The FAIRness of data management plans: an assessment of some European DMPs

The FAIR principles have become a data management instrument for the academic and scientific community, since they provide a set of guiding principles to bring findability, accessibility, interoperability and reusability to data and metadata stewardship. Since their official publication in 2016 by S...

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Detalles Bibliográficos
Autores: Henning, Patricia, da Silva, Luis Olavo Bonino, Pires, Luís Ferreira, Sinderen, Marten van, Moreira, João Luís Rebelo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:Brasil
Institución:Fundação Oswaldo Cruz (FIOCRUZ)
Repositorio:RECIIS (Online)
Idioma:inglés
OAI Identifier:oai:www.reciis.icict.fiocruz.br:article/2270
Acceso en línea:https://www.reciis.icict.fiocruz.br/index.php/reciis/article/view/2270
Access Level:acceso abierto
Palabra clave:Data Management Plan
FAIR Principles
Research Data
Data Management.
Plan de Gestión de Datos
Principios FAIR
Datos de investigación
Gestión de datos.
Descripción
Sumario:The FAIR principles have become a data management instrument for the academic and scientific community, since they provide a set of guiding principles to bring findability, accessibility, interoperability and reusability to data and metadata stewardship. Since their official publication in 2016 by Scientific Data – Nature, these principles have received worldwide recognition and have been quickly endorsed and adopted as a cornerstone of data stewardship and research policy. However, when put into practice, they occasionally result in organisational, legal and technological challenges that can lead to doubts and uncertainty as to whether the effort of implementing them is worthwhile. Soon after their publication, the European Commission and other funding agencies started to require that project proposals include a Data Management Plan (DMP) based on the FAIR principles. This paper reports on the adherence of DMPs to the FAIR principles, critically evaluating ten European DMP templates. We observed that the current FAIRness of most of these DMPs is only partly satisfactory, in that they address data best practices, findability, accessibility and sometimes preservation, but pay much less attention to metadata and interoperability.