Ontological approach to system geo-information analysis

DOI: 10.31673/2412-9070.2024.060447

Abstract

One of the main tasks of conceptual modeling is to obtain from a large array of diverse information the data necessary to solve specific tasks or problems. Ontologies are an important element of modern information technologies of knowledge engineering. An ontology describes facts and relationships in a particular subject area. This is one of the important directions in the field of artificial intelligence, which allows to systematize and organize information for its effective use, to provide an analysis of the semantics of information about the subject area for its effective use and presentation.
The article examines the application of the principle of the ontological approach to obtaining subject-oriented knowledge from a set of natural language texts, their formal-logical presentation and application processing using the example of the definition "system geoinformation analysis". The application of the systemic ontological approach allows you to formally describe the subject area, clarify the concept of the subject area, and define a common terminological base. It is shown that the Protégé software environment is an effective means of structuring and analyzing the subject area, terms and relationships between them. A conceptual analysis of the term "systemic geo-informational analysis" was carried out, which gives characteristics to its properties, shows the classes of basic concepts and relations between classes for the construction of the ontology of the studied subject area. It is shown that the given toolkit allows considering the terms and concepts of the subject area in development, which is provided by a chain of quanta of knowledge about the studied concept or object. The paper shows the importance of the ontological approach for the development and improvement of methods of systematic geoinformation analysis, which in turn will contribute to more effecttive decision-making in various areas where spatial analysis is critically important.
Keywords: ontology, knowledge engineering, complexly structured subject area, knowledge modeling, system geoinformation analysis, system analysis