”cityjson2rdf” a Converter for Producing 3d City Knowledge Graphs

Abstract

Abstract. The increasing prevalence of 3D city models (3DCMs) in various applications, such as mixed reality and navigation, highlights the need for efficient data exchange. CityGML serves as a standard model for this purpose, encompassing geometric and semantic information in 3DCM data. To enhance interoperability, a compatible transfer mechanism is essential. This study introduces a conversion tool that transforms CityGML data into RDF, a knowledge graph (KG) format. Utilizing semantic web technologies, this conversion ensures the data’s seamless integration across applications. The RDF model facilitates linking to open ontologies, promoting data circulation without loss. The tool employs CityJSON encoding for its mappable JSON structure, enabling straight-forward conversion to RDF using Python components. While existing XML to RDF tools exist, this tool distinguishes itself by addressing accessibility and user intervention challenges. Linking is established by matching subject classes with relevant ontology definitions, a process dependent on developers’ understanding of the CityGML data model. The tool, accessible through URL-2, is still in development, offering a promising solution for achieving effective 3DCM data interoperability.