Towards Urban Data Interoperability: A Brick-Based Semantic Architecture for Smart Building Data Spaces

Abstract

Smart city ecosystems increasingly depend on heterogeneous data generated by buildings, sensors, and urban infrastructures. However, the lack of common semantic models limits interoperability, data reuse, and the integration of smart building information into broader urban data spaces. This paper proposes a Brick-based semantic architecture for smart building data spaces, aimed at enabling standardized representation, integration, and querying of IoT-generated data. The proposed approach models the physical and logical infrastructure of Building 11C at Escuela Superior Politecnica del Litoral (ESPOL), including laboratories, outdoor areas, zones, equipment, and sensors, using Brick Schema and RDF-based representations. The architecture integrates IoT data acquisition, semantic modeling, operational storage, and interactive visualization. Sensor data are collected through MQTT and Node-RED workflows, stored in MongoDB, and semantically linked to a Brick-based RDF graph managed through Apache Jena Fuseki. Custom semantic properties are introduced to connect Brick entities with operational sensor records, enabling traceability between data points, physical locations, and building assets. A Django backend and ReactFlow-based interface support data access, management, and visualization of the semantic graph. The case study demonstrates that Brick can provide a consistent semantic layer for reducing ambiguity, improving interoperability, and supporting the integration of smart building data into future smart city data spaces.