Development of an ontological model of the subject area for corporate storage data processing

Purpose of reseach. Formalize an ontological model of the research subject area and develop, based on it, data models for an information system for extracting and processing expectations for the quality of corporate data storage.

Methods. In this study, an ontological approach and data modeling methods were used, and the task of implementing a data model was formalized using the conceptual apparatus and formal language of the relational data model and set theory. The Entity-Relationship model was used as a modeling approach.

Results. As a result of the research, conceptual, logical and physical models were developed for a relational database information system for retrieving and processing expectations for the quality of corporate data storage based on the ontology of the subject area under study. This allows us to expand the possibilities of using the information system developed in further research in industrial operation by organizations carrying out work on creating corporate data warehouses.

Conclusion. As a result, the results of the study showed that the transition to using a relational data model while preserving ontological semantics is possible and has been studied by a number of researchers: sets of classes, relationships between them and their attributes are defined in the ontological model, which makes it possible to develop data models for a relational database without providing for the need for ontology changes, and the relational database, in turn, can store instances of ontology classes in separate tables for each class, the fields of which will be the attributes of a particular class.

1. Luchkin N. A. Creating a data warehouse model for a corporate information and analytical system of an enterprise. Ob"ektnye sistemy = Object Systems. 2011; 1 (3): 36-39. (In Russ.)

2. Masyuk N.N. Main trends in the digital transformation of the economy. Vladivostok, izdvo VGUES; 2021. 200 p. (In Russ.)

3. Saliy V.V., Kukharenko L.V., Ishchenko O.V. Digital transformation of the economy and the introduction of data warehouses based on big data into the company’s infrastructure. Vestnik Akademii znanij = Bulletin of the Academy of Knowledge. 2021; (3): 208-214. (In Russ.)

4. Ilyin A. A. Some problems in building corporate data warehouses. Programmnye produkty i sistemy = Software Products and Systems. 2005; 3: 29-32. (In Russ.)

5. Abdrakhmanova G. I., Vasilkovsky S. A., Vishnevsky K. O., Gershman M. A., Gokhberg L. M. [et al.], hands auto count Rudnik P. B. Digital transformation: expectations and reality. In: XXIII Yasinskoy (Aprel'skoy) mezhdunar. nauch. konf. po problemam razvitiya ekonomiki i obshchestva = XXIII Yasinsk (April) international. scientific conf. on problems of economic and social development. Moscow: Izd. dom Vysshei shkoly ekonomiki; 2022. 221 p. (In Russ.)

6. DAMA-DMBOK: Data Management Body of Knowledge. 2nd ed.]. Moscow: OlimpBusiness; 2020. 828 p. (In Russ.)

7. Dobritsa V. P., Titenko E. A., Khalin Y. A., Katykhin A. I. Models of knowledge representation and processing in information-analytical systems. Kursk, 2023. 172 p. (In Russ.)

8. Zagorulko Yu. A. Modern means of formalizing the semantics of knowledge areas based on ontologies. Informacionnye i matematicheskie tekhnologii v nauke i upravlenii = Information and mathematical technologies in science and management. 2018: (3): 27-35. (In Russ.)

9. Khalin Y. A., Katykhin A I., Zinkin S. A., Shilin A. A. Cognitive Modeling of Information Support for Game-Based Automated Learning. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta = Proceedings of the Southwest State University. 2022; 26(4): 117- 131 (In Russ.). https://doi.org/10.21869/2223-1560-2022-26-4-117-131.

10. Gruber T.R. A translational approach to portable ontology specification. Knowledge Acqusition. 1993; 5 (2): 199-220.

11. Afanasyev A.A., Kudinov V.A. Research of approaches to data modeling based on the ontology of the data quality domain of corporate storages. In: Intellektual'nye informacionnye sistemy: Teoriya i praktika: sb. nauch.st. po materialam IV Vseros. s mezhdunar. uchastiem konf. = Intelligent information systems: Theory and practice: collection. scientific article based on materials of the IV All-Russian. with international participation of the conf. Kursk; 2023. P. 188-200. (In Russ.)

12. Khan S. A., Qadir M. A. A Genaric Framework for Evaluation of Ontology to Relational Database Transformation Process. 2010 International Conference on Information and Emerging Technologies (ICIET). Karachi, 2010. P. 1-5.

13. Afanasyev A.A., Kudinov V.A. Using an Ontology Approach to Extract Quality Expectations for Enterprise Data Warehouses. Ekonomika. Informatika = Economy. Computer Science.2022; 49(3): 566–574. (In Russ.).

14. Olivier Curé, Guillaume Blin. RDF Database Systems. Morgan Kaufmann, 2014, 256 p.

15. Yongqi Huang, Gaoyan Deng. Research on Storage of Geo-ontology in Relational Database. 2nd International Symposium on Information Engineering and Electronic Commerce (IEEC). Ternopil, 2010. P. 1-4.

16. Ahmed W., Aslam M. A., Jun Shen, Jianming Yong. A Light Weight Approach for Ontology Generation and Change Synchronization between Ontologies and Source Relational Databases. 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD). Lausanne, 2011. P. 208-214.

17. Erkimbaev A. O., Zitserman V. Yu., Kobzev G. A., Kosinov A. V. Ontologies and databases - mutual complementarity when using scientific data. Monitoring. nauka i tekhnologii = Monitoring. Science and technology. Center for Associated Monitoring of the Environment and Natural Resources, 2015; (3): 41-50. (In Russ.)

18. Vekhorev M. N., Panteleev M. G. Construction of repositories of ontological knowledge bases. Programmnye produkty i sistemy = Software Products and Systems. 2011; (3): 1-6. (In Russ.)

19. Oleinik P. P., Greger S. E. Application and implementation of ontologies in the development of database applications. Prikladnaya informatika = Applied informatics. 2016; (3): 76-102. (In Russ.)

20. Zagorulko Yu. A., Sidorova E. A., Zagorulko G. B., Akhmadeeva I. R., Sery A. S. Automation of the development of ontologies of scientific subject areas based on ontological design patterns. Ontologiya proektirovaniya = Ontology of Design. 2021; (4): 500-520. (In Russ.)

21. Codd E. F. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM. 1970; 13 (6): 377–387.

22. Chen P. P.-S. The Entity-Relationship Model: Toward a Unified View of Data. ACM Transactions on Database Systems. 1976; 1 (1): 9–36.