Integration of research support services (RSS) and research data management (RDM) strategies to enhance research efficiency and impact: a scientometric study

Purpose This study aims to review the scientific landscape of research support services (RSS) and research data management (RDM) provided by libraries, focusing on their application in research and learning contexts. This research seeks to examine the growth of literature in this field, identify the most influential authors, countries, affiliations and journals and assess collaboration across different geographical regions. In addition, the study will identify the most impactful paper based on the highest citation count and Altmetric Attention Score and analyse keywords to determine research trends in this subject area. Design/methodology/approach This study uses a Scientometric and Altmetric approach to analyse a decade (2014–2023) of research outputs from Scopus. Data was retrieved with a keyword-based search strategy and visualized for science mapping (author, country, organization collaborations and keyword co-occurrence) using VOSviewer. Dimension.ai was used to determine Altmetric scores and Mendeley readership of influential works. Findings This study analyses 1,085 RSS and RDM publications (2014–2023), showing global growth but lagging citations. Christina Ribeiro leads with 21 publications. Key sources include the Data Science Journal and the University of Pittsburgh. RDM has more focus than RSS, which needs further study. RSS and RDM simplify research tasks, widely used in social and computer sciences. Top works are mainly in library science. Effective RSS in libraries can enhance research and redefine their academic role. Originality/value This study examines global scientific literature to assess libraries’ awareness of RSS and RDM services for research and learning. To the best of the authors’ knowledge, no previous study has applied Scientometrics and Altmetrics to these aims and objectives before.