Abstract
The FAIR principles have become a popular means to guide researchers when publishing their research outputs (i.e., data, software, etc.) in a Findable, Accessible, Interoperable and Reusable manner. In order to ease compliance with FAIR, different frameworks have been developed by the scientific community, offering guidance and suggestions to researchers. However, scientific outputs are rarely published in isolation. Research Objects have been proposed as a framework to capture the relationships and context of all constituents of an investigation. In this paper we present FAIROs, a framework for assessing the compliance of a Research Object (and its constituents) against the FAIR principles. FAIROs reuses existing FAIR validators for individual resources and proposes i) two scoring methods for assessing the fairness of Research Objects, ii) an initial implementation of the scoring methods in the FAIROs framework, and iii) an explanation-based approach designed to visualize the obtained scores. We validate FAIROs against 165 Research Objects, and discuss the advantages and limitations of different scoring systems.
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References
Bechhofer, S., De Roure, D., Gamble, M., Goble, C., Buchan, I.: Research objects: towards exchange and reuse of digital knowledge. Nat. Precedings 1 (2010). https://doi.org/10.1038/npre.2010.4626.1
Belhajjame, K., et al.: Using a suite of ontologies for preserving workflow-centric research objects. J. Web Semant. 32, 16–42 (2015). https://doi.org/10.1016/j.websem.2015.01.003
Benitez, A., González, E., Garijo, D.: FAIROs: a framework to assess FAIR principles in research objects (2022). https://doi.org/10.5281/zenodo.6599423
Collins, S., et al.: Turning fair into reality: final report and action plan from the European commission expert group on fair data (2018)
De Geest, P., et al.: RO-crate-py (2022). https://doi.org/10.5281/zenodo.3956493
De Smedt, K., Koureas, D., Wittenburg, P.: Fair digital objects for science: from data pieces to actionable knowledge units. Publications 8(2) (2020). https://doi.org/10.3390/publications8020021
Devaraju, A., Huber, R.: F-UJI - an automated fair data assessment tool (2020). https://doi.org/10.5281/zenodo.4063720
Devaraju, A., et al.: From conceptualization to implementation: fair assessment of research data objects. Data Sci. J. 20(1), 1–14 (2021)
Dumontier, M.: A comprehensive comparison of automated fairness evaluation tools (2022). http://ceur-ws.org/Vol-3127/paper-6.pdf
Garcia-Silva, A., et al.: Enabling fair research in earth science through research objects. Futur. Gener. Comput. Syst. 98, 550–564 (2019). https://doi.org/10.1016/j.future.2019.03.046
Garijo, D., Corcho, O., Poveda-Villalón, M.: FOOPS!: An ontology pitfall scanner for the fair principles. International Semantic Web Conference (ISWC) 2021: Posters, Demos, and Industry Tracks 2980 (2021). http://ceur-ws.org/Vol-2980/paper321.pdf
Garijo, D., Poveda-Villalón, M.: Best practices for implementing fair vocabularies and ontologies on the web. In: Giuseppe Cota, M.D., Pozzato, G.L. (eds.) Applications and Practices in Ontology Design, Extraction, and Reasoning. IOS Press, Netherlands (2020). https://doi.org/10.3233/SSW200034
Gonzalez, E., Benitez, A., Garijo, D.: TPDL 2022 - experiment - research objects data (2022). https://doi.org/10.5281/zenodo.6595409
Gonzalez, E., Benitez, A., Garijo, D.: TPDL 2022 - experiment - results (2022). https://doi.org/10.5281/zenodo.6595466
Katz, D.S., Gruenpeter, M., Honeyman, T.: Taking a fresh look at fair for research software. Patterns 2(3), 100222 (2021). https://doi.org/10.1016/j.patter.2021.100222
Lamprecht, A.L., et al.: Towards fair principles for research software. Data Sci. 3(1), 37–59 (2020)
Mao, A., Garijo, D., Fakhraei, S.: SoMEF: a framework for capturing scientific software metadata from its documentation. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 3032–3037 (2019). https://doi.org/10.1109/BigData47090.2019.9006447, http://dgarijo.com/papers/SoMEF.pdf
de Miranda Azevedo, R., Dumontier, M.: Considerations for the conduction and interpretation of fairness evaluations. Data Intell. 2(1–2), 285–292 (2020)
Poveda-Villalón, M., Espinoza-Arias, P., Garijo, D., Corcho, O.: Coming to terms with FAIR ontologies: a position paper. In: Keet, C.M., Dumontier, M. (eds.) EKAW 2020. LNCS (LNAI), vol. 12387, pp. 255–270. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-61244-3_18
Soiland-Reyes, S., et al.: Packaging research artefacts with RO-crate. Data Sci. 1–42 (2022). https://doi.org/10.3233/DS-210053
Spaaks, J.H., Kuzak, M., et al.: howfairis (2021). https://doi.org/10.5281/zenodo.4591110
Wilkinson, M.D., et al.: The fair guiding principles for scientific data management and stewardship. Sci. Data 3(1), 1–9 (2016)
Wilkinson, M.D., et al.: Evaluating fair maturity through a scalable, automated, community-governed framework. Sci. Data 6(1), 1–12 (2019)
Acknowledgements
This work has been funded by the European Commission within the H2020 Programme in the context of the project RELIANCE under grant agreement no. 101017501 and by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Universidad Politécnica de Madrid (UPM) in the line Support for R &D projects for Beatriz Galindo researchers, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation), and through the call Research Grants for Young Investigators from UPM.
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González, E., Benítez, A., Garijo, D. (2022). FAIROs: Towards FAIR Assessment in Research Objects. In: Silvello, G., et al. Linking Theory and Practice of Digital Libraries. TPDL 2022. Lecture Notes in Computer Science, vol 13541. Springer, Cham. https://doi.org/10.1007/978-3-031-16802-4_6
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