To propel and institutionalise AI for science, university libraries are strategically developing specialised Research Support Services (RSS). This paper presents a research study that aims to identify and understand user requirements for RSS during the research paradigm shifting. Due to the exploratory nature of this study, a case study approach is adopted as the overarching methodology. Overall, 25 participants were approached and interviewed, including library managers, librarians and researchers. The analysis of interview data involves a thematic approach and uses two analytic tools: coding for tagging and interpreting data, and a concept map for visualising and demonstrating the progress of analysis. As a result, 10 user requirements are identified and then categorised into 5 themes: promoting AI4S readiness, formulating research ideas, building a collaborative network, conducting research, and publishing results. Furthermore, to support RSS development, the analysis indicates that libraries should consider three major challenges, namely technical limitations of AI algorithms, AI ethics and data property issues, and concerns about over-reliance. Also, intensified user requirements for specialised information and services should be paid great attention to. Although this study is designed for university libraries in China, the research results can be shared across national borders and provide useful indications for university libraries around the world when developing similar services.
Wang et al. (Wed,) studied this question.