DataLad:用于共同管理代码,数据及其关系的分布式系统.
Yaroslav O Halchenko1, Kyle Meyer1, Benjamin Poldrack2
1Center for Open Neuroscience, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
Journal of open source software
|October 29, 2024
概括
DataLad是一个开源工具,通过整合代码和数据版本管理来简化研究数据管理 (RDM). 它通过简化数据共享和来源跟踪来增强科学可重复性和FAIR数据原则.
科学领域:
- 计算科学 计算科学
- 数据科学数据科学数据科学
- 研究 软件工程 软件工程
背景情况:
- 有效管理和共享研究数据对于科学可重复性和协作至关重要.
- 现有的工具经常与大型数据集扎,版本复杂的数据对象关系,并捕获来源.
- 分散的方法提供灵活性,但需要强大的管理系统.
研究的目的:
- 介绍DataLad,一个基于Python的工具,用于统一管理代码,数据及其关系.
- 提高科学可重复性和遵守 FAIR 数据原则.
- 为研究数据管理 (RDM) 提供灵活,分散的平台.
主要方法:
- 利用git-annex进行数据后勤和git进行版本控制.
- 为方便使用提供Python和命令行接口.
- 具有可扩展的架构,支持与现有工具和工作流程集成.
主要成果:
- DataLad简化了任何大小或类型的数据的消费,发布和更新.
- 它允许精确的版本和管理数据作为轻量级依赖关系.
- 捕获可操作的过程来源,用于自动重新计算,提高可重现性.
结论:
- DataLad提供了一个开放的开放平台,用于灵活,分散的RDM.
- 它使数据管理与代码管理一样简单.
- 该工具是跨平台的,可以轻松地集成到现有研究环境中.
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