Ontological Modeling of the Knowledge Base “Operating Systems”

Abstract

In the current context of the development of higher education information ecosystems and generative artificial intelligence systems, the implementation of ontological knowledge bases has got particular importance. The application of Semantic Web technologies facilitates this process by enabling machine understanding of content, data interoperability, and seamless integration across various educational platforms. This article focuses on the ontological modeling of the "Operating Systems" subject domain as a foundation for the intellectualization of the educational process. The relevance of this research is driven by the rapidly increasing architectural complexity of modern system software, which necessitates a transition from fragmentary descriptions to machine-readable formalization. The paper outlines the advantages of utilizing the Web Ontology Language (OWL) standard to describe functional dependencies between OS components. The aim of this work is to systematize the interrelationships and genealogy of operating systems through ontological engineering. It details the process of creating a model within the Protégé environment, selected for its robust support of modern reasoners. The structure of the knowledge base encompasses OS components, system software, and the classification of operating systems. Special attention is given to modeling legacy succession and architectural forks, which are critical for understanding the evolution of modern operating systems. The practical value of this study lies in the verification of the ontology using SPARQL queries, enabling the analysis of relationships between kernel types, file systems, network stacks, and virtualization tools. This approach overcomes the limitations of static repositories and ensures the dynamic inference of new knowledge. The research results confirm the model’s effectiveness for integration into the educational environment, particularly in providing context for LLMs during student knowledge assessment. This development opens up new prospects for intelligent learning support systems that transcend traditional teaching methods for the "Operating Systems" discipline, thereby granting students a more profound understanding of the architectural principles behind complex software products.