Unveiling the dynamics of research data management: Insights from bibliometric and BERTopic analysis

IF 2.3 3区管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

Journal of Academic Librarianship Pub Date : 2025-08-28 DOI:10.1016/j.acalib.2025.103126

Ye Yuan, A.M.K. Yanti Idaya, A. Noorhidawati, Yi-Shuai Xu, Guan Wang

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引用次数: 0

Abstract

With the continuous progress of open science and the refinement of research data policies, research data management has become an important component of the modern scientific ecosystem. This study aims to: (i) systematically analyze the publication characteristics of RDM-related research, (ii) identify its key research topics and to reveal its semantic structures and thematic features. To achieve this, a combination of bibliometric analysis and BERTopic-based topic modeling was applied to 1154 RDM-related articles indexed in the Web of Science database from 2005 to 2024. The results show a notable increase in RDM research outputs since the FAIR principles were introduced in 2016, with journals coming from the fields of library science, information science, and medical informatics highlighting the interdisciplinary nature of the field. Analysis of international collaboration shows that the United States, the United Kingdom, and Germany occupy a central position, with increasingly diverse patterns of global collaboration. The BERTopic modeling identified 18 representative topics, which were divided into four semantically coherent research directions: Cluster 1 focuses on institutional services, capacity development, and platform support; Cluster 2 focuses on data citation, research assessment, and collaboration networks, emphasizing the role of RDM in assessing impact and scholarly collaboration; Cluster 3 addresses data sharing, reuse and misuse, highlighting governance challenges related to data use norms and risk control; Cluster 4 covers open science strategies, open access publishing and journal data policies, highlighting how RDM is increasingly embedded in scholarly communication. This study fills gaps in previous reviews on subject hierarchy and semantic modeling and provides theoretical insights and methodological support for strengthening research data governance and fostering interdisciplinary collaboration.

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揭示研究数据管理的动态：来自文献计量学和BERTopic分析的见解

随着开放科学的不断推进和科研数据政策的不断细化，科研数据管理已成为现代科学生态系统的重要组成部分。本研究旨在：(1)系统分析rdm相关研究的发表特征；(2)确定rdm的重点研究课题，揭示rdm的语义结构和主题特征。为了实现这一目标，将文献计量分析和基于bertopic的主题建模相结合，应用于2005年至2024年在Web of Science数据库中索引的1154篇rdm相关文章。结果显示，自2016年引入FAIR原则以来，RDM研究产出显著增加，来自图书馆学、信息科学和医学信息学领域的期刊突出了该领域的跨学科性质。国际合作分析显示，美国、英国和德国占据中心地位，全球合作模式日益多样化。BERTopic模型确定了18个代表性主题，并将其划分为四个语义一致的研究方向：集群1侧重于机构服务、能力发展和平台支持；集群2侧重于数据引用、研究评估和合作网络，强调RDM在评估影响和学术合作中的作用；集群3解决数据共享、重用和滥用问题，强调与数据使用规范和风险控制相关的治理挑战；集群4涵盖了开放科学策略、开放获取出版和期刊数据政策，突出了RDM如何越来越多地嵌入到学术交流中。本研究填补了以往研究在学科层次和语义建模方面的空白，为加强研究数据治理和促进跨学科合作提供了理论见解和方法支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Academic Librarianship INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

5.30

自引率

15.40%

发文量

120

审稿时长

29 days

期刊介绍： The Journal of Academic Librarianship, an international and refereed journal, publishes articles that focus on problems and issues germane to college and university libraries. JAL provides a forum for authors to present research findings and, where applicable, their practical applications and significance; analyze policies, practices, issues, and trends; speculate about the future of academic librarianship; present analytical bibliographic essays and philosophical treatises. JAL also brings to the attention of its readers information about hundreds of new and recently published books in library and information science, management, scholarly communication, and higher education. JAL, in addition, covers management and discipline-based software and information policy developments.