根据FAIR原则提供COVID-19相关研究数据的可用性和质量:一项元研究研究
Ahmad Sofi-Mahmudi1,2, Eero Raittio3,4, Yeganeh Khazaei5
1National Pain Centre, Department of Anesthesia, McMaster University, Hamilton, ON, Canada.
PloS one
|November 18, 2024
概括
COVID-19研究数据显示,公平性很低,特别是在互操作性和可重复使用性方面. 数据共享存储库需要改进,以提高可查找性,可访问性,互操作性和可重复使用性,以促进科学进步.
科学领域:
- 数据科学数据科学数据科学
- 图书统计学 图书统计学
- 传染病研究 传染病研究
背景情况:
- 公平原则 (可查找,可访问,可互操作,可重复使用) 指导科学数据的共享.
- 随着COVID-19的流行,大量的研究和出版物被激发,需要进行数据共享评估.
- 之前对COVID-19研究数据的评估缺乏公平性.
研究的目的:
- 调查COVID-19研究中开放数据的可用性.
- 评估COVID-19研究数据是否符合FAIR原则.
主要方法:
- 在PubMed中搜索了开放访问的COVID-19文章 (2020年1月至2023年6月).
- 使用自动化工具 (metareadr,rtransparent) 来识别和选与文章相关的数据库.
- 使用F-UJI和rfuji评估FAIRness,通过线性回归分析影响得分的因素.
主要成果:
- 分析了来自通用存储库的5700个URL;平均公平度得分为9.4/22.
- 可查找率为100%,但可访问性 (21.5%),互操作性 (46.7%) 和可重复使用性 (61.3%) 较低.
- 存储库类型显著影响了 FAIRness 评分 (R2=0.809);哈佛数据源得分最高,GitHub得分最低.
结论:
- 对于改善COVID-19数据所有原则的公平性,存在很大的潜力.
- 在一般数据存储库中,互操作性和可重复使用性需要特别注意.
- 存储库的选择是数据公平性的关键决定因素.
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