比较使用研究资源标识符和自然语言处理来引用数据库,软件和其他数字文物
Chun-Nan Hsu1, Anita E Bandrowski2, Thomas H Gillespie1
1University of California San Diego.
Computing in science & engineering
|August 12, 2025
概括
研究资源标识符 (RRID) 改善了科学文献中数字资源的跟踪. 将RRID与文本挖掘相结合,为准确的数字资源引用提供了一个可扩展的解决方案.
科学领域:
- 生物医学信息学 生物医学信息学
- 科学出版科学出版
- 数据科学数据科学数据科学
背景情况:
- 研究资源标识符 (RRID) 于2014年建立,以提高研究资源的可追溯性.
- 准确引用数据库和软件等数字资源对于可复制性至关重要.
研究的目的:
- 提供RRID的概述,并分析它们在识别数字资源方面的有效性.
- 为了比较RRID策划工作流程与自动化文本挖掘系统的性能.
主要方法:
- 量化比较RRID策划工作流输出与文本挖掘系统输出.
- 对作者遵守RRID报告准则的分析.
- 展示RRID和文本挖掘对资源引用的互补作用.
主要成果:
- 作者通常很好地遵守RRID报告准则.
- 基于自然语言处理的文本挖掘成功地识别了大多数与RRID相关的资源以及许多额外的资源.
- RRID和文本挖掘显示出一种协同作用的关系.
结论:
- RRID是有效的识别数字资源,与良好的作者合规性.
- 文本挖掘显著提高了研究资源的识别超出RRID-only方法.
- 整合RRID和文本挖掘为数字资源引用提供了强大的和可扩展的方法.
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