Patterns in forming the ontology-based environment of information-analytical activity in administrative management




informational-analytical system, management body, administrative management, information resources, ontology, taxonomy, classifier


A new paradigm of the formation of the environment of informational-analytical activity in administrative management based on ontologies was proposed. It was shown that application of this approach makes it possible to formalize domain area and structure the information necessary for analytical activity. It was established that the use of ontological descriptions in the technological chain of analytical activity ensures dynamic formation for the analysis of the respective sets of the criteria based on the use of the properties of concepts of the domain areas, by which appropriate decisions are made. It is noted that the process of solving an analytical problem may represent a certain sequence of ordered tautologies, each of which inherits all the properties of the concepts that make up the tautology that directly precedes it. In turn, this sequence determines the set of possible taxonomies as functional components of the operational environment of informational-analytical activity. To support the work of an analyst, it is proposed to apply the hierarchies of ontologies from the upper level to the subject ontologies, including the intermediate level of the ontology core. The ontology core is expanding through ontological linking of ontology classes to such information resources as classifiers. Correctness and adequacy of such decision is proved by the use of this paradigm to solve the problem of administrative monitoring of socio-economic development of the regions of a country from the state level to local self-government

Author Biographies

Oleksandr Nesterenko, National Academy of Management Ushinskoho str., 15, Kyiv, Ukraine, 03151

PhD, Associate Professor

Department of Computer Science, Information Technology and Systems Analysis

Oleksandr Trofymchuk, Institute of Telecommunications and Global Information Space Chokolivskyi blvd., 13, Kyiv, Ukraine, 03186

Doctor of Technical Sciences, Professor, Corresponding Member of the National Academy of Sciences of Ukraine


  1. Nesterenko, O. V. (2005). Osnovy pobudovy avtomatyzovanykh informatsiyno-analitychnykh system orhaniv derzhavnoi vlady. Kyiv: Naukova dumka, 628.
  2. Larichev, O. I. (1979). Nauka i iskusstvo prinyatiya resheniy. Moscow: Nauka, 200.
  3. Gaft, M. G. (1979). Prinyatie resheniy pri mnogih kriteriyah. Moscow: Znanie, 64.
  4. Saraev, A. D. (2006). Sistemniy analiz i sovremennye informatsionnye tehnologi. Trudy Krymskoy Akademii nauk, 47–59.
  5. Larichev, O. I., Petrovskiy, A. V. (1987). Sistemy podderzhki prinyatiya resheniy. Sovremennoe sostoyanie i perspektivy ih razvitiya. Itogi nauki i tehniki. Seriya: Tehnicheskaya kibernetika, 21, 131–164.
  6. Rohushyna, Yu. V., Hladun, A. Ya. (2007). Vykorystannia orhanizatsiynykh ontolohiy dlia poshuku ekspertiv u novykh predmetnykh oblastiakh. Problemy prohramuvannia, 1, 73–84. Available at:
  7. Gruninger, M., Atefi, K., Fox, M. (2000). Ontologies to support process integration in enterprise engineering. Computational & Mathematical Organization Theory, 6 (4), 381–394. doi:
  8. Järvenpää, E., Siltala, N., Hylli, O., Lanz, M. (2018). The development of an ontology for describing the capabilities of manufacturing resources. Journal of Intelligent Manufacturing, 30 (2), 959–978. doi:
  9. Grimaldi, M., Sebillo, M., Vitiello, G., Pellecchia, V. (2019). An Ontology Based Approach for Data Model Construction Supporting the Management and Planning of the Integrated Water Service. Lecture Notes in Computer Science, 243–252. doi:
  10. Almeida, M. B., Pessanha, C. P., Barcelos, R. (2017). Information Architecture for Organizations: An Ontological Approach. Ontology in Information Science. IntechOpen. doi:
  11. DeStefano, R. J., Tao, L., Gai, K. (2016). Improving Data Governance in Large Organizations through Ontology and Linked Data. 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud). doi:
  12. Zaouga, W., Rabai, L. (2019). Modeling and Evaluating a Human Resource Management Ontology. Software Engineering Methods in Intelligent Algorithms, 380–390. doi:
  13. Hagedorn, T. J., Smith, B., Krishnamurty, S., Grosse, I. (2019). Interoperability of disparate engineering domain ontologies using basic formal ontology. Journal of Engineering Design, 1–30. doi:
  14. Wang, S., Chen, K., Liu, Z., Guo, R.-Y., Chen, S. (2018). An ontology-based approach for supply-chain quality control: From a principal–agent perspective. Journal of Information Science, 45 (3), 283–303. doi:
  15. Malishevskiy, A. V. (1998). Kachestvennye modeli v teorii slozhnyh sistem. Moscow: Nauka, Fizmatlit, 528.
  16. Buch, G. (1992). Obektno-orientirovannoe proektirovanie s primerami primeneniya. Moscow: Konkord, 519.
  17. Palagin, A. V. (2016). An Introduction to the Class of the Transdisciplinary Ontology-controled Research Design Systems. Upravlyayushchie sistemy i mashiny, 6, 3–11.
  18. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5 (2), 199–220. doi:
  19. Stryzhak, O. Ye. (2014). Ontological information and analytical system. Radioelektronni i kompiuterni systemy, 3 (67), 71–76. Available at:
  20. Common Core Ontologies for Data Integration. Available at:
  21. Gladun, V. P. (1994). Protsessy formirovaniya novyh znaniy. Sofiya: SD «Pedagog 6», 192.
  22. Knyazeva, E. N. (2011). Transdisciplinary research strategies. Vestnik Tomskogo gosudarstvennogo pedagogicheskogo universiteta, 10 (112), 193–201. Available at:




How to Cite

Nesterenko, O., & Trofymchuk, O. (2019). Patterns in forming the ontology-based environment of information-analytical activity in administrative management. Eastern-European Journal of Enterprise Technologies, 5(2 (101), 33–42.