Data Librarians’ Skills and Competencies Are Heterogeneous and Cluster into Those for Generalists and Specialists

A Review of: Federer, L. (2018). Defining data librarianship: A survey of competencies, skills, and training. Journal of the Medical Library Association 106(3), 294–303. https://doi.org/10.5195/jmla.2018.306 Abstract Objective – To better define the skills, knowledge, and competencies necessary to data librarianship. Design – Electronic survey. Setting – Unknown number of research institutions in English-speaking countries with a focus on North America. Subjects – Unknown number of information professionals who follow data-related interest group electronic mail lists or discussions on Twitter. Methods – Author distributed an electronic survey via electronic mail lists and Twitter to information professionals, particularly those in biomedicine and the sciences, who self-determined that they spend a significant portion of their work providing data services. The survey asked respondents to rate the importance of various skills and expertise that had been selected from a review of the literature. In addition to other quantitative analysis, author performed cluster analysis on the final dataset to detect subgroups of similar respondents. Main Results – 82 valid responses were received. Most respondents supported more than one academic discipline and spent at least half of their time on data-related work. Competencies in the “Personal Attributes” category (such as interpersonal, written, and presentation skills) were rated as most important, while those in the “Library Skills” category were rated as least important. A cluster analysis detected two groups that could best be described as subject specialists and data generalists. Subject specialists focus on a smaller number of disciplines and view a smaller number of tasks as important to their work compared to data generalists. In addition, data generalists are more likely to report spending most of their time on data-related work. Conclusion – Data librarianship is a heterogeneous profession with many skillsets at play depending on the work environment, but the existence of two overarching subgroups – subject specialists and data generalists – deserves further study and may have implications for a number of stakeholders. Hiring institutions may consider the breadth of their user population’s needs before recruitment. Educational institutions as well as other on-the-job training opportunities may do well to focus more on “soft skills” as this is deemed more important by data librarians