NEED4Interoperability: An ontology-based data integration for municipal heat planning in Germany

Municipal heat planning in Germany plays a central role in achieving national decarbonisation goals but is impeded by fragmented, heterogeneous datasets and low data interoperability. This paper presents a compact and extensible ontology-based data integration framework developed within the NEED project, designed to overcome these challenges. At its core are the modular NEED ontologies, which adopt a system-oriented modelling approach to semantically represent physical and spatial entities, such as buildings, streets, and street segments, along with their attributes and geographic context. The framework builds on the The World Avatar architecture, using a virtual knowledge graph for semantic access to relational data and enabling cross-domain querying via SPARQL. A case study in Oberhausen, Germany illustrates how semantic mappings and structured queries enhance data accessibility, enable integrated calculations, such as heat line density, and support built-in interactive visualisation. The results demonstrate improved interoperability, query flexibility, and conceptual clarity, highlighting the potential of ontology-driven methods to streamline municipal energy planning and support scalable, and interoperable urban data infrastructures.