Applying Knowledge Graphs as Integrated Semantic Information Model for the Computerized Engineering of Building Automation Systems

During the life cycle of a smart building, an extensive amount of heterogeneous information is required to plan, construct, operate and maintain the building and its technical systems. Traditionally, there is an information gap between the different phases and stakeholders, leading to information being exchanged, processed and stored in a variety of mostly human-readable documents. This paper shows how a knowledge graph can be established as integrated information model that can provide the required information for all phases in a machine-interpretable way. The knowledge graph describes and connects all relevant information, which allows combining and applying it in a holistic way. This makes the knowledge graph a key enabler for a variety of advanced, computerized engineering tasks, ranging from the planning and design phases over the commissioning and the operation of a building. The computerized engineering of building automation systems (BAS) with an advanced software tool chain is presented as such a use case in more detail. The knowledge graph is based on standard semantic web technologies and builds on existing ontologies, such as the Brick and QUDT ontologies, with various novel extensions presented in this paper. Special attention is given to the rich semantic definition of the entities, such as the equipment and the typically thousands of datapoints in a BAS, which can be achieved as a combination of contextual modeling and semantic tagging.