A comparison of research data management platforms: architecture, flexible metadata and interoperability
A comparison of research data management platforms: architecture, flexible metadata and interoperability
复制标题
研究数据管理平台的比较：架构、灵活的元数据和互操作性
DOI：
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发表时间：
2016
影响因子：
2.4
通讯作者：
Cristina Ribeiro
中科院分区：
文献类型：
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作者：
R. C. Amorim;João Aguiar Castro;J. Silva;Cristina Ribeiro
研究数据管理正迅速成为研究人员经常关注的问题，机构需要为他们提供支持数据组织和出版准备的平台。一些机构采用了机构存储库作为数据存储的基础，而另一些机构正在试验更丰富的数据描述环境，尽管现有工作流程存在多样性。本文综合概述了当前可用于数据管理的平台。本文对数据管理采取了务实的观点，重点关注在工具和人力投资有限的科学长尾领域可以采用的解决方案。首先，提出了一套广泛的数据管理平台——其中一些是为机构存储库和数字图书馆设计的——以选择一个更有前途的数据管理平台的短列表。对这些平台的比较考虑了它们的架构、对元数据的支持、现有的编程接口以及它们的搜索机制和社区接受程度。在这个过程中，也要考虑到利益相关者的需求。结果表明，数据管理平台仍有很大的改进空间，主要体现在不同领域数据描述的特殊性，以及数据管理平台与现有研究管理工具集成的潜力。然而，根据环境的不同，一些平台可以满足所有或部分利益相关者的需求。
Research data management is rapidly becoming a regular concern for researchers, and institutions need to provide them with platforms to support data organization and preparation for publication. Some institutions have adopted institutional repositories as the basis for data deposit, whereas others are experimenting with richer environments for data description, in spite of the diversity of existing workflows. This paper is a synthetic overview of current platforms that can be used for data management purposes. Adopting a pragmatic view on data management, the paper focuses on solutions that can be adopted in the long tail of science, where investments in tools and manpower are modest. First, a broad set of data management platforms is presented—some designed for institutional repositories and digital libraries—to select a short list of the more promising ones for data management. These platforms are compared considering their architecture, support for metadata, existing programming interfaces, as well as their search mechanisms and community acceptance. In this process, the stakeholders’ requirements are also taken into account. The results show that there is still plenty of room for improvement, mainly regarding the specificity of data description in different domains, as well as the potential for integration of the data management platforms with existing research management tools. Nevertheless, depending on the context, some platforms can meet all or part of the stakeholders’ requirements.