SMOF

The multidisciplinary nature of urban data, which encompasses areas, such as land management, environmental protection, and traffic management, presents significant challenges to effective urban governance. Each urban governance domain establishes unique standards and data-schema definitions tailored to their specific operational characteristics. To overcome these limitations, this study aimed to introduce an ontology framework that can support data fusion and urban governance applications in a flexible and efficient manner, while being compatible with various data standards and preserving semantic information.We successfully developed and implemented an ontology framework using semantic web technology based on diverse international and domestic standards. The framework can effectively addresses the challenges of data fusion and interoperability across diverse formats and standards.The shared files include SMOF.excel and SMOF.rdf files, which contain a hierarchical classification of generic entities, relationships, and properties.