中国科技期刊研究 ›› 2023, Vol. 34 ›› Issue (10): 1328-1337. doi: 10.11946/cjstp.202308230683

• 评价与分析 • 上一篇    下一篇

基于中国科学引文数据库的中国科技期刊论文科学数据引用特征研究

陈莉玥1)()(), 马娜1), 刘筱敏1,2),*()()   

  1. 1)中国科学院文献情报中心,北京市海淀区北四环西路33号 100190
    2)中国科学院大学经济与管理学院信息资源管理系,北京市海淀区中关村东路80号 100190
  • 收稿日期:2023-08-23 修回日期:2023-09-01 出版日期:2023-10-15 发布日期:2023-10-30
  • 通讯作者: *刘筱敏(ORCID:0000-0002-4438-008X),研究馆员,硕士生导师,E-mail:liuxm@mail.las.ac.cn。
  • 作者简介:

    陈莉玥(ORCID:0000-0001-9039-6851),博士,馆员,E-mail:;

    马 娜,博士,副研究馆员。

    作者贡献声明: 陈莉玥:提出研究思路,设计研究方案,撰写、修订论文; 马 娜:提出研究方向,设计论文框架,修订论文; 刘筱敏:设计研究方案和论文框架,修订论文。
  • 基金资助:
    中国科学院科普与期刊出版项目“数字化平台建设”(E329140801); 中国科学院特别研究助理资助项目(E229140101)

Scientific data citation characteristics of Chinese scientific journal papers based on Chinese Science Citation Database

CHEN Liyue1)()(), MA Na1), LIU Xiaomin1,2)()()   

  1. 1) National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu, Haidian District, Beijing 100190, China
    2) Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, 80 East Zhongguancun Road, Haidian District, Beijing 100190, China
  • Received:2023-08-23 Revised:2023-09-01 Online:2023-10-15 Published:2023-10-30

摘要:

【目的】 对中国科技期刊论文的科学数据引用情况进行量化分析,探究我国科技期刊论文实施数据引用的效果,分析数据引用标准和科技期刊管理政策对数据引用行为的影响。【方法】 以中国科学引文数据库收录的论文为基础,选取参考文献列表中的科学数据引用文本为研究对象,从引用基础特征、引用数据来源、引用元数据要素及数据类型3个定量维度和案例期刊对比定性维度展开分析。【结果】 我国科技期刊论文科学数据的被引频次相对较少但近年来逐渐增长,各学科领域的科学数据引用倾向存在差异,科学数据引用格式与国家标准规范还存在较大差距,数据开放共享正在改变科研论文对各类科学数据的引用趋势。【结论】 应增强科研人员数据引用意识,完善期刊数据引用细则,以学科领域期刊学会为单位细化引用规范,加强科技期刊与国家自主数据资源标识体系合作。

关键词: 科学数据, 数据引用, 引用特征, 引用标准

Abstract:

[Purposes] This paper aims to quantitatively analyze the scientific data citations of Chinese scientific journal papers, explore their implementation effect in data citation, and investigate the impact of data citation standards and scientific journal management policies on data citation behavior.[Methods] Based on the papers included in the Chinese Science Citation Database, we selected the scientific data citation texts in the reference list as the research object and conducted an analysis of data citations from three quantitative dimensions including basic citation features, data source, and cited metadata elements and data types, as well as a qualitative dimension of case journal comparison. [Findings] The scientific data citations of China's scientific journal papers are relatively few, while in recent years they have shown an overall growth trend. Additionally, there are differences in the citation tendency in various disciplines. The scientific data citation format is far from meeting the requirements of national standards, while open data sharing is changing the trend of scientific research papers citing various scientific data.[Conclusions] Data citation awareness of researchers should be enhanced, detailed rules for journal data citations should be improved, the citation norms should be refined based on journal society in various disciplines, and the cooperation between scientific journals and the data resource identification system of China should be strengthened.

Key words: Scientific data, Data citation, Citation characteristic, Citation standard