Implementation of data cataloguing and metadata management in higher education institutions based on artificial intelligence technologies

this article addresses the pressing issue of effectively managing educational data in higher education institutions in the context of digital transformation objectives defined by the Decree of the President of the Russian Federation. The aim of the study is to develop and describe an approach to automating data cataloging and metadata management based on artificial intelligence technologies. The paper presents a specialized AI service, "Agregator," designed for the automatic collection, indexing, and semantic analysis of heterogeneous documents (scientific articles, dissertations, educational materials, audio recordings). The key functional modules of the service are described, including bibliographic metadata extraction, content classification, and the generation of analytical reports. It is shown that the implementation of this solution significantly reduces labor costs for information processing, improves the quality of its accounting, and provides a basis for personalizing learning and making data-driven management decisions. The practical significance of this research lies in the possibility of integrating the service into the electronic information educational environment of a university.

education, artificial intelligence, large language model, data, information, higher military educational institutions, multimodal information, data management