通过提供从数据生成到数据发布的数字工作流来增强FAIRdata:描述了循环电压测量的开源方法
David Herrmann1, Patrick Hodapp2, Martin Starman1
1Institute of Biological and Chemical Systems, Functional Molecular Systems (IBCS), Karlsruhe Institute of Technology Kaiserstraße 12 76131 Karlsruhe Germany nicole.jung@kit.edu stefan.braese@kit.edu https://ror.org/04t3en479.
Chemical science
|February 7, 2025
概括
本研究介绍了一种开源工作流程,用于标准化各种分析数据,如循环电压测量,确保FAIR数据原则. 可适应的方法支持数字化研究的整个数据生命周期.
科学领域:
- 化学 化学 化学
- 数据科学数据科学数据科学
- 科学研究 科学研究
背景情况:
- 分析数据通常存在于多种不同,非标准化的格式中,阻碍了FAIR (可查找,可访问,可互操作,可重复使用) 数据原则.
- 缺乏共同的数据和元数据标准使研究数据管理和跨学科共享变得复杂.
研究的目的:
- 开发和介绍一个工作流程,用于将非标准化,专有分析数据转换为具有丰富元数据的开放,标准化格式.
- 支持数据的整个生命周期,从测量到存储库中的发布,促进公平的数据处理.
- 为可重复和可访问的科学数据管理提供开源工具和基础设施.
主要方法:
- 使用循环电压测量作为数据格式标准化的例子.
- 开发了一种工作流程,包括数据处理和元数据注释的概念,软件和基础设施.
- 将所有工作流组件作为开源提供,以促进采用和重复使用.
主要成果:
- 成功地将非标准化的循环电压测量数据转化为开放的,标准化的数据,并注释了全面的元数据.
- 建立了一个完整的数据生命周期支持系统,从数据生成到仓库发布.
- 为数据管理创建了可重复使用的开源组件.
结论:
- 提出的工作流有效地解决了各种分析数据格式的挑战,使FAIR数据原则成为可能.
- 工作流的开源性质促进了其在各种实验室和不同测量类型的采用和适应.
- 这种方法促进了数字化研究,并增强了科学数据收集的数据管理实践.
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