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FAIR degree assessment in agriculture datasets using the F-UJI tool

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FAIR degree assessment in agriculture datasets using the F-UJI tool

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dc.contributor.author Petrosyan, Luiza es_ES
dc.contributor.author Aleixandre-Benavent, Rafael es_ES
dc.contributor.author Peset Mancebo, María Fernanda es_ES
dc.contributor.author Valderrama-Zurián, Juan Carlos es_ES
dc.contributor.author Ferrer Sapena, Antonia es_ES
dc.contributor.author Sixto-Costoya, Andrea es_ES
dc.date.accessioned 2024-01-18T19:01:27Z
dc.date.available 2024-01-18T19:01:27Z
dc.date.issued 2023-09 es_ES
dc.identifier.issn 1574-9541 es_ES
dc.identifier.uri http://hdl.handle.net/10251/202026
dc.description.abstract [EN] For the agricultural scientific community, data sharing is crucial both for the advancement of the discipline and ability to meet global challenges, such as the target no. 2, i.e., ¿Zero Hunger,¿ of the Sustainable Development Goals (SDG 2030). In this context, FAIR (Findable, Accessible, Interoperable and Reusable) principles play an important role, as they guarantee the findability, accessibility, interoperability, and reusability of shared data. To improve the practice of data sharing, institutions, funders, and publishers are increasingly demanding data be shared as well as be of an acceptable level of quality, including compliance with FAIR principles. Therefore, the objective of this work is twofold: first, this research aims to determine the degree of compliance with the FAIR principles exhibited by a number of datasets; and second, it aims to explore useful and valid methodologies and procedures that can be used to perform this evaluation quickly, automatically, and effectively. For this purpose, the Data Citation Index (DCI) was used to obtain many datasets in the field of agriculture, which were further grouped by repositories and evaluated using the automated assessment tool F-UJI provided by the FAIRsFAIR project. The results indicated that the principle that exhibited the highest scores was ¿Findable¿, while ¿Reusable¿ received the lowest scores, as none of the analysed repositories achieved a 50% compliance score in this respect. The datasets published in the Zenodo and Dryad repositories exhibited better overall results in terms of the FAIR principles, and the AG Commons repository was the third best rated repository, representing only one of the first three repositories belonging to the agricultural sector. Regarding the use of F-UJI as an automated assessment tool and DCI as a source for obtaining datasets, we conclude that this methodology is useful, and that although it can be improved, it is easy to use and implement by other scientific groups and agents of interest. es_ES
dc.description.sponsorship The authors would like to thank the grant PID2019-105708RB "Stable methodologies to evaluate and measure quality, interoperability, blockchain, and reuse of open data in the agricultural field: DATAUSE" funded by MCIN/AEI/10.13039/501100011033; the pre-doctoral grant (PRE2020-092585) of LP; and the postdoctoral grant (MS21-020) of ASC. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Ecological Informatics es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Agriculture es_ES
dc.subject Data sharing es_ES
dc.subject FAIR principles es_ES
dc.subject.classification BIBLIOTECONOMIA Y DOCUMENTACION es_ES
dc.title FAIR degree assessment in agriculture datasets using the F-UJI tool es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.ecoinf.2023.102126 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105708RB-C21/ES/SP1: DATAUSE STABLE METHODOLOGIES TO EVALUATE AND MEASURE QUALITY, INTEROPERABILITY, BLOCKCHAIN AND REUSE OF OPEN DATA IN THE AGRICULTURAL FIELD/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PRE2020-092585//SP1: DATAUSE STABLE METHODOLOGIES TO EVALUATE AND MEASURE QUALITY, INTEROPERABILITY, BLOCKCHAIN AND REUSE OF OPEN DATA IN THE AGRICULTURAL FIELD/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Facultad de Administración y Dirección de Empresas - Facultat d'Administració i Direcció d'Empreses es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Gestión de la Innovación y del Conocimiento - Institut de Gestió de la Innovació i del Coneixement es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Matemática Pura y Aplicada - Institut Universitari de Matemàtica Pura i Aplicada es_ES
dc.description.bibliographicCitation Petrosyan, L.; Aleixandre-Benavent, R.; Peset Mancebo, MF.; Valderrama-Zurián, JC.; Ferrer Sapena, A.; Sixto-Costoya, A. (2023). FAIR degree assessment in agriculture datasets using the F-UJI tool. Ecological Informatics. 76. https://doi.org/10.1016/j.ecoinf.2023.102126 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.ecoinf.2023.102126 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 76 es_ES
dc.relation.pasarela S\495362 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.subject.ods 02.- Poner fin al hambre, conseguir la seguridad alimentaria y una mejor nutrición, y promover la agricultura sostenible es_ES


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