As urban data is becoming more complex, researchers are exploring the use of linked data for studying complex urban phenomena. However, mere transformation of heterogeneous data formats to formal knowledge graph formats such as Ontology Web Language (OWL) result in the loss of data. Therefore, we propose an automated approach based on standards to automatically transform conceptual models of urban data to OWL. In this article, we propose reusable configuration rules for transforming UML to OWL as well as the reasoning behind our choice. Our approach is demonstrated by the transformation of a 3D geospatial urban data model, CityGML 3.0, to a network of computational ontologies, informally entitled “CityOWL”. We also propose several alignments between the resulting ontologies and existing geospatial, semantic, and temporal linked data standards such as GeoSPARQL, SKOS, and OWL-Time.