Model, data integration algorithms of information systems based on ontology

Uskenbayeva R. Chinibayeva T.
15 May 2021 Little Lion Scientific

Journal of Theoretical and Applied Information Technology
2021 #99 Issue 9 2125 - 2143 pp.

Today is difficult to imagine without integrated automated information systems (IAIS) that support various business processes. Obtaining aggregated information for the purpose of making management decisions depends on the effective interaction of information systems (IS) included in the structure of the IAIS. Business processes are often automated using software solutions of its own and third-party developers, regardless of their interconnectedness, which is especially true for universities. With constant changes in these business processes, IAIS developers are forced to adjust programs and data models, which leads to structural and semantic heterogeneity of information elements and, accordingly, the need to re-develop software data converters. The use of such solutions leads to complication and, consequently, a decrease in the reliability of the IAIS. This article continues the series of publications [25-27], which includes the problem of building integrated automated information systems that support various business processes based on ontologies. The purpose of the article is to develop a mathematical model, algorithm and software system for integrating IS data based on the application of the ontological approach. To achieve this goal, the following tasks were set. 1. Build a mathematical model of data integration of information systems with heterogeneous ontological specifications. 2. To develop a computational method for evaluating the semantic proximity of concepts (elements) of heterogeneous ontologies.

Data integration algorithms , Genetic operator , Heterogeneous information systems , Lexical proximity , Ontology description languages

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International Information Technology University, Almaty, 050040, Kazakhstan

International Information Technology University

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