Abstract <p>This paper examines the development of the SciLibRu library of scientific subject areas as a continuation of the semantic description of scientific works from across the library LibMeta project. This library is based on a conceptual data model, the structure and semantics of which are formed from the principles of ontological modeling. This approach ensures the strict description of the subject area, a formalization of the relationships between entities, and the possibility of additional automated data analysis. The goal of the study is to develop and experimentally apply methods for structuring scientific journal data in LaTeX format for their integration into a library ontology and to support semantic search. An algorithm for translating data that are represented by multiple files into XML format is proposed for integration into the library ontology. A vector search module that is based on embedding calculation using language models is implemented. Patterns in the distribution of embeddings and factors influencing the accuracy of search results ranking are identified. Testing of the two components is conducted. The developed method forms the basis for automatically incorporating scientific journal data into the SciLibRu knowledge graph and creating training corpora for language models limited to scientific subject areas. The results contribute to the development of journal knowledge graph navigation systems, recommendation engines, and intelligent search tools for Russian-language scientific texts.</p>