This study aims to (i) track trends in academic library data management positions, (ii) identify key themes in job advertisements related to data management, and (iii) examine how these themes have evolved. Using text mining techniques, this study applied Latent Dirichlet Allocation (LDA) and TF-IDF vectorization to systematically analyze 803 job advertisements related to data management posted on the IFLA LIBJOBS platform from 1996 to 2023. The findings reveal that the development of these positions has undergone three phases: exploration, growth, and adjustment. Four core themes in data management functions emerged: “Cataloging and Metadata Management,” “Data Services and Support,” “Research Data Management,” and “Systems Management and Maintenance.” Over time, these themes have evolved from distinct roles to a more balanced distribution.
https://doi.org/10.1016/j.acalib.2025.103017
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |