ABSTRACT
Although Building Information Modelling (BIM) promised a new collaborative work paradigm for the AEC disciplines, current workflows in the AEC sector are still sequential, fragmented, and served by diverse software, especially in the building performance disciplines. The building performance domain has multiple native performance models and data schemas from a wide variety of simulation tools, which leads to incompatible, incomplete, or redundant information and the need for rework in the current performance analysis workflows. A new paradigm is needed, in which performance domain analytical models can be prepared automatically from a database system that can also check for and maintain consistency, accuracy, and completeness within and across federated building models. This paper describes a BIM platform consisting of a holistic ontological framework for building performance modeling with cloud and semantic web technologies and founded on a knowledge-graph-driven database management system. It describes a future state-of-the-art configuration designed to address these challenges. It also outlines the suggested method and the potential workflow benefits in the AEC sector. The paradigm design is intended for software vendors, who can apply its principles to develop new generation software programs in the future.
