The work is devoted to the problem of data integration for representing scientific subject areas based on their semantic description in the SciLibRu digital library. The LibMeta library's ontology and knowledge graph are used as the data model. SciLibRu is populated by adding data from scientific journals. The paper demonstrates how the stages of processing semi-structured scientific publications for their integration into the library's ontology are implemented. Completing all data preprocessing stages yields a dataset that can be used to train language models for queries in Russian-language scientific subject areas.