A simplified relational database schema for transformation of BIM data into a query-efficient and spatially enabled database

- We present the transformation of IFC schema into a simplified RDBMS schema
- Transformation rules ensure there is no loss of data into the star-like schema
- The schema includes geometry data integration allowing spatial queries
- The schema's effectiveness is tested with queries against realistic models
- The schema allows users to efficiently search building elements for rule checking purpose

With the rising adoption of BIM in the AECO (Architecture, Engineering, Construction and Owner-operator) industry, BIM content is increasingly more complete and valuable. Unfortunately, the data is largely locked inside the respective BIM authoring tool with limited facility for users to perform queries beyond simple queries on objects and their properties. Even with the use of open data exchange format such as IFC (Industry Foundation Classes), getting the data out of BIM is still not an easy task. This research focuses on defining a schema and transformation rules to bring BIM data into a form that is easily queried. The schema is defined using popular relational database structure following an established star schema model that is well-defined within the data warehouse domain. The primary aim of the concept is to allow flexible and efficient queries into the BIM data using standard SQL that removes restrictions on predefined queries, effectively transforming BIM data into an open and queryable database. Another major contribution of this research is the significant potential for supporting spatial queries. This is a critical feature often neglected in the current approach to BIM-based databases. This paper presents the integration of spatial operations into standardized SQL queries making the BIM data accessible for wide ranges of query capabilities. Such feature will allow much better visibility into BIM data for better decision-making processes.