在实验生物医学研究中数据管理和共享的最佳实践
Teresa Cunha-Oliveira1,2, John P A Ioannidis3,4, Paulo J Oliveira1,2
1Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.
Physiological reviews
|March 7, 2024
概括
有效的数据管理对于科学完整性和可重复性至关重要. 本综述提供了对组织,记录和共享实验生物医学数据的最佳实践的见解,以提高研究可信度和进展.
科学领域:
- 生物医学研究生物医学研究
- 数据科学数据科学数据科学
- 科学完整性 科学完整性
背景情况:
- 科学进步依赖于数据的完整性和可重复性.
- 有效的数据管理涉及组织,文档,存储,共享和保存.
- 强大的数据管理建立了可信度,有利于研究人员的职业生涯.
研究的目的:
- 为实验生物医学研究人员提供对数据管理实践的关键见解.
- 系统地呈现数据处理的资源和最佳实践.
- 为应对管理低通量实验数据的具体挑战.
主要方法:
- 审查原始和处理数据管理.
- 分析元数据和数据集类型 (高吞吐量与低吞吐量).
- 审查文档标准,报告准则和数据共享实践.
主要成果:
- 强调了通用文档语言的重要性.
- 讨论有效的数据管理系统和相关存储库.
- 强调研究实践中的透明度和问责制.
结论:
- 在实验生物医学中,全面的数据管理对于验证和累积知识至关重要.
- 资助机构越来越需要遵守标准,文件和数据共享.
- 实施最佳的数据管理实践可以确保科学发现的长期可访问性和可重复性.
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