中国科技期刊研究 ›› 2025, Vol. 36 ›› Issue (9): 1198-1209. doi: 10.11946/cjstp.202507030793

• 质量建设 • 上一篇    下一篇

科学数据重用研究的问题及建议

徐琳宏1)()(), 周嘉怡1), 林原2)   

  1. 1) 大连外国语大学软件学院,辽宁省大连市旅顺口区旅顺南路西段6号 116044
    2) 大连理工大学公共管理学院,辽宁省大连市高新区凌工路2号 116024
  • 收稿日期:2025-07-03 出版日期:2025-09-25 发布日期:2025-10-28
  • 作者简介:

    徐琳宏(ORCID: 0000-0001-9805-3554),博士,副教授,硕士研究生导师,E-mail:

    周嘉怡,硕士研究生

    林 原,博士,副教授,硕士研究生导师。

    作者贡献声明: 徐琳宏:提出研究选题,设计研究思路,撰写与修订论文; 周嘉怡:收集数据,撰写论文; 林 原:提出修改意见,论文审阅与修订。
  • 基金资助:
    2025年教育部人文社科规划基金“生成式人工智能赋能的论文贡献测度研究”

Challenges and recommendations in the research of scientific data reuse

XU Linhong1)()(), ZHOU Jiayi1), LIN Yuan2)   

  1. 1) School of Software,Dalian University of Foreign Languages,6 West Section of Lüshun South Road,Lüshunkou District,Dalian 116044,China
    2) School of Public Administration,Dalian University of Technology,2 Linggong Road,Hi-Tech Zone,Dalian 116024,China
  • Received:2025-07-03 Online:2025-09-25 Published:2025-10-28

摘要:

目的 系统梳理科学数据共享与重用的研究现状,为提升数据重用水平和推动科研创新提供参考。方法 基于Leont’ev行动理论,从“为何重用”“重用什么”“如何重用”3 阶段综述数据重用的相关研究。以2015—2024年CNKI和WoS上与数据重用相关的文献为研究对象,初步精炼数据重用领域的关键研究链条。结果 动机层面,存在“重共享轻重用”问题,数据共享受制度与道德驱动,已有主客观系统分析,而重用动机仍关注表层;在行动层面,决策聚焦数据的易获取、易用性与可信性;在操作层面,数据重用的学科差异显著,数据引用受限于自动化识别技术瓶颈,特征分析焦点过于集中。结论 通过构建数据协同治理体系与学科分级策略,以技术和制度创新驱动,提升数据重用效能。

关键词: 数据重用, 数据共享, 数据引用, 引用行为

Abstract:

Purposes This study aims to systematically review the current state of research on scientific data sharing and reuse, providing insights to enhance data reuse efficiency and promote scientific innovation. Methods Based on Leont’ev’s activity theory, the research on data reuse is reviewed from three dimensions: “why to reuse” “what to reuse”and “how to reuse”. Using literature related to data reuse from CNKI and WoS (from 2015 to 2024) as the research sample, key research chains in the field of data reuse are preliminarily refined. Findings First, at the motivational level, there is an imbalance between “emphasizing sharing over reuse”. Data sharing is driven by institutional and ethical factors and has been analyzed both subjectively and systematically, while reuse motivations remain superficial. Second, at the decision-making level, actions focus on data accessibility, usability, and credibility. Third, at the operational level, significant disciplinary differences exist in data reuse practices. Data citation is constrained by bottlenecks in automated identification technologies, and feature analysis tends to be overly concentrated. Conclusions By establishing a collaborative data governance system and implementing disciplinary grading strategies, driven by technological and institutional innovations, the efficiency of data reuse can be enhanced.

Key words: Data reuse, Data sharing, Data citation, Citing behavior