Abstract
The research paper discusses the methods of creating, applying and analyzing knowledge bases with a description of subject areas. The methods considered apply an integrated approach to knowledge representation. We propose an approach to developing an intelligent system designed to tackle intricate problems. This approach is built upon semantic models of knowledge bases and coherent models of machines dedicated to processing these knowledge bases. The foundation for constructing these models lies in a unified semantic representation of knowledge, grounded in universal semantics with a theoretical aspect of multiple interpretations. Using this language as a basis, we construct an open family of collaborative languages, where the meaning of each language is determined by an appropriate ontological approach. The semantic model for machine processing of fundamental knowledge adopts the concept of multiagents, facilitating interactions among agents through shared semantic memories. This article serves as a comprehensive introduction to utilizing Protégé as a tool for ontology building in the field of computer science. It provides practical recommendations and insights into the software's advantages and limitations. Researchers and practitioners in computer science seeking a convenient and powerful tool for ontology development will find this article beneficial. In order to more effectively develop knowledge in the field of computer science, the author defines the classification of knowledge, explains the choice of ways to develop knowledge, analyzes forms, methods of control depending on the information approach.