Онтологічний підхід до структурування бази знань бібліотеки на основі метаданих. Аналітичний огляд

The relevance of the research. In the digital age, libraries require sophisticated tools to manage and analyze vast amounts of information. Traditional systems struggle with the complexities of digital resources, hindering data management and user service. Ontological models offer a promising solution. This research studies innovative approaches to structuring library knowledge bases using metadata. The purpose. This study aims to develop an ontological model for structuring library knowledge bases based on metadata, integrating standards like Dublin Core and MARC21. The purpose is to improve resource organization, enable semantic search, and automate library processes, ultimately enhancing library services. The results. A comprehensive ontological model was developed, capturing the hierarchical and relational aspects of library resources. Key outcomes include improved search accuracy, enhanced interoperability, and personalized recommendations. The model supports automated resource classification and metadata processing. The scientific novelty. This research develops a model of an ontological framework that integrates metadata for potential library optimization towards user recommendation systems. Unlike previous approaches focusing on individual standards, this model provides a comprehensive metadata integration for improved resource organization and personalized recommendations. The practical significance. The proposed model can transform library operations across various library types. By enabling semantic search and automation, it enhances resource accessibility and usability. Its adaptability allows for future expansions, such as integrating additional standards and AI tools. The conclusion. This research demonstrates the effectiveness of an ontological approach to structuring library knowledge bases. The model addresses key challenges in modern library management, offering a scalable solution. Future work will expand the ontology and explore AI integration.