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在德国生物信息学基础设施网络(de.NBI)中实施 FAIR 数据管理,以选定的用例为例。

Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases.

机构信息

Ruhr University Bochum, Faculty of Medicine, Medizinisches Proteom-Center, Bochum, Germany.

Ruhr University Bochum, Center for Protein Diagnostics (ProDi), Medical Proteome Analysis, Bochum, Germany.

出版信息

Brief Bioinform. 2021 Sep 2;22(5). doi: 10.1093/bib/bbab010.

Abstract

This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.

摘要

本文描述了一些使用案例研究和 de.NBI 服务的 FAIR 状态自评,以说明在大型分布式生物信息学基础设施中定义遵守 FAIR(可发现、可访问、可互操作和可重用)数据原则的需求所面临的挑战和要求。我们应对湿实验室技术、数据、元数据、软件、计算工作流程以及不同生物信息学子学科中 FAIR 原则的实施和监测水平的异构性的挑战,这些子学科联合在 de.NBI 中。一方面,这种广泛的服务领域和优秀的专家网络是制定有用的研究数据管理计划的坚实基础。另一方面,由分布式团队维护的大量工具和技术使得 FAIR 的合规性具有挑战性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6645/8425304/db335f322ff3/bbab010f1.jpg

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