实现透明的研究评估:使用公共NIH元数据检索历史RCR的方法
Fabian Haupt1, Jan F Senge2,3, Hendrik von Tengg-Kobligk1
1Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
PloS one
|January 20, 2026
概括
研究人员现在可以访问历史的相对引用率 (RCR) 数据,这是出版影响力的关键指标,这要归功于基于Python的新方法. 这促进了透明的研究评估,符合DORA原则.
科学领域:
- 图书统计学 图书统计学
- 研究评估研究评估
- 科学出版科学出版
背景情况:
- 关于研究评估的宣言 (DORA) 强调需要改进研究成果评估.
- 国家卫生研究院 (NIH) 引入了相对引用率 (RCR) 作为出版物影响力指标.
- 历史RCR数据存在于NIH数据库中,但研究人员无法轻松访问.
研究的目的:
- 开发一种用于重建和访问历史相对引用率 (RCR) 数据的方法.
- 为了使研究人员能够随着时间的推移查看RCR值.
- 支持更加透明和负责任的学术评价.
主要方法:
- 使用基于Python的方法从NIH数据库中提取RCR数据.
- 该方法重建了自数据库创建以来的所有时间点的RCR值.
- 使用数据可视化技术绘制RCR趋势图.
主要成果:
- 成功重建了以其他方式无法访问的历史RCR数据.
- 证明了恢复历史文献信息的可行性.
- 启用了每个时间点的RCR值的绘图.
结论:
- 开发的方法可以访问历史的RCR数据,提高研究评估的透明度.
- 这项工作符合DORA和开放科学倡议的目标.
- 促进学术界更负责任地使用文献计量指标.
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