A Digital Twin Ontology Based on Open Standards for Integrating Heterogeneous Smart City Metadata

In sensor systems, a critical component of smart cities, two major challenges exist. First, the silo phenomenon, where sensor services operate independently without integration between them. Second, the issue of heterogeneity, where variations in sensor data formats and information make interpretation difficult. These challenges hinder the realization of digital twins. To address these issues, we propose an ontology-based approach that leverages the open standard OGC SensorThings API, embedding the advantages of this structure while providing clear semantic definitions for elements and relationships. In particular, to optimize metadata-related queries, we define an “IndexPoint” to link measurements be- tween metadata. To validate this approach, we conducted experiments comparing query processing times after loading RDF data, including sensors currently in use within real smart city environments. The experimental results confirmed that the proposed OWL structure is enhanced for metadata-oriented queries.