A generalist institutional data repository offering both open and restricted access to support NIH data sharing compliance.

IF 1.7 4区 医学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Journal of the Medical Library Association Pub Date : 2026-04-01 Epub Date: 2026-04-13 DOI:10.5195/jmla.2026.2339
Seonyoung Kim, Xing Jian, Marcy L Vana
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引用次数: 0

Abstract

In response to the 2023 NIH Data Management and Sharing (DMS) Policy, Washington University School of Medicine in St. Louis launched Digital Commons Data@Becker, a generalist institutional data repository supporting both open and restricted access to research data. Managed by Bernard Becker Medical Library's DMS Team, the repository offers a fully mediated curation workflow that guides researchers through consultation, metadata capture, documentation, and quality control. Draft Digital Object Identifiers (DOIs) can be issued once access type is determined, with final DOI publication following curation and QC. Restricted datasets require Human Research Protection Office (HRPO) review and Data Transfer and Use Agreements (DTUAs), while open access datasets are freely downloadable. The repository leverages persistent identifiers such as Open Researcher and Contributor ID (ORCID iDs), Research Organization Registry (ROR) IDs, and DOIs, along with the DataCite metadata schema and custom metadata fields. Since its launch in 2023, Digital Commons Data@Becker has published 30 datasets spanning biomedical imaging, sequencing, quantitative assays, flow cytometry, and qualitative survey data. Across all datasets, there have been 4,409 views and 4,120 files downloaded, with restricted datasets generating 13 access requests, three of which were granted through DTUAs. Researchers emphasize the value of free institutional curation, flexible access models, and rapid DOI assignment. Digital Commons Data@Becker demonstrates how a generalist institutional data repository can balance accessibility and security to support NIH compliance, while advancing FAIR (Findable, Accessible, Interoperable, Reusable) data sharing and long-term stewardship.

一个通用的机构数据存储库,提供开放和限制访问,以支持NIH数据共享合规性。
为了响应2023年美国国立卫生研究院数据管理和共享(DMS)政策,圣路易斯华盛顿大学医学院推出了数字共享Data@Becker,这是一个通用的机构数据存储库,支持对研究数据的开放和限制访问。该存储库由Bernard Becker医学图书馆的DMS团队管理,提供了一个完全中介的管理工作流程,通过咨询、元数据捕获、文档和质量控制来指导研究人员。一旦确定了访问类型,就可以发布数字对象标识符(DOI)草案,并在管理和质量控制之后发布最终DOI。限制性数据集需要人类研究保护办公室(HRPO)审查和数据传输和使用协议(DTUAs),而开放获取数据集可免费下载。存储库利用持久的标识符,如Open Researcher和Contributor ID (ORCID ID)、Research Organization Registry (ROR) ID和doi,以及DataCite元数据模式和自定义元数据字段。自2023年推出以来,Digital Commons Data@Becker已经发布了30个数据集,涵盖生物医学成像、测序、定量分析、流式细胞术和定性调查数据。在所有数据集中,有4,409个视图和4,120个文件被下载,受限制的数据集产生了13个访问请求,其中3个是通过dtua授予的。研究人员强调了免费机构管理、灵活的访问模式和快速DOI分配的价值。Digital Commons Data@Becker展示了一个通用的机构数据存储库如何平衡可访问性和安全性,以支持NIH合规性,同时推进FAIR(可查找、可访问、可互操作、可重用)数据共享和长期管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of the Medical Library Association
Journal of the Medical Library Association INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
4.10
自引率
10.00%
发文量
39
审稿时长
26 weeks
期刊介绍: The Journal of the Medical Library Association (JMLA) is an international, peer-reviewed journal published quarterly that aims to advance the practice and research knowledgebase of health sciences librarianship. The most current impact factor for the JMLA (from the 2007 edition of Journal Citation Reports) is 1.392.
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