Big data-driven investigation into the maturity of library research data services (RDS)

• Published in: The Journal of academic librarianship 2023-01, Vol.49 (1), p.102646, Article 102646
• Main Authors: Nahotko, Marek, Zych, Magdalena, Januszko-Szakiel, Aneta, Jaskowska, Małgorzata
• Format: Article
• Language: English
• Subjects: Academic libraries; Data librarianship; Datafication; RDS maturity; Research data management (RDM); Research data services (RDS)
• ISSN: 0099-1333; 1879-1999
• DOI: 10.1016/j.acalib.2022.102646

Research data management (RDM) poses a significant challenge for academic organizations. The creation of library research data services (RDS) requires assessment of their maturity, i.e., the primary objective of this study. Its authors have set out to probe the nationwide level of library RDS maturity, based on the RDS maturity model, as proposed by Cox et al. (2019), while making use of natural language processing (NLP) tools, typical for big data analysis. The secondary objective consisted in determining the actual suitability of the above-referenced tools for this particular type of assessment. Web scraping, based on 72 keywords, and completed twice, allowed the authors to select from the list of 320 libraries that run RDS, i.e., 38 (2021) and 42 (2022), respectively. The content of the websites run by the academic libraries offering a scope of RDM services was then appraised in some depth. The findings allowed the authors to identify the geographical distribution of RDS (academic centers of various sizes), a scope of activities undertaken in the area of research data (divided into three clusters, i.e., compliance, stewardship, and transformation), and overall potential for their prospective enhancement. Although the present study was carried within a single country only (Poland), its protocol may easily be adapted for use in any other countries, with a view to making a viable comparison of pertinent findings. •We used Web scraping methodology, which is automated data extraction from the Internet•The method was used to search the library web pages for the presence of keywords in their source code•The data collected and then analyzed with several NLP tools, allowed for the determination of the data services maturity level•Research data management processes are most developed in university (classical) and technical university libraries•There is lack of the most mature activities of libraries, requiring significant changes in the organization of their work