数据管理计划的公平性:对一些欧洲dmp的评估

Patrícia Henning, Luis Olavo Bonino Da Silva, L. F. Pires, M. V. Sinderen, J. Moreira
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引用次数: 2

摘要

FAIR原则已经成为学术和科学界的数据管理工具,因为它们提供了一套指导原则,为数据和元数据管理带来可查找性、可访问性、互操作性和可重用性。自2016年《科学数据-自然》正式发表以来,这些原则得到了全世界的认可,并迅速得到认可和采纳,成为数据管理和研究政策的基石。然而,当付诸实践时,它们偶尔会导致组织、法律和技术方面的挑战,从而导致对实施它们的努力是否值得的怀疑和不确定性。发布后不久,欧盟委员会和其他资助机构开始要求项目提案包括基于公平原则的数据管理计划(DMP)。本文报告了DMP对公平原则的遵守,批判性地评估了十个欧洲DMP模板。我们观察到,目前大多数dmp的公平性只是部分令人满意,因为它们解决了数据最佳实践、可查找性、可访问性和有时保存问题,但对元数据和互操作性的关注要少得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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