LAUSR

Abstract In the healthcare industry, the BIM-based benchmarking approach was identified as an alternative method to improve the current laborious and error-prone benchmarking practice by reducing manual inputs required for data collection and entry. However, the current body of knowledge lacks a robust and consistent approach to obtain useful and reliable benchmarking data from heterogeneous models. To accomplish the BIM-based benchmarking for healthcare projects, this paper develops a formalized schema that aims to transform data stored in BIM models for obtaining useful and reliable benchmarking data focusing on Industry Foundation Classes (IFC) and Construction Operations Building Information Exchange (COBie). Based on findings from previous research combined with case studies using five real-world information models, it defines the sets of transformation processes applicable to different groups of benchmarking data classified according to their attributes. Through the validation, it was found that the schema generated benchmarking data with a reasonable range of deviation from their actual values.