Year: 2025
Type: article
Abstract: Rapid urbanization and the proliferation of heterogeneous urban data have intensified the challenges of semantic interoperability and integrated urban governance. To address this, we propose the Smart City Ontology Framework (SMOF), a standards-driven ontology that unifies Building Information Modeling (BIM), Geographic Information Systems (GIS), Internet of Things (IoT), and relational data. SMOF organizes five core modules and eleven major entity categories, with universal and extensible attributes and relations to support cross-domain data integration. SMOF was developed through competency questions, authoritative knowledge sources, and explicit design principles, ensuring methodological rigor and alignment with real governance needs. Its evaluation combined three complementary approaches against baseline models: quantitative metrics demonstrated higher attribute richness and balanced hierarchy; LLM as judge assessments confirmed conceptual completeness, consistency, and scalability; and expert scoring highlighted superior scenario fitness and clarity. Together, these results indicate that SMOF achieves both structural soundness and practical adaptability. Beyond structural evaluation, SMOF was validated in two representative urban service scenarios, demonstrating its capacity to integrate heterogeneous data, support graph-based querying and enable ontology-driven reasoning. In sum, SMOF offers a robust and scalable solution for semantic data integration, advancing smart city governance and decision-making efficiency.
Source: Smart Cities
Authors: Xiaolong He, Xi Kuai, Xinyue Li, Zihao Qiu, Biao He, Renzhong Guo
Institution: Shenzhen University
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,413
Awards: G1055031426, G4079903954
OpenAlex ID: W7084500799