Innovation Series: Advanced Science (ISSN 2938-9933, CNKI Indexed)

A Study on the Optimization of Information Service Models in University Libraries in the Era of Big Data

Juan Ye

Library of Northwest Normal University, Lanzhou 730000, Gansu, China

Abstract: Against the dual backdrop of the rapid proliferation of big data technology and the profound digital transformation of education, university libraries—as the central hubs for academic literature and information and key platforms for talent development—find their traditional information service models increasingly unable to meet the diverse, personalized and immediate information needs of today’s university students. Leveraging its core strengths in massive data processing, multi-source information integration and user needs analysis, big data technology offers a novel pathway for the innovation of university library information service models. By systematically examining the core relationship between big data and university library information services, and thoroughly analyzing the difficulties and challenges faced by such services in the big data environment, this study draws upon relevant domestic practices in big data applications within university libraries. It proposes targeted optimization strategies across six dimensions — technological integration, service models, resource provision, librarian competencies, feedback mechanisms and data security, this paper proposes targeted optimization strategies. The aim is to drive the transformation of university library information services towards precision, personalization, intelligence and efficiency, thereby providing practical guidance and theoretical support for the high-quality development of university libraries, and contributing to the enhancement of talent cultivation and disciplinary development in higher education.

Keywords: Big Data; University Libraries; Information Service Models; Optimization

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