DOI:https://doi.org/10.15407/kvt214.04.004
Cybernetics and Computer Engineering, 2023, 4(214)
Gladun A.Y.1, PhD (Engineering), Associate Professor,
Leading Researcher of the Department of Complex Research
of Information Technologies and Systems,
https://orcid.org/0000-0002-4133-8169,
e-mail: glanat@yahoo.com
Rogushina J.V.2, PhD (Phys.-Math.), Associate Professor,
Senior Researcher of the Automated Information Systems Department,
https://orcid.org/0000-0001-7958-2557,
e-mail: ladamandraka2010@gmail.com
Pryima S.M.3, DSc (Pedagogy), Professor,
Professor of the Computer Science Department,
https://orcid.org/0000-0002-2654-5610,
e-mail: pryima.serhii@tsatu.edu.ua
1International Research and Training Center for Information
Technologies and Systems of the National Academy of Sciences
of Ukraine and the Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine
2Institute of Software Systems of National Academy of Sciences of Ukraine,
40, Acad. Glushkov av., Kyiv, 03187, Ukraine
3Dmytro Motornyi Tavria State Agrotechnological University,
66, Zhukovskogo street, Zaporizhzhia, 72312, Ukraine
COMPLEX INFORMATION OBJECTS REPOSITORY AS A COMPONENT OF THE SEMANTIC ANALYTIC-INFORMATION WEB-ORIENTED SYSTEMS DEVELOPMENT
Introduction. The paper examines the issue of reusing ontological knowledge in semantic analytical and informational web-oriented systems and analyzes the problems that arise in the process of searching for and exporting such knowledge from external ontologies. It proposes to create a repository of complex information objects, which should expand the functionality of services provided by ontology repositories, and provide opportunities to search for elements of such ontologies at the content level, taking into account the semantics of the relationships between them. The work states the basic requirements for such a repository, analyzes the technologies that can be used to replenish it, and offers some examples of areas of its practical use. The proposed approach consideres on a practical example of the creation of a semantic directory for finding educational materials, which is oriented towards functioning in an open web environment and exporting information from external sources. The prototype of the system is implemented on the basis of the semantic extension of wiki technology, and the elements of the structure of complex information objects processed in the system are obtained from relevant external ontologies.
The purpose of the paper is to develop algorithms and methods of using formalized ontological knowledge of the subject area for the creation of applied semantically oriented information and analytical systems, to export knowledge from external ontologies, to create a repository of complex information objects with extended functionality of services.
The results. Development of the concept of a repository of complex information objects for applied systems of artificial intelligence, which provides a search for instances of various ontological classes connected by certain types of semantic relations. Improvement of existing functionalities of ontology repositories due to export of knowledge about the structure of CIO from external sources of knowledge and semantically marked documents. The developed algorithms and methods of creating repositories of complex information objects make it possible to analyze complex collections of different classes of information objects, interconnected by relationships, restrictions and rules for semantic analytical and informational web-oriented systems. The basic requirements for the repository are formed and the method of its replenishment is presented. The obtained results make it possible to create original intelligent information systems for artificial intelligence in the field of big data processing, cyber security, competence analysis when creating professional groups for the implementation of an innovative project, human resources management, finance and business, for companies that work with dynamically changing content of documents (jurisprudence , standardization, state authorities), national security, defense and military spheres.
Conclusions. The proposed original approach, algorithms and method for improving the repository of complex information objects, expanding its functionality and ensuring its replenishment due to the export of knowledge from external sources (Wikipedia, encyclopedias, dictionaries, repositories of scientific publications, directories) and semantically marked documents and tracking dynamic changes occurring in these sources and documents. A prototype of the semantic web-oriented system “e-Textbook” is created, which ensures the selection of relevant textbooks for teachers and students of educational institutions for work programs of educational disciplines. The application of ontologies and data in the “e-Textbook” system based on the semantic analysis of metadata and the determination of the semantic similarity of structural data models (ontologies, data) and the formation of a ranked set of related ontologies to solve the tasks.
Keywords: wiki, knowledge-oriented information resource, ontology, formal ontology model, intelligent information system, ontology repository, complex information object.
REFERENCES
1 Rogushina J.V. , Gladun A.Ya. The use of ontologycal knowledge for multi-criteria comparison of complex information objects. Problems of programming. 2022, N2-3. P. 249-259. URL: pp.isofts.kiev.ua/ojs1/article/view/526/523. pp 2022.03-04.249 (In Ukrainian)
https://doi.org/10.15407/pp2022.03-04.249
2 Guarino N. Formal Ontology and Information Systems. Formal Ontology in Information Systems. Proceedings of FOIS’98, by N. Guarino (ed.). Trento. Italy, Amsterdam, IOS-Press. 1998. P. 3-15 https://klevas.mif.vu.lt/~donatas/Vadovavimas/Temos/OntologiskaiTeisingas KoncepcinisModeliavi-mas/papildoma/Guarino98-Formal%20Ontology%20and% 20Informa-tion%20Systems.pdf
3 Rogushina J.V. Classification of means and methods of the Web semantic retrieval. Problems of programming. 2017. № 1. P. 30-50. (In Ukrainian)
https://doi.org/10.15407/pp2017.01.030
4 Rogushina J., Priyma S. Use of competence ontological model for matching of qualifications // Chemistry: Bulgarian Journal of Science Education, Volume 26, Number 2, 2017. P.216-228. http://elar.tsatu.edu.ua/bitstream/123456789/ 3181/1/2.pdf.
5 Gladun A.Ya., Rogushina J.V. Ontologies repository as a method to knowledge reusage for information objects recognition. Ontology of design, № 1 (7), 2013. P. 35-50.
6 FAIR_data. https://en.wikipedia.org/wiki/FAIR_data.
7 Rogushina, Y. V. (2023). Use of ontologies and semantic mediawiki for representation and retrieval of scientific data in the FAIR paradigm. CEUR Workshoop Proceedings. Vol. 2866. P. 61-73.
https://doi.org/10.30525/978-9934-26-277-7-200
8 Bassiliades N. EvdoGraph: A Knowledge Graph for the EVDOXUS Textbook Management Service for Greek Universities. Accepted for presentation at, 15th International Conference on Knowledge Engineering and Ontology Development (KEOD 2023), 13-15 Nov 2023, Rome, Italy. https://intelligence.csd.auth.gr/wp-content/uploads/2023/08/EvdoGraph-CR.pdf
https://doi.org/10.5220/0012153600003598
9 Bizer, C., Heath, T., & Berners-Lee, T. (2023). Linked data-the story so far. Linking the World’s Information: Essays on Tim Berners-Lee’s Invention of the World Wide Web (pp. 115-143).
https://doi.org/10.1145/3591366.3591378
10 Wylot M., Hauswirth M., Cudré-Mauroux P., Sakr, S. RDF data storage and query processing schemes: A survey. ACM Computing Surveys (CSUR). 2018, 51(4), 1-36.
https://doi.org/10.1145/3177850
11 Antoniou G., Van Harmelen F. Web ontology language: Owl. Handbook on ontologies. Springer Berlin Heidelberg, 2004, pp. 67-92.
https://doi.org/10.1007/978-3-540-24750-0_4
12 Hogan A., Blomqvist E., Cochez M., D’amato C., Melo G., Gutierrez C., Zimmermann A. Knowledge graphs. ACM Computing Surveys. 2022, 54(4), pp. 1-37.
https://doi.org/10.1145/3447772
13 Yu, L., & Yu, L. (2011). Linked open data. A Developer’s Guide to the Semantic Web. 2011, pp. 409-466.
https://doi.org/10.1007/978-3-642-15970-1_11
14 Bizer C., Heath T., Berners-Lee T. Linked datathe story so far. International journal on semantic web and information systems. 2009, 5(3), pp. 1-22.
https://doi.org/10.4018/jswis.2009081901
15 Stancin K., Poscic P., Jaksic D. Ontologies in education – state of the art. Education and Information Technologies. 2020, 25(6), pp. 5301-5320.
https://doi.org/10.1007/s10639-020-10226-z
16 Färber M. The Microsoft Academic Knowledge Graph: A Linked Data Source with 8 Billion Triples of Scholarly Data. ISWC 2019, LNCS. 11779, pp. 113-129. Springer.
https://doi.org/10.1007/978-3-030-30796-7_8
17 Jaradeh M. Y., Oelen A., Farfar K. E., Prinz M., D’Souza J., Kismihók G., Auer S. Open research knowledge graph: Next generation infrastructure for semantic scholarly knowledge. KCAP 2019 (pp. 243-246). ACM.
https://doi.org/10.1145/3360901.3364435
18 Abu-Salih, B. Domain-specific knowledge graphs: A survey. Journal of Network and Computer Applications. 2021, 185.
https://doi.org/10.1016/j.jnca.2021.103076
19 Vandenbussche P.-Y., Atemezing G. A., Poveda-Villalón M., Vatant B. Linked Open Vocabularies (LOV): A gateway to reusable semantic vocabularies on the Web. Semantic Web. 2017, 8(3), pp. 437-452.
https://doi.org/10.3233/SW-160213
20 Corson-Rikert J., Mitchell S., Lowe B., Rejack N., Ding Y., Guo C. The VIVO Ontology. VIVO, Synthesis Lectures on Data, Semantics, and Knowledge. 2012, pp. 15-33. Springer, Cham.
https://doi.org/10.1007/978-3-031-79435-3_2
21 Demartini G., Enchev I., Gapany J., Cudré-Mauroux P. The Bowlogna ontology: Fostering open curricula and agile knowledge bases for Europe’s higher education landscape. Semantic Web. 2013. 4(1), pp. 53-63.
https://doi.org/10.3233/SW-2012-0064
22 ESCO (the European Multilingual Classifier of Skills, Competences, Qualifications and Occupations. https://ec.europa.eu/esco/portal/home.
23 Vrandečić D., Krötzsch K. Wikidata: a free collaborative knowledgebase. Communications ACM. 2014, 10, pp. 78-85.
https://doi.org/10.1145/2629489
Received 30.08.2023