The compliance to FAIR principles of shared data in addiction research

The aim of this study is to assess the scientific data sharing in the field of addictions by applying FAIR principles. These principles play an important role, as they guarantee a minimum of findability, accessibility, interoperability and reusability of the shared data. They are one of the main mea...

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Autores: Sixto-Costoya, A., Ferrer-Sapena, Antonia, Aleixandre-Benavent, Rafael, Peset, Fernanda, Valderrama-Zurián, Juan Carlos, Petrosyan, Luiza
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/406035
Acceso en línea:http://hdl.handle.net/10261/406035
Access Level:acceso abierto
Palabra clave:Addictions
Data sharing
Open data
Repositories
FAIR principles
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spelling The compliance to FAIR principles of shared data in addiction researchSixto-Costoya, A.Ferrer-Sapena, AntoniaAleixandre-Benavent, RafaelPeset, FernandaValderrama-Zurián, Juan CarlosPetrosyan, LuizaAddictionsData sharingOpen dataRepositoriesFAIR principlesThe aim of this study is to assess the scientific data sharing in the field of addictions by applying FAIR principles. These principles play an important role, as they guarantee a minimum of findability, accessibility, interoperability and reusability of the shared data. They are one of the main measures to improve the integrity and quality of research data. For this study, three automated tools were used: the Data Citation Index (DCI) to capture datasets on addictions; Bibliometricos, proprietary software for data retrieval; and the F-UJI tool for the FAIR evaluation of datasets. The datasets on the most common addiction topics, such as alcohol, cannabis, tobacco, cocaine, opioids and stimulants, were downloaded by the DCI (5967 DOIs) and parsed into a database for subsequent analysis. In terms of datasets characteristics, alcohol, tobacco and opioids were the most productive. After assessment by F-UJI, none of the addictions analyzed reached an average of 30% FAIR compliance since all of them were between 20% and 29%. When analyzing each principle, Findable was the best scored principle (in a range of 40%–59%), followed by Accessible, Interoperable and Reusable. The results of our study show, first, an increasing number of shared datasets over the years, especially from basic studies. In terms of quality, there are issues that remain to be resolved, especially in relation to interoperability and reusability principles. This emphasizes the important role of adequate data sharing procedures in ensuring that datasets are FAIR compliant and usable in addiction research.The authors would like to thank the grant “Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field” funded by MCIN/AEI/https://doi.org/10.13039/501100011033; the predoctoral grant (PRE2020-092585) of LP; the postdoctoral grant (MS21-020) of ASC; and the funding from the Generalitat Valenciana (Spain) through the PROMETEO 2024 CIPROM/2023/32 grant.Peer reviewedSpringerAkadémiai Kiadó (Budapest)Ministerio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/406035reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI//PRE2020-092585Sixto-Costoya, A.; Ferrer-Sapena, Antonia; Aleixandre-Benavent, Rafael; Peset, Fernanda; Valderrama-Zurián, Juan Carlos; Petrosyan, Luiza; 2023; The quality of datasets in the area of addictions (REPORTS) [Dataset]; Figshare; https://doi.org/10.6084/m9.figshare.23716287.v1https://doi.org/10.1007/s11192-024-05227-5Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4060352026-05-22T06:33:51Z
dc.title.none.fl_str_mv The compliance to FAIR principles of shared data in addiction research
title The compliance to FAIR principles of shared data in addiction research
spellingShingle The compliance to FAIR principles of shared data in addiction research
Sixto-Costoya, A.
Addictions
Data sharing
Open data
Repositories
FAIR principles
title_short The compliance to FAIR principles of shared data in addiction research
title_full The compliance to FAIR principles of shared data in addiction research
title_fullStr The compliance to FAIR principles of shared data in addiction research
title_full_unstemmed The compliance to FAIR principles of shared data in addiction research
title_sort The compliance to FAIR principles of shared data in addiction research
dc.creator.none.fl_str_mv Sixto-Costoya, A.
Ferrer-Sapena, Antonia
Aleixandre-Benavent, Rafael
Peset, Fernanda
Valderrama-Zurián, Juan Carlos
Petrosyan, Luiza
author Sixto-Costoya, A.
author_facet Sixto-Costoya, A.
Ferrer-Sapena, Antonia
Aleixandre-Benavent, Rafael
Peset, Fernanda
Valderrama-Zurián, Juan Carlos
Petrosyan, Luiza
author_role author
author2 Ferrer-Sapena, Antonia
Aleixandre-Benavent, Rafael
Peset, Fernanda
Valderrama-Zurián, Juan Carlos
Petrosyan, Luiza
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Addictions
Data sharing
Open data
Repositories
FAIR principles
topic Addictions
Data sharing
Open data
Repositories
FAIR principles
description The aim of this study is to assess the scientific data sharing in the field of addictions by applying FAIR principles. These principles play an important role, as they guarantee a minimum of findability, accessibility, interoperability and reusability of the shared data. They are one of the main measures to improve the integrity and quality of research data. For this study, three automated tools were used: the Data Citation Index (DCI) to capture datasets on addictions; Bibliometricos, proprietary software for data retrieval; and the F-UJI tool for the FAIR evaluation of datasets. The datasets on the most common addiction topics, such as alcohol, cannabis, tobacco, cocaine, opioids and stimulants, were downloaded by the DCI (5967 DOIs) and parsed into a database for subsequent analysis. In terms of datasets characteristics, alcohol, tobacco and opioids were the most productive. After assessment by F-UJI, none of the addictions analyzed reached an average of 30% FAIR compliance since all of them were between 20% and 29%. When analyzing each principle, Findable was the best scored principle (in a range of 40%–59%), followed by Accessible, Interoperable and Reusable. The results of our study show, first, an increasing number of shared datasets over the years, especially from basic studies. In terms of quality, there are issues that remain to be resolved, especially in relation to interoperability and reusability principles. This emphasizes the important role of adequate data sharing procedures in ensuring that datasets are FAIR compliant and usable in addiction research.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/406035
url http://hdl.handle.net/10261/406035
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI//PRE2020-092585
Sixto-Costoya, A.; Ferrer-Sapena, Antonia; Aleixandre-Benavent, Rafael; Peset, Fernanda; Valderrama-Zurián, Juan Carlos; Petrosyan, Luiza; 2023; The quality of datasets in the area of addictions (REPORTS) [Dataset]; Figshare; https://doi.org/10.6084/m9.figshare.23716287.v1
https://doi.org/10.1007/s11192-024-05227-5
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
Akadémiai Kiadó (Budapest)
publisher.none.fl_str_mv Springer
Akadémiai Kiadó (Budapest)
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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