%0 Journal Article %A Schneider, Georg F. %A Kontes, Georgios D. %A Qiu, Haonan %A Silva, Filipe J. %A Bucur, Mircea %A Malanik, Jakub %A Schindler, Zdenek %A Andriopolous, Panos %A de Agustin-Camacho, Pablo %A Romero-Amorrortu, Ander %A GrĂ¼n, Gunnar %T Design of knowledge-based systems for automated deployment of building management services %D 2020 * Elsevier B.V. %X Despite its high potential, the building's sector lags behind in reducing its energy demand. Tremendous savings can be achieved by deploying building management services during operation, however, the manual deployment of these services needs to be undertaken by experts and it is a tedious, time and cost consuming task. It requires detailed expert knowledge to match the diverse requirements of services with the present constellation of envelope, equipment and automation system in a target building. To enable the widespread deployment of these services, this knowledge-intensive task needs to be automated. Knowledge-based methods solve this task, however, their widespread adoption is hampered and solutions proposed in the past do not stick to basic principles of state of the art knowledge engineering methods. To fill this gap we present a novel methodological approach for the design of knowledge-based systems for the automated deployment of building management services. The approach covers the essential steps and best practices: (1) representation of terminological knowledge of a building and its systems based on well-established knowledge engineering methods; (2) representation and capturing of assertional knowledge on a real building portfolio based on open standards; and (3) use of the acquired knowledge for the automated deployment of building management services to increase the energy efficiency of buildings during operation. We validate the methodological approach by deploying it in a real-world large-scale European pilot on a diverse portfolio of buildings and a novel set of building management services. In addition, a novel ontology, which reuses and extends existing ontologies is presented. %@ 0926-5805 %K Building management services %K Knowledge-based systems %K Energy efficiency %K Knowledge engineering %K Ontology doi 10.1016/j.autcon.2020.103402 %U http://hdl.handle.net/11556/982 %~ GOEDOC, SUB GOETTINGEN