Control Systems and Computers, N3, 2022, Article 2

https://doi.org/10.15407/csc.2022.03.011

Control Systems and Computers, 2022, Issue 3 (299), pp. 11-28

UDC 004.318

M.G. Petrenko, Doctor of Technical Sciences, Leading Researcher, Microprocessor Technology Department, V.M. Glushkov Institute of Cybernetics, The National Academy of Sciences of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine, ORCID: https://orcid .org/0000-0001-6440-0706, petrng@ukr.net

O.V. Palagin, Academician of NAS of Ukraine (Computer Science), Professor, Doctor of Technical Sciences (Computers, Systems and Networks), deputy director of V.M. Glushkov Institute of Cybernetics, The National Academy of Sciences of Ukraine,  Glushkov ave., 40, Kyiv, 03187, Ukraine, ORCID: https://orcid.org/0000-0003-3223-1391, palagin_a@ukr.net

M.O. Boyko, Research Fellow,Microprocessor Technology Department, V.M. Glushkov Institute of Cybernetics, The National Academy of Sciences of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine,  ORCID: http://orcid.org/0000-0003-1723-5765swsfrmac@gmail.com

S.M. Matveyshyn, Research Fellow, Microprocessor Technology Department, V.M. Glushkov Institute of Cybernetics, The National Academy of Sciences of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine, ORCID: https://orcid.org/0000-0001-9329-8800, sergmmm2507@gmail.com.

Knowledge-Oriented Tool Complex for Developing Databases of Scientific Publications and Taking into account Semantic Web Technology

Introduction. The development of theories, methods, and algorithms for the discovery and formation of new knowledge has always occupied one of the central places for any researcher, especially if he is actively working on the creation of new scientific publications. It is known that there is no universal language for the formal description of concepts (knowledge) and systemology of transdisciplinary scientific research. And therefore, scientists face a number of priority problems, including the problem of significantly accelerating the receipt by a researcher of the cognitively structured information he needs from his sources. The tool complex for processing databases of scientific publications is oriented in this way to a researcher who has published from several tens to hundreds of scientific papers. We are not aware of search engines that could provide such information to a researcher in the shortest possible time. The toolkit implements Information Retrieval and Knowledge Discovery in Databases technologies with an emphasis on Semantic Web and cognitive graphics technologies and tools. The development of such a tool complex involves three stages: at the first stage, tools for implementing the complex, methods and algorithms for the interaction of the “User – Knowledge Engineer – Remote Endpoint” system and filling it with data are created; the second stage, the tasks of multimedia representation of figurative-conceptual structures are solved, which are described in scientific documents, and at the third stage — the solution of the problem of extracting new knowledge.

Purpose. The purpose of our research was to further develop a tool complex for processing databases of scientific publications, which allows a scientist to significantly speed up the receipt of the necessary cognitively structured information from his sources.

Methods. The methods and models used in the work are based on the information technologies of the Semantic Web and ontological engineering.

Results. A tool complex for processing databases of scientific publications based on a remote endpoint based on the Apachi Jena Fuseki server, basic UML diagrams of functioning and examples of executing user requests have been developed.

Conclusion. The article introduced and described the architectural and structural organization of the tool complex, which includes a local network from the user’s PC and the PC of the administrator-knowledge engineer and a remote endpoint based on the Apachi Jena Fuseki server, the main UML diagrams of the tool complex functioning and examples of executing user requests.

Download full text! (On Ukrainian)

Keywords: semantic Web technologies, ontological engineering, a database of scientific publications, transdisciplinary scientific research, information and analytical support for a researcher.

  1. Palagin, A.V., Petrenko, M.G., 2020. “Knowledge-Oriented Tool Complex Processing Data-bases of Scientific Publications”. Control systems and computers. N 5, pp. 17-33. https://doi.org/10.15407/usim.2020.05.003 (In Ukrainian).
    https://doi.org/10.15407/csc.2020.05.017
  2. Palagin, A.V., Petrenko, N.G., Velychko, V.Yu., Malakhov, K.S., 2014. “Development of formal models, algorithms, procedures, engineering and functioning of the software system. Instrumental complex for ontological engineering purpose”. In Proceedings of the 9th International Conference of Programming UkrPROG. CEUR Workshop Proceedings 1843. Kyiv, Ukraine, May 20–22, 2014. [Online]. <http://ceur-ws.org/Vol-1843/221-232.pdf> (date of access: 23.06.2022) (In Russian).
  3. Palagin, A.V., Kryvyy, S.L., Petrenko, N.G., 2012. “Ontological methods and means of processing subject knowledge”. Lugansk: V.I. Dal East Ukr. Nac. University. [Online]. <http://www.aduis.com.ua/Monography.pdf> (date of access: 20.06.2022).
  4. Palagin, A.V., Malakhov, K.S., Velichko, V.Yu., Shchurov O.S., 2017. “Design and software implementation of the subsystem for creating and using the ontological knowledge base of the re-searcher’s publications”. Programming problems, N 2, pp. 72-81 (In Ukrainian).
    https://doi.org/10.15407/pp2017.02.072
  5. Palagin, O.V., Velychko, V.Yu., Malakhov, K.S., Shchurov, O.S., 2020. “Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach”. In Proceedings of the 12th International Scientific and Practical Conference of Programming UkrPROG 2020. CEUR Workshop Proceedings 2866. Kyiv, Ukraine, September 15–16, 2020. [Online]. <http://ceur-ws.org/Vol-2866/ceur_342-352palagin34.pdf> (date of access: 23.06.2022).
  6. Palagin, A.V., Petrenko, N.G., 2018. “Methodological foundations for development, formation and it-support of transdisciplinary research”. Journal of automation and information sciences. Vol. 50, no. 10. pp. 1-17. 
    https://doi.org/10.1615/JAutomatInfScien.v50.i10.10
  7. Palagin, A.V., 2013. “Problemy` transdiscziplinarnosti i rol` informatiki”. Kibernetika i sistemny`j analiz. N 5. pp. 3–13.
  8. Petrenko, N.G., Zelentsov, D.G., 2019. “On the practical use of ontological models of subject areas”. Computer modeling: analysis, management, optimization. N 2(6). pp. 58-73. 
    https://doi.org/10.32434/2521-6406-2019-6-2-58-73
  9. Palagin, A.V., 2006. “Arkhitektura ontologo-upravlyaemy`kh komp`yuterny`kh system”. Kibernetika i sistemny`j analiz. N 2. pp. 111–124.
  10. Palagin, A.V., 2016. “An Introduction to the Class of the ransdisciplinary Ontology-controled Research Design Systems”. Upravlausie sistemy i masiny. N 6, pp. 3-11 (In Russian).
    https://doi.org/10.15407/usim.2016.06.003
  11. Palahin, O., Kurhaiev, O., 2009. “Mizhdystsyplinarni naukovi doslidzhennia: optymizatsiia systemno-informatsiinoi pidtrymky”. Visn. NAN Ukrainy. N 3. pp. 14–25. (In Russian).
  12. Palagin, A.V., Petrenko, N.G., Kryvyj, S.L., 2015. “To the Question of Constructing Knowledge-Oriented Computer Systems for Scientific Research”. Upravlausie sistemy i masiny. N 2. pp. 64–73.
  13. Booch, G., Rumbaugh, J., Jacobson, I., 2005. The Unified Modeling Language User Guide. Addison-Wesley. Reading. MA. 475 p.
  14. Shmuller, D., 2005. Osvoj samostoyatel`no UML 2 za 24 chasa. Prakticheskoe rukovodstvo.Sams Teach Yourself UML in 24 Hours, Complete Starter Kit. M.: Vil`yams, 416 p. ISBN 0-672-32640-X.
  15. Leonenkov, A.V., 2007. Samouchitel UML SPb.: BKhV-Peterburg, 576 p. ISBN 978-5-94157-878-8 (In Russian).
  16. OWL 2 Web Ontology Language Primer. [Online]. <http://www.w3.org/TR/2012/REC-owl2-primer-20121211/> (date of access: 23.06.2022).
  17. Horridge, M. A Practical Guide to Building OWL Ontologies Using Protégé 4 and CO-ODE Tools. Edition 1.3. Copyright The University Of Manchester. March 24, 2011. 107 p.
  18. Apache Jena Fuseki. [Online]. <https://jena.apache.org/documentation/fuseki2/> (date of access: 23.06.2022).
  19. DuCharme, B., 2013. Learning SPARQL. Querying and Updating with SPARQL1 (Second edition), O’Reilly Media, All rights reserved, August 2013. 367 p.

Received 18.07.2022