Features of working with Russian-language ontologies using the Owlready2 library in Python

The use of domain ontologies to create information systems is currently becoming more and more widespread. Based on ontologies, it is possible to create so-called knowledge bases, which are essential components of most information systems. To work with ontologies, there are various software products, such as Protégé or the Owlready2 module for the Python programming language. As a rule, to search for new knowledge or facts that are in the ontology, a logical inference machine or reasoner is used, which checks it for consistency, i.e. consistency. When working in the Owlready2 library of the Python language with Russian-language ontologies, i.e. Ontologies in which initially all classes, individuals and relationships are written in Cyrillic, reasoner gives incorrect data that is simply unreadable. Due to a failure in the encoding during the operation of reasoner owlready2, firstly, it duplicates the ontology, and, secondly, unreadable characters appear instead of the Cyrillic text. With such data, further actions in Python or Protégé are not possible without additional actions. The article proposes a way to solve this problem by explicitly setting the encoding of the output file after reasoner's work, namely cp1251 encoding, i.e. standard 8-bit encoding for Russian versions of Microsoft Windows. As a result, when working with Russian-language ontologies, it becomes possible to use the full potential of the Owlready2 library of the Python programming language. Therefore, the creation of Russian-language ontologies that can be used as the basis for Russian-language information systems is an urgent task at the present time. The method proposed in the article can be useful for IT specialists involved in the development of information systems based on ontologies of subject areas and when working with ontologies as part of the educational process at a university.