Development of ontological support of constructive-synthesizing modeling of information systems

Authors

  • Vladislav Skalozub Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0002-1941-4751
  • Valeriy Ilman Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0003-0983-8611
  • Victor Shynkarenko Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0001-8738-7225

DOI:

https://doi.org/10.15587/1729-4061.2017.119497

Keywords:

constructive-synthesizing modeling, ontology, conceptualization, unification of models, constructive object

Abstract

The methodology and means of ontological support of the processes of constructive-synthesizing modeling of complex information technologies have been developed in the study. The requirements for the applied ontology of constructive-synthesizing modeling have been formulated along with developing and specifying the conceptualization methods, axiomatics, the output system and performers that provide effective modeling for a wide range of subject areas.

The theoretical basis of constructive-synthesizing modeling has been devised as the underlying principle of applied ontologies, with examples of the formation of concept models of subject domains.

In ontology, constructive-synthesizing models of subject domains have been formed and presented on the basis of a single constructive structure containing primary classes of ontology instances, active binders of operators of actions and performers. It ensures universality and opportunity to use the models for developing and setting them in subject domains of modeling.

The completed formalization of the ontology design allows improving the quality of automated processes of creating intelligent information technologies for structurally complex areas of modeling. This methodology is based on the paradigm of constructivism of all components of subject domains, on the revealed properties and unified models of representing concept structures, concepts and basic relations in CSM. At the same time, it has been made possible to create and maintain models of conceptual systems of subject domains that are different from taxonomy, given the uncertainties in the choice of the structure of conceptual models, both for systems of concepts of subject areas and their distinctive features

Author Biographies

Vladislav Skalozub, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

Doctor of Technical Sciences, Professor

Department of Computer Information Technologies

Valeriy Ilman, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

PhD, Associate Professor

Department of Computer Information Technologies

Victor Shynkarenko, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

Doctor of Technical Sciences, Professor, Head of Department

Department of Computer Information Technologies

References

  1. Palagin, A. V. (2016). Ontologicheskaya kontseptsiya informatizatsii nauchnyh issledovaniy. Kibernetika i sistemnyy analiz, 52 (1), 3–9.
  2. Frye, L., Cheng, L., Heflin, J. (2014). TRIDSO: Traffic-based Reasoning Intrusion Detection System using Ontology. Journal of Research and Practice in Information Technology, 46 (4), 215–233.
  3. Manuja, M., Garg, D. (2015). Intelligent text classification system based on self-administered ontology. Turkish Journal of Electrical Engineering & Computer Sciences, 23, 1393–1404. doi: 10.3906/elk-1305-112
  4. Luke, S., Spector, L., Rager, D. (1996). Ontology-Based Knowledge Discovery on the World-Wide Web. AAAI Technical Report WS-96-06, 96–102.
  5. Fensel, D., Hendler, J. A., Lieberman, H., Wahlster, W. (Eds.) (2005). Spinning the Semantic Web: bringing the World Wide Web to its full potential. Mit Press, 272.
  6. Bechhofer, S. (2009). OWL: Web ontology language. Encyclopedia of Database Systems. Springer, 80.
  7. Gruber, T. R. (1995). Toward principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43 (5-6), 907–928. doi: 10.1006/ijhc.1995.1081
  8. Noy, N. F., McGuinness, D. L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880. Available at: http://protege.stanford.edu/publications/ontology_development/ontology101.html
  9. Guarino, N. (1998). Formal ontology and information systems. Proceedings of FOIS, 98, 81–97.
  10. Nardi, J. C., De Almeida Falbo, R., Almeida, J. P. A., Guizzardi, G., Pires, L. F., Van Sinderen, M. J. et. al. (2015). A commitment-based reference ontology for services. Information Systems, 54, 263–288. doi: 10.1016/j.is.2015.01.012
  11. Kazi, Z., Kazi, L., Radulovic, B., Bhatt, M. (2016). Ontology-Based System for Conceptual Data Model Evaluation. International Arab Journal of Information Technology, 13 (5), 542–551.
  12. Alexopoulos, P., Wallace, M., Kafentzis, K., Askounis, D. (2010). Utilizing Imprecise Knowledge in Ontology-based CBR Systems by Means of Fuzzy Algebra. International Journal of Fuzzy Systems, 12 (1).
  13. Titenko, S. V. (2012). Ontologicheski-orientirovannaya sistema upravleniya kontentom informatsionno-uchebnyh Web-portalov. Obrazovatel'nye tekhnologii i obshchestvo, 15 (3), 522–533.
  14. Shynkarenko, V. I., Il'man, V. M. (2014). Konstruktivno-produktsionnye struktury i ih grammaticheskie interpretatsii. І. Obobshchennaya formal'naya konstruktivno-produktsionnaya struktura. Kibernetika i sistemniy analiz, 50 (5), 8–16.
  15. Shynkarenko, V. I., Sablin, O. I., Ivanov, O. P. (2016). Constructive modelling for zone of recovery energy distribution of dc traction. Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 5 (65), 125–135. doi: 10.15802/stp2016/84036
  16. Shinkarenko, V. I., Il'man, V. M., Zabula, G. V. (2014). Konstruktsionno-produktsionnaya model' struktur dannyh na logicheskom urovne. Problemi programuvannya, 2-3, 10–16.
  17. Shynkarenko, V. I., Kuropyatnik, E. S. (2016). Konstruktivno-produktsionnaya model' grafovogo predstavleniya teksta. Problemi programuvannya, 2-3, 63–72.
  18. Shynkarenko, V. I., Vasetskaya, T. N. (2015). Modelirovanie protsessa adaptatsii algoritmov szhatiya sredstvami konstruktivno-produktsionnyh struktur. Kibernetika i sistemniy analiz, 6, 19–34.
  19. Shynkarenko, V. I., Vasetskaya, T. N. (2016). Modelirovanie protsessa ranzhirovaniya al'ternativ metodom analiza ierarhiy sredstvami konstruktsionno-produktsionnyh struktur. Matematychni mashyny ta systemy, 1, 39–47.
  20. Zholtkevich, G. N., Semenova, T. V., Fedorchenko, K. A. (2004). Predstavlenie poluskhem predmetnyh oblastey informatsionnyh sistem sredstvami relyatsionnyh baz dannyh. Visnyk Khark. nats. un-tu im. V. N. Karazina. Seriya: Matematychne modeliuvannia. Informatsiyni tekhnolohiy. Avtomatyzovani systemy upravlinnia, 629 (3), 11–24.
  21. Pancerz, K., Lewicki, A., Tadeusiewicz, R. (2015). Ant-based extraction of rules in simple decision systems over ontological graphs. International Journal of Applied Mathematics and Computer Science, 25 (2). doi: 10.1515/amcs-2015-0029
  22. Pancerz, K. (2016). Paradigmatic and Syntagmatic Relations in Information Systems over Ontological Graphs. Fundamenta Informaticae, 148 (1-2), 229–242. doi: 10.3233/fi-2016-1432
  23. Grabusts, P., Borisov, A., Aleksejeva, L. (2015). Ontology-Based Classification System Development Methodology. Information Technology and Management Science, 18 (1). doi: 10.1515/itms-2015-0020
  24. Kogut, P., Cranefield, S., Hart, L., Dutra, M., Baclawski, K., Kokar, M., Smith, J. (2002). UML for ontology development. The Knowledge Engineering Review, 17 (01). doi: 10.1017/s0269888902000358
  25. Bova, V. V., Leshchanov, D. V., Kravchenko, D. Yu., Novikov, A. A. (2014). Komp'yuternaya ontologiya: zadachi i metodologiya postroeniya. Informatika, vychislitel'naya tekhnika i inzhenernoe obrazovanie, 4, 44–55.
  26. Thomsen, E., Read, F., Duncan, W., Malyuta, T., Smith, B. (2014). Ontological Support for Living Plan Specification, Execution and Evaluation. Semantic Technology in Intelligence, Defense and Security (STIDS), CEUR, 1304, 10–17.
  27. Gonen, B., Fang, X., El-Sheikh, E., Bagui, S., Wilde, N., Zimmermann, A. (2014). Ontological Support for the Evolution of Future Services Oriented Architectures. Transactions on Machine Learning and Artificial Intelligence, 2 (6). doi: 10.14738/tmlai.26.784
  28. Grishin, M. V., Larin, S. N., Sosnin, P. I. (2015). Tools ontological support of the design template equipment in the aircraft production. V Mire Nauchnykh Otkrytiy, 4, 10. doi: 10.12731/wsd-2015-4-1
  29. Breitsprecher, T., Codescu, M., Jucovschi, C., Kohlhase, M., Schröder, L., Wartzack, S. (2014). Towards Ontological Support for Principle Solutions. Mechanical Engineering. InFOIS, 5, 427–432.
  30. Khalipova, N. V. (2016). Vektorna optymizatsiya v zadachakh udoskonalennia mizhnarodnykh transportnykh system. Dnipropetrovsk: Universytet mytnoi spravy ta finansiv, 271.

Downloads

Published

2017-12-25

How to Cite

Skalozub, V., Ilman, V., & Shynkarenko, V. (2017). Development of ontological support of constructive-synthesizing modeling of information systems. Eastern-European Journal of Enterprise Technologies, 6(4 (90), 58–69. https://doi.org/10.15587/1729-4061.2017.119497

Issue

Section

Mathematics and Cybernetics - applied aspects