for Health Care and Life Sciences, 13th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, Virtual Event, Leiden, Netherlands, 3127, pp. 44–53. Available at:
https://ceur-ws.org/Vol-3127/paper-6.pdf - Taylor & Francis. (2025) Understanding our data sharing policies. Available at:
https://authorservices.taylorandfrancis.com/data-sharing-policies/ (Accessed: 22 January 2026). - Tuozzo, G. and Pellegrino, M.A. (2026) ‘FAIR-O: An Ontology for FAIR Assessment and Scoring (1.0.0)’, Zenodo. Available at: 10.5281/zenodo.20027101
- Verburg, M., Priddy, M., Huber, R., Jonquet, C. and Chue Hong, N. (2023) ‘FAIRIMPACT project response to community-driven governance of FAIRness assessment: an open issue, an open discussion’, Zenodo. Available at: 10.5281/zenodo.7848126
- Wentzel, B., Kirstein, F., Jastrow, T., Sturm, R., Peters, M. and Schimmler, S. (2023) ‘An extensive methodology and framework for quality assessment of DCAT-AP datasets’, in: Lindgren, I., et al. (eds.) Electronic Government. EGOV 2023. Lecture Notes in Computer Science, 14130. Available at: 10.1007/978-3-031-41138-0_17
- Wilkinson, M. and Garijo, D. (2026) ‘D1.3 FAIRness reference model for digital objects V2’, Zenodo. Available at: 10.5281/zenodo.18506494
- Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. (2016) ‘The FAIR Guiding Principles for scientific data management and stewardship’, Sci Data, 3, 160018. Available at: 10.1038/sdata.2016.18
- Wilkinson, M.D., Dumontier, M., Sansone, S.-A., da Silva Santos, L.O.B, Prieto, M., Batista, D., McQuilton, P., Kuhn, T., Rocca-Serra, P., Crosas, M. and Schultes, E. (2019) ‘Evaluating FAIR maturity through a scalable, automated, community-governed framework’, Scientific Data, 6(1), p. 174. Available at: 10.1038/s41597-019-0184-5
- Wilkinson, M.D., Sansone, S.-A., Grootveld, M., Dennis, R., Hecker, D., Huber, R., Soiland-Reyes, S., Van de Sompel, H., Czerniak, A., Thurston, M., Lister, A. and Gaignard, A. (2024). ‘Report on FAIR signposting and its uptake by the community’, Zenodo. Available at: 10.5281/zenodo.10490289
- Wilkinson, M.D., Sansone, S.-A., Méndez, E., David, R., Dennis, R., Hecker, D., Kleemona, M., Lacagnina, C., Nikifora, A. and Castro, L.J. (2023) ‘Community-driven governance of FAIRness assessment: an open issue, an open discussion’, Open Research Europe, 2, p. 146. Available at: 10.12688/openreseurope.15364.2
DOI: https://doi.org/10.5334/dsj-2026-030 | Journal eISSN: 1683-1470
Language: English
Page range: 30 - 30
Submitted on: Jan 23, 2026
Accepted on: Jul 28, 2026
Published on: Aug 12, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2026 Robert Huber, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.