ellibsЭлектронные библиотекиRussian Digital Libraries Journal1562-5419Казанский (Приволжский) федеральный университет10.26907/1562-5419-2026-29-2-627-650ellibs-754Research ArticleСтатьиОнтологическая модель интеграции когнитивных и социологических данных для оценки персоналаAn Ontological Model for Integrating Cognitive and Sociological Data for Personnel AssessmentХалинЮрий АлексеевичKhalinYuri Alekseevichyur-khalin@yandex.ruИльинаАнна АлексеевнаIlinaAnna Alekseevnaanya.ilina.2000@bk.ruЮго-Западный государственный университетSouthwest State University202607052026292627650Copyright © Халин Ю.А., Ильина А.А., 20262026Халин Ю.А., Ильина А.А.Khalin Y.A., Ilina A.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ellibs.elpub.ru/jour/article/view/754

В условиях цифровой трансформации организаций и роста объемов данных появляется запрос на более прозрачные и объяснимые подходы к оценке сотрудников. Цель проведенного исследования состояла в проектировании и верификации онтологической модели (OWL 2/SHACL), которая интегрирует когнитивные показатели и социологические характеристики работников в единое пространство знаний для поддержки HR (Human Resources)-процессов – процессор управления человеческими ресурсами. Научная новизна работы заключается в разработке единой семантической модели, связывающей данные когнитивных тестов, опросников, контекста труда и показателей результативности; в формулировании компетентностных вопросов, запускающих механизм вывода в графе знаний; и в разработке паттернов для прогнозирования дефицитов компетенций, выявления риска перегрузки/выгорания с контролем этики и недискриминации. Предлагаемый подход опирается на методологии инженерии онтологий – METHONTOLOGY и NeOn, концепции семантического веба и методы психометрики.

In the context of digital transformation of organizations and the growing volume of data, there is a demand for more transparent and explainable approaches to employee evaluation. The purpose of the study is to design and validate an ontological model (OWL 2/SHACL) that integrates employees’ cognitive indicators and sociological characteristics into a unified knowledge space to support HR processes. The scientific novelty of the work lies in the development of a unified semantic model linking data from cognitive tests, questionnaires, work context, and performance indicators; in the formulation of competency questions (CQ) that trigger reasoning mechanisms within the knowledge graph; and in the creation of patterns for predicting competency gaps, identifying the risk of overload/burnout, while ensuring ethics and non-discrimination control. The proposed approach is based on ontology engineering methodologies – METHONTOLOGY and NeOn, semantic web concepts, and psychometric methods.

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The authors declare that there are no conflicts of interest present.