图书情报工作 ›› 2022, Vol. 66 ›› Issue (10): 122-130.DOI: 10.13266/j.issn.0252-3116.2022.010.011

• 情报研究 • 上一篇    下一篇

结合计量分析和内容分析的科学数据集使用特征研究

杨宁1,2, 张志强1,2   

  1. 1. 中国科学院成都文献情报中心 成都 610041;
    2. 中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190
  • 收稿日期:2021-10-26 修回日期:2022-01-28 出版日期:2022-05-20 发布日期:2022-06-01
  • 通讯作者: 张志强,研究员,博士生导师,通信作者,E-mail:zhangzq@clas.ac.cn。
  • 作者简介:杨宁,副研究馆员,博士研究生。
  • 基金资助:
    本文系国家社会科学基金重点项目"面向领域知识发现的学科信息学理论与应用研究"(项目编号:17ATQ008)研究成果之一。

Research on the Use Characteristics of Scientific Datasets Combined with Quantitative Analysis and Content Analysis

Yang Ning1,2, Zhang Zhiqiang1,2   

  1. 1. Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041;
    2. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
  • Received:2021-10-26 Revised:2022-01-28 Online:2022-05-20 Published:2022-06-01

摘要: [目的/意义]从计量分析和内容分析两个视角对科学数据集的使用特征进行研究,定量化评估科学数据集对学科发展的影响,为科学数据管理服务及政策研究提供参考。[方法/过程]综合运用文本挖掘和文献计量方法对PubMed Central的全文文献进行分析,从时间分布、使用强度等7个方面全面考察科学数据集的使用情况,并在此基础上评估科学数据集对学科发展产生的实际影响。[结果/结论]研究结果表明,科学数据集对生物医学领域科研产生的影响力与日俱增,数据出版和高水平期刊促进了科学数据集的开放和共享,科学数据集的使用集中在论文的后半部分且正式引用较少,相应的标准规范还有待进一步加强。

关键词: 计量分析, 内容分析, 科学数据集, 使用特征

Abstract: [Purpose/Significance] This paper analyzes the use characteristics of scientific datasets from the perspective of quantitative analysis and content analysis, quantitatively evaluates the impact of scientific datasets on discipine development, and provides references for scientific data management services and policy research.[Method/Process] Methods of text mining and bibliometric were used to analyze the full-text literature in PubMed Central, this study comprehensively investigated the use of scientific datasets from 7 aspects such as time distribution and use intensity, and on this basis, evaluated the actual impact of scientific datasets on discipline development.[Result/Conclusion] The research results show that the influence of scientific datasets on scientific research in the biomedical field is increasing with each passing day. Data publishing and high-level journals promote the opening and sharing of scientific datasets. The use of scientific datasets is concentrated in the second half of the paper and there are few formal references. The corresponding standards and specifications need to be further strengthened.

Key words: quantitative analysis, content analysis, scientific dataset, use characteristics

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