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FAIR EVA:将机构多学科知识库纳入 FAIR 计划。

FAIR EVA: Bringing institutional multidisciplinary repositories into the FAIR picture.

机构信息

CSIC (Spanish National Research Council), Institute of Physics of Cantabria (IFCA), Santander, Spain.

CSIC (Spanish National Research Council), DIGITAL.CSIC, URICI, Madrid, Spain.

出版信息

Sci Data. 2023 Nov 4;10(1):764. doi: 10.1038/s41597-023-02652-8.

Abstract

The FAIR Principles are a set of good practices to improve the reproducibility and quality of data in an Open Science context. Different sets of indicators have been proposed to evaluate the FAIRness of digital objects, including datasets that are usually stored in repositories or data portals. However, indicators like those proposed by the Research Data Alliance are provided from a high-level perspective that can be interpreted and they are not always realistic to particular environments like multidisciplinary repositories. This paper describes FAIR EVA, a new tool developed within the European Open Science Cloud context that is oriented to particular data management systems like open repositories, which can be customized to a specific case in a scalable and automatic environment. It aims to be adaptive enough to work for different environments, repository software and disciplines, taking into account the flexibility of the FAIR Principles. As an example, we present DIGITAL.CSIC repository as the first target of the tool, gathering the particular needs of a multidisciplinary institution as well as its institutional repository.

摘要

FAIR 原则是一套在开放科学环境中提高数据可重复性和质量的良好实践。已经提出了不同的指标集来评估数字对象的 FAIR 程度,包括通常存储在存储库或数据门户中的数据集。然而,像研究数据联盟提出的那些指标是从高层次的角度提供的,可以进行解释,而且它们并不总是适用于像多学科存储库这样的特定环境。本文描述了 FAIR EVA,这是在欧洲开放科学云环境中开发的一个新工具,它面向特定的数据管理系统,如开放存储库,可以在可扩展和自动的环境中针对特定情况进行定制。它旨在足够灵活以适应不同的环境、存储库软件和学科,同时考虑到 FAIR 原则的灵活性。作为一个例子,我们提出了 DIGITAL.CSIC 存储库作为该工具的第一个目标,它收集了一个多学科机构及其机构存储库的特殊需求。

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