Continuing Education and Data Training Initiatives are Needed to Positively Impact Academic Librarians Providing Data Services - Prince, Nandi (Evidence Based Library and Information Practice, 2023)
A Review of: Fuhr, J. (2022). Developing data services skills in academic libraries. College & Research Libraries, 83(3), 474. https://doi.org/10.5860/crl.83.3.474 Objective – To measure the existing data services skills of academic librarians and gather information on the preferred training programs available to enhance those skill Design – Survey questionnaire. Setting – Libraries in Canada, the United States, the United Kingdom, and Australia. Subjects – One hundred and twenty respondents who self-identified as providing data services. Most (85%) worked in academic libraries with 7% in hospital libraries, 3% in government libraries and 5% in other types of libraries. Methods – Permission was received from the institution ethics board to administer an incentivized survey. All respondents received a 22-question survey which consisted of a mix of Likert-scale questions, multiple choice, open-ended, and short answer questions. The survey was open for two months, beginning on February 20, 2020. One hundred and twenty responses were collected from librarians. A regression analysis was run for the four-skill set categories: general data services, programming languages and software, library instruction, and soft skills. The four variables measured were: geographic region, percentage of time spent performing data management services, length of time served in the data services role, and overall length of time spent in the library science field. Main Results – The strongest data services skill sets were soft skills and instruction. The weakest skill set was programming languages and software. The more time a librarian spent providing data services, the higher their self-assessed score was for programming languages and software and general data services. Librarians from the United States rated themselves higher than Canadian librarians in data analysis software, data visualization, data mining, programming languages, text editors and project management. Preferred forms of professional development were learning by doing and self-directed learning. Biggest impediments to professional development were lack of time (34%), high cost (28%), and lack of support from administrators and supervisors (26%). Qualitative comments revealed challenges related to a lack of support, a lack of direction, and a lack of defined roles. Conclusion – The survey revealed that additional training and development skills initiatives are necessary for practitioners supporting data services in academic libraries. Academic data librarianship is an emerging field with vaguely articulated roles for the data practitioner in a broad range of settings. Furthermore, the skills and training needed are not clearly defined. The standardization of education, training and the core competencies needed for the mechanics of the roles are challenging to define because of diversity within the field. Libraries embarking on providing data management services need to explore what services their community of researchers needs and plan to equip their staff with appropriate skill sets.