Architecture of ontology-driven system for analysis of intellectual and educational achievements

DOI: 10.31673/2412-9070.2026.025815

Abstract

The article presents a formally substantiated model of an intelligent system for monitoring and rating the academic achievements of gifted youth, built on a combination of ontological engineering and multi-criteria analysis methods. The work is aimed at solving an important educational problem: the absence in Ukraine of a single, methodologically consistent and scalable system for evaluating the results of intellectual competitions capable of providing an objective comparison of the achievements of students, teachers, and educational institutions. The diversity of protocols, data fragmentation, and heterogeneity of assessment criteria create significant barriers to the formation of an effecttive state policy to support talented youth and complicate the long-term monitoring of the dynamics of their achievements. The absence of formal mechanisms for integrating the results of intellectual competitions limits the possibilities for their cross-competition comparison and analytical aggregation. To overcome these limitations, a holistic data processing architecture is proposed, covering the full transformation cycle: from structuring and normalizing documents of various formats to building a formal ontology of the subject area and enriching it with an evaluation layer based on multi-criteria analysis. The implementation of this model ensures logical consistency, semantic transparency, and reproducibility of computations by integrating rigorous mathematical operators with adaptive mechanisms of semantic analysis. As a result, within the formed ontologically consistent evaluation space, invariant and correct comparison of results is ensured regardless of the type of competition, year, or evaluation procedures. The results obtained create a methodological and technological basis for building a national system for monitoring and supporting gifted youth and open prospects for the application of ontologically oriented systems to the integration of heterogeneous educational data and multi-criteria evaluation. The proposed model can be used to develop long-term strategies for educational program development and to provide analytical support for state and regional initiatives in the field of gifted education.

Кeywords: ontology engineering, formal ontology, semantic normalization, data structuring, multi-criteria analysis, competitive normalization, academic achievement ranking, ontology-driven assessment, educational analytics.