A Scientometric Analysis of Global Trends in Research Data Management Practices

Abstract

Aim: Research Data Management (RDM) has
developed as a critical field of scholarly attention in response to
the rising significance of data-intensive research, open art
initiatives, and the evolving demands of data stewardship.
Methodology: This theoretical investigation presents an
inclusive scientometric examination of global trends, patterns,
and thematic developments in RDM research from 2015 to 2024.
Drawing data from the Web of Science (WoS) and Scopus
databases, this research employed quantitative techniques using
tools, such as VOSviewer and Bibliometrics (R-package) to
analyze publication volume, citation impact, co-authorship
networks, country and institutional contributions, and keyword
co-occurrence mapping.
Result: The results indicate a substantial increase in RDMrelated
publications, particularly after 2015, which is aligned
with the proliferation of FAIR data principles and mandates by
funding bodies. Thematic clustering revealed key focus areas,
including data-sharing policies, metadata standards, digital
curation, data repositories, and institutional strategies for
research data services. Furthermore, the analysis highlights a
shift toward interdisciplinary approaches, involving domains,
such as data science, computer science, library science, and
health sciences.
Conclusion: This scientometric evaluation provides a
foundational understanding of the intellectual and collaborative
structure of RDM research, offering actionable insights for
researchers, data professionals, and policymakers aiming to
enhance research data infrastructure and governance on a
global scale.