Beyond Collections: The Evolving Role of Medical Librarians in Research Data Management
Journal of Medical Library and Information Science,
Vol. 6 No. 6 (2025),
5 April 2025
,
Page 1-4
https://doi.org/10.22037/jmlis.v6i6.52444
Abstract
Contemporary scientific inquiry is firmly situated in the era of Big Data, characterized by an unprecedented growth in research data volumes. This data ecosystem encompasses a vast spectrum of inputs, ranging from clinical trials and longitudinal cohort studies to high-throughput genomic sequencing, medical imaging, Electronic Health Records (EHRs), and outputs derived from emerging artificial intelligence technologies (1). Yet, amidst this surge, the critical challenge lies not merely in data generation, but in its optimal management.
In essence, RDM is an integral component of the research lifecycle, extending from initial project planning through post-project archival, sharing, and eventual disposition (8, 9). The RDM framework encompasses a holistic set of activities: Data planning, documentation, secure storage, access control, long-term preservation, and the facilitation of data reuse (10-12). Technological advancements have now enabled the collection, storage, and cross-disciplinary analysis of scientific data at a global scale. Consequently, governments, funding agencies, and publishers are increasingly mandating comprehensive Data Management Plans (DMPs) and the implementation of Open Data policies (4).
In this landscape, rigorous RDM is indispensable for ensuring research transparency, data integrity, and the continuous advancement of knowledge. Sound data management practices not only facilitate the verification of research findings—thereby accelerating scientific progress—but also ensure that data are accurately documented, organized, and archived for future utility. Ultimately, when implemented effectively, RDM serves as a cornerstone for improving data quality and fostering robust collaboration across institutions, research groups, and individual investigators. By mitigating the risks of data loss and minimizing redundant efforts, high-quality RDM acts as a catalyst for a more efficient and collaborative global research enterprise (13-15)
- Medical librarians
How to Cite
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