Digital Decision Support System Prototyping for Building Performance Analysis and Management

The ongoing transformation of the AECO sector towards digitalization has led to a growing need for digital decision support systems (DDSS) to aid in managing built heritage. While there have been many technological improvements in this area, creating these digital tools still demands substantial technical and financial investments and highly specialized IT competencies. To respond to this challenge, this paper presents BTwin, a toolkit developed to facilitate the prototyping processes of DDSSs for performance-oriented building management. This open-source software, implemented in Python, allows for integrating building data from multiple sources into graph networks, such as building information models and building performance simulations, meters, and sensors. This integration capability, supported by specific semantic and ontological rules, is complemented by the possibility of quickly displaying the data on interactive dashboards accessible to non-expert users. After explaining the theoretical framework behind the toolkit, the paper showcases its practical application in a university building, focusing on energy- and occupancy-related topics.