Collaborating Authors


Towards French Smart Building Code: Compliance Checking Based on Semantic Rules Artificial Intelligence

Manually checking models for compliance against building regulation is a time-consuming task for architects and construction engineers. There is thus a need for algorithms that process information from construction projects and report non-compliant elements. Still automated code-compliance checking raises several obstacles. Building regulations are usually published as human readable texts and their content is often ambiguous or incomplete. Also, the vocabulary used for expressing such regulations is very different from the vocabularies used to express Building Information Models (BIM). Furthermore, the high level of details associated to BIM-contained geometries induces complex calculations. Finally, the level of complexity of the IFC standard also hinders the automation of IFC processing tasks. Model chart, formal rules and pre-processors approach allows translating construction regulations into semantic queries. We further demonstrate the usefulness of this approach through several use cases. We argue our approach is a step forward in bridging the gap between regulation texts and automated checking algorithms. Finally with the recent building ontology BOT recommended by the W3C Linked Building Data Community Group, we identify perspectives for standardizing and extending our approach.

What IBM, the Semantic Web Company, and Siemens are doing with semantic technologies


The Semantics conference is one of the biggest events for all things semantics. Key research and industry players gathered this week in Leipzig to showcase and discuss, and we were there to get that vibe. Graphs are everywhere: we have social graphs and knowledge graphs and office graphs, and in the minds of most these have been associated with Facebook and Google and Microsoft. But the concept of Knowledge Graphs is broader and vendor-agnostic. All graphs can be considered as knowledge graphs, insofar as they represent information by means of nodes and (directional) edges.