如何使用DataLad建立和维护多式动物研究数据集?
Aref Kalantari1, Michał Szczepanik2, Stephan Heunis2
1University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany.
Scientific data
|June 5, 2023
概括
这项研究引入了一种具有成本效益的工作流程,用于共享可再生动物研究数据. 它允许使用版本控制和开放平台进行安全的数据管理和协作,促进 FAIR 数据原则.
科学领域:
- 动物研究是动物研究.
- 数据科学是数据科学.
- 生物信息学是一种生物信息学.
背景情况:
- 分享实验数据和处理工具至关重要,但在动物研究中很少实施.
- 现有的FAIR指南和出版商的要求强调了需要更好的数据管理.
- 缺乏标准化的协议阻碍了大型多式联络数据集中的协作和可重复性.
研究的目的:
- 介绍一个版本控制和远程协作的大型多式联络动物研究数据集的逐步协议.
- 确保数据安全,并促进采用FAIR数据物流和处理工作流程.
- 为各种研究领域提供可重复的数据处理基础设施.
主要方法:
- 实施数据安全的数据管理计划和统一的文件/文件结构.
- 使用DataLad进行数据更改和版本控制的自动跟踪.
- 在研究数据平台GIN上共享所有数据,以实现可访问性和协作.
主要成果:
- 开发了一种简单,具有成本效益的工作流程,用于管理和共享大型,多模式的动物研究数据.
- 启用了对数据修改的自动跟踪,并促进了远程协作.
- 提供原始和处理过的数据,支持数据处理步骤的独立复制.
结论:
- 提出的工作流简化了FAIR数据的物流和动物研究的处理.
- 这种基础设施支持收集异质获取的数据集,并提高可重现性.
- 该协议作为改善跨研究站点和学科数据处理的蓝图.
相关概念视频
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