通过目录进行数据管理:一个独立于存储库的数据发现模型

Helenmary Sheridan, Anthony J. Dellureficio, Melissa A. Ratajeski, Sara Mannheimer, Terrie R. Wheeler
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引用次数: 4

摘要

机构数据存储库是公认的学术图书馆数据管理平台的黄金标准。但并不是每个机构都能维持一个存储库,由于法律、道德或授权的限制,也不是每个数据集都能存档。数据目录是研究数据的纯元数据索引,提供详细的访问说明和使用条件,是一种潜在的解决方案,可能特别适合“具有挑战性”的数据集。本文介绍了数据目录在提高研究数据的可发现性和可访问性方面的优势。作者认为,数据目录是数据存储库的一种可行的替代或补充,并提供了他们机构经验的例子,以展示他们的数据目录如何满足特定的管理要求。文章还报告了数据目录和数据发现倡议实践社区的发展情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Curation through Catalogs: A Repository-Independent Model for Data Discovery
Institutional data repositories are the acknowledged gold standard for data curation platforms in academic libraries. But not every institution can sustain a repository, and not every dataset can be archived due to legal, ethical, or authorial constraints. Data catalogs—metadata-only indices of research data that provide detailed access instructions and conditions for use—are one potential solution, and may be especially suitable for "challenging" datasets. This article presents the strengths of data catalogs for increasing the discoverability and accessibility of research data. The authors argue that data catalogs are a viable alternative or complement to data repositories, and provide examples from their institutions' experiences to show how their data catalogs address specific curatorial requirements. The article also reports on the development of a community of practice for data catalogs and data discovery initiatives.
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