BIM to GIS: Multi-Criteria Queries for Material Tracking in Circular Built Environments

This study proposes a lightweight approach to BIM-GIS integration for circular economy applications, focusing on timber component repurposing in the Norwegian housing stock. Rather than emphasizing detailed geometric representations, we address key challenges in material stock assessment by prioritizing semantic data. Using the Level of Information Need (LOIN) framework, we identify critical parameters for timber reuse based on European standards EN 14080 and EN 14081. We implement a GeoJSON-based method that selectively extracts purpose-specific information from IFC models, achieving an 80.73% reduction in data volume while preserving all required semantic attributes. This enables multi-criteria queries linking 525 timber components to a cadaster dataset of 14,081 detached houses in Trondheim. Validation results confirm complete semantic data retention and sub-3-second query execution on standard GIS hardware. By focusing on essential material attributes rather than computationally intensive 3D models, the method supports scalable material stock assessments and efficient identification of reusable components. These findings demonstrate that selective information extraction enhances computational performance while maintaining decision-critical detail. Future work should explore ontology-driven approaches to improve multi-domain interoperability and enable more advanced semantic querying.