This thesis aims to develop and implement a method for integrating additional data into a semantic city model. Specifically, the graph Database Management System (DBMS) Neo4j is used to expand a City Geography Markup Language (CityGML) data set, thereby creating an expandable urban knowledge graph. CityGML, an international standard for 3D city and landscape models, captures both geometric and semantic information, making it highly useful for urban planning and analysis. However, integrating additional data into CityGML presents challenges due to the complexity of the existing CityGML schema and differences in how data sets represent semantic and spatial features. To address this, a novel approach is proposed using Neo4j, a flexible graph database system, which supports a schemaless structure, allowing the integration of new data and relationships more easily than traditional methods. Additionally, data modelled as a Knowledge Graph (KG) lends itself to easy ad-hoc querying, making it possible to instantly analyse the expanded graph. The thesis outlines a concept that allows users without deep technical knowledge of CityGML or its schema to integrate data thematically relevant to them and query the enriched graph for their specific use cases. These queries can include both the filtering of thematic attributes like building functions as well as spatial ones, for example distance and area calculations. The concept was implemented by enriching a CityGML data set of downtown Munich with information from OpenStreetMap (OSM) buildings and Points of Interest (POIs). Through the use and development of spatial matching and KG integration algorithms, the CityGML knowledge graph was expanded with additional data. A Graphical User Interface (GUI) was also developed, helping users to thematically and spatially query the expanded graph database and instantly visualize the results without requiring in-depth knowledge of databases or query languages. The results showed that this approach is effective for data enrichment, enabling both spatial and semantic querying of the extended knowledge graph, as well as intuitive visualisation of the query results. However, limitations remain, such as the uncertainty of applicability in regard to highly specialized data or CityGML data sets from different regions with varying standards. Possible additions and adjustments to address these limitations are also discussed.     «

This thesis aims to develop and implement a method for integrating additional data into a semantic city model. Specifically, the graph Database Management System (DBMS) Neo4j is used to expand a City Geography Markup Language (CityGML) data set, thereby creating an expandable urban knowledge graph. CityGML, an international standard for 3D city and landscape models, captures both geometric and semantic information, making it highly useful for urban planning and analysis. However, integrating add...     »