A linked-data paradigm for the integration of static and dynamic building data in digital twins
Dimitris Mavrokapnidis, Kyriakos Katsigarakis, Pieter Pauwels, Ekaterina Petrova, Ivan Korolija, Dimitrios Rovas
Abstract
Digital Twins is an emerging field of research, mainly because they span the entire building lifecycle promising to uncover hidden inefficiencies and deliver data-driven applications. Broadly defined as real-time digital representations of physical assets, Digital Twins require a connection between static and real-time data. However, building information is usually stored in different formats across the lifecycle, making data integration a challenging task. We hereby often rely on linked data technologies, yet overall system integration approaches with multiple types of data sources. In this work, a data linking methodology is proposed to combine static building design data from Industry Foundation Classes (IFC) and dynamic data using the Brick Schema; a domain ontology which configures data analytics applications during the operational phase. To facilitate this integration, we develop a tool to facilitate the linking of building topology, product, and sensor data using the two schemata. The implementation of our methodology in a real test case demonstrates its significance in combining diverse data sources which can be an important step for the delivery of Digital Twin applications.