Version 1
: Received: 31 October 2024 / Approved: 31 October 2024 / Online: 31 October 2024 (16:47:34 CET)
How to cite:
Kuai, X.; He, X.; He, B.; Liu, Y.; Zhao, Z.; Guo, R. Smart City Ontology Framework for Urban Data Integration and Governance Applications. Preprints2024, 2024102577. https://doi.org/10.20944/preprints202410.2577.v1
Kuai, X.; He, X.; He, B.; Liu, Y.; Zhao, Z.; Guo, R. Smart City Ontology Framework for Urban Data Integration and Governance Applications. Preprints 2024, 2024102577. https://doi.org/10.20944/preprints202410.2577.v1
Kuai, X.; He, X.; He, B.; Liu, Y.; Zhao, Z.; Guo, R. Smart City Ontology Framework for Urban Data Integration and Governance Applications. Preprints2024, 2024102577. https://doi.org/10.20944/preprints202410.2577.v1
APA Style
Kuai, X., He, X., He, B., Liu, Y., Zhao, Z., & Guo, R. (2024). Smart City Ontology Framework for Urban Data Integration and Governance Applications. Preprints. https://doi.org/10.20944/preprints202410.2577.v1
Chicago/Turabian Style
Kuai, X., Zhigang Zhao and Renzhong Guo. 2024 "Smart City Ontology Framework for Urban Data Integration and Governance Applications" Preprints. https://doi.org/10.20944/preprints202410.2577.v1
Abstract
The diverse, heterogeneous, and dynamic nature of urban data poses challenges for semantic integration and knowledge sharing in smart city applications. Traditional urban governance sectors often develop domain-specific data standards, which are insufficient for integrating and applying multi-source heterogeneous data. This article proposes the Smart City Ontology Framework (SMOF), leveraging ontology technology for semantic-level data sharing and interoperability across different industries. SMOF adopts a top-down integration strategy, harmonizing diverse data standards from IoT, BIM, and GIS into a cohesive structure. This research delineates the foundational components of SMOF, encompassing entities, relationships, properties, events, and rules, and outlines the methodology and principles underpinning its construction. We further develop a scalable, hierarchical classification system for entities, properties and relationships, adaptable for specific semantic applications. Through a fire emergency scenario, we exemplify SMOF's practical utility in knowledge representation and data mapping, highlighting its capacity for semantic querying within complex urban data ecosystems. Our findings indicate SMOF's significant role in fostering integrated urban data management, thereby enhancing data interoperability and applicability in diverse urban governance contexts.
Keywords
Smart city ontology framework; Urban Informatics Entities; urban governance; data integration
Subject
Engineering, Civil Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
