Analysis of the Optimization Path of Library and Information Service Mode under the Background of Big Data

DOI: https://doi.org/10.62517/jnse.202517604

Author(s)

Botao Liu

Affiliation(s)

Henan Medical University, Xinxiang, Henan, China

Abstract

This study investigates the fundamental transformations and challenges posed by big data environments to document service models in library and information institutions, proposing systematic optimization strategies. The research reveals that traditional models demonstrate limitations in data processing, knowledge mining, and demand response, necessitating a deep paradigm shift-from document management to data governance, from information services to knowledge services, and from universal provision to scenario-integrated solutions. To address core issues including technological lag, superficial content, and interaction barriers, the optimization strategy focuses on establishing an intelligent resource foundation integrating multi-source data, designing personalized knowledge service pathways guided by user needs, and creating cross-domain collaborative embedded service mechanisms. The final conclusion emphasizes that library and information institutions must undergo structural innovation to transform from information managers into core knowledge enablers within the knowledge ecosystem, thereby achieving a fundamental leap in service value.

Keywords

Big Data; Library and Information Science; Service Model Optimization; Knowledge Service; Data Governance

References

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