Towards AI for science: developing a conceptual basis for transforming research support services in university libraries
DOI:
https://doi.org/10.47989/ir31iConf64182Keywords:
AI for science, Library transformation, Research support service, Systematic review, University librariesAbstract
Introduction. This paper reports on an ongoing research project that investigates the development of research support services (RSS) in China’s university libraries to facilitate AI for science (AI4S) projects. Specifically, this paper focuses on developing a conceptual model based on a literature review.
Method. A systematic literature review approach was adopted. English and Chinese academic databases were searched.
Analysis. After screening, 67 articles were analysed using a thematic analysis and qualitative coding.
Results. The analysis points to a conceptual model that consists of 21 library RSS and five main themes: promoting AI readiness, formulating research ideas, building collaborative networks, conducting research, and publishing results.
Conclusion(s). Preparing university libraries for AI4S is difficult, facing two primary challenges: (1) the paradigm of AI4S is fast-growing, has not fully emerged; (2) libraries are late and slow in adopting AI technologies. For future studies, the conceptual model can serve as a theoretical basis.
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