Труды КНЦ (Технические науки вып. 7/2023(14))

с последующим объединением частных онтологий в одну общую. В качестве экспериментального подтверждения работоспособности метода проведено преобразование источников данных о ДТП и погоде с их объединением в единой системе. По результатам объединения проведен пространственный анализ с выделением мест концентрации ДТП по г. Санкт-Петербургу. Список источников 1. Mishra R. K., Kumari C. L., Janaki Krishna P. S., Dubey A. Smart Cities for Sustainable Development: An Overview // Smart Cities for Sustainable Development. Springer, Singapore, 2022. P. 1-12. 2. Yakimov M. R. Features o f the Use o f Geoanalytical Data in the Development o f Transport Planning Documents // 2022 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2022 — Conference Proceedings. Institute o f Electrical and Electronics Engineers Inc., 2022. 3. Mashhadi A., Quattrone G., Capra L. The Impact o f Society on Volunteered Geographic Information: The Case of OpenStreetMap // OpenStreetMap in GIScience: Experiences, Research, Applications / ed. Jokar Arsanjani J. et al. Cham: Springer International Publishing, 2015. P. 125-141. 4. Parisi F., Grant J. Knowledge representation in probabilistic spatio-temporal knowledge bases // Journal o f Artificial Intelligence Research. 2016. Vol. 55. P. 743-798. 5. Parisi F., Grant J. On repairing and querying inconsistent probabilistic spatio-temporal databases // International Journal o f Approximate Reasoning. Elsevier Inc., 2017. Vol. 84. P. 41-74. 6. Dylla F., Lee J. H., Mossakowski T., Schneider T., Delden A. V., Ven J. V. D., Wolter D. A Survey o f Qualitative Spatial and Temporal Calculi // ACM Computing Surveys. 2017. Vol. 50, № 1. P. 1-39. 7. Wolter D., Lee J. H. Connecting qualitative spatial and temporal representations by propositional closure // IJCAI International Joint Conference on Artificial Intelligence. 2016. Vol. 2016-Janua. P. 1308-1314. 8. Freksa C., van de Ven J., Wolter D. Formal representation o f qualitative direction // International Journal o f Geographical Information Science. Taylor & Francis, 2018. Vol. 32, № 12. P. 2514-2534. 9. Shrinidhi L., Kadiresan N., Parameswaran L. Ontology Model for Spatio-Temporal Contexts in Smart Home Environments // IFIP Advances in Information and Communication Technology. Springer Science and Business Media Deutschland GmbH, 2021. Vol. 611 IFIPAICT. P. 113-124. 10. Кандрашина Е. Ю., Литвинцева Л. В., Поспелов Д. А. Представление знаний о времени и пространстве в интеллектуальных системах / под ред. Д. А. Поспелов. М.: Наука, 1989. 328 с. 11. Lopez X. GeoSPARQL — A geographic query language for RDF data A proposal for an OGC Draft Candidate Standard. 2012. P. 13. 12. Cox S. J. D., Little C. Time Ontology in OWL. 2017. 13. Baratis E., Petrakis E. G., Batsakis S., Maris N., Papadakis N. TOQL: Temporal ontology querying language // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer, Berlin, Heidelberg, 2009. Vol. 5644 LNCS. P . 338-354. 14. Nys G.-A., Ruymbeke M. Van, Billen R. Spatio-Temporal Reasoning in CIDOC CRM: An Hybrid Ontology with GeoSPARQL and OWL-Time // 2nd Workshop On Computing Techniques For Spatio- Temporal Data in Archaeology And Cultural Heritage. 2018. 15. Subramanian A., RR P. K., Vikkurthi M., & Buttigieg P. L. Semantic Harmonisation o f Numeric Data from Open Government Data // Proceedings o f the ACM India Joint International Conference on Data Science and Management of Data — CoDS-COMAD ’19. New York, New York, USA: ACM Press, 2019. P . 238-244. 16. Hoffart J., Suchanek F. M., Berberich K., & Weikum G. YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia // Artificial Intelligence. 2013. Vol. 194. P. 28-61. 17. Calvanese D., Cogrel B., Komla-Ebri S., Kontchakov R., Lanti D., Rezk M., Rodriguez-Muro M., Xiao G. Ontop: Answering SPARQL queries over relational databases // Semantic Web. IOS Press, 2017. Vol. 8, № 3. P. 471-487. Труды Кольского научного центра РАН. Серия: Технические науки. 2023. Т. 14, № 7. С. 79-85. Transactions of the Kola Science Centre of RAS. Series: Engineering Sciences. 2023. Vol. 14, No. 7. P. 79-85. © Смирнов А. В., Тесля Н. Н., 2023 83