开放生物学家的第二份工作中的日常生活,作为数据管理员
Livia C T Scorza1, Tomasz Zieliński1, Irina Kalita1,2,3
1Centre for Engineering Biology and School of Biological Sciences, University of Edinburgh, Edinburgh, Scotland, EH9 3BF, UK.
Wellcome open research
|October 3, 2024
概括
实施FAIR数据原则对于研究至关重要. 本研究为实验研究人员提供了实用策略,以提高数据的可重复使用性和影响力,简化从创建到共享的数据管理.
科学领域:
- 生命科学 生命科学
- 生物学研究生物学研究
- 数据科学数据科学数据科学
背景情况:
- 数据的可重复使用性对于研究数据生命周期至关重要,但实际实施仍然具有挑战性.
- 公开共享的数据集往往不完整或无法重复使用,阻碍了科学进步.
- 实现FAIR (可查找,可访问,可互操作,可重复使用) 数据原则在生物学中面临障碍,原因是数据类型多样化和缺乏标准化实践.
研究的目的:
- 为实验研究人员提供管理和共享可重复使用数据集的实用策略.
- 为出版作者弥合数据生成和数据共享之间的差距.
- 简化研究数据管理,提高数据可见性和影响.
主要方法:
- 与实验研究人员直接合作,了解他们的数据管理需求.
- 详细描述组织数据集的过程,从创建到共享.
- 推工具,策略和网络资源,以最大限度地提高数据的可重复使用性和生产力.
主要成果:
- 一个简化的研究数据管理方法对实验人员的挑战.
- 通过改进数据共享,提高数据的可见性,识别和影响.
- 实用示例和资源,以促进 FAIR 数据的实施.
结论:
- 拟议的战略简化了实验研究人员的数据管理.
- 这种方法促进了公平的数据共享,使更广泛的科学界受益.
- 有效的数据管理提高了研究的可见性和科学影响.
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