Metrics for Quantifying the Similarities and Differences between IFC Files

Abstract

Recently, several papers reported problems in data exchange using industry foundation classes (IFC). However, most comparisons were made based on a visual check, a manual count, and observation of properties that were selectively chosen. This study proposes a set of metrics for quantifying the similarities and differences between IFC files. The proposed metrics include the similarity rate, the matching rate, the globally unique identifier (GUID) preservation rate, the missing rate, and the addition rate. A long-term goal of this study is to develop a set of metrics for quantifying the information exchange rate between two IFC files. Automated identification of modified information versus newly generated information is an unsolved challenge. The proposed metrics were used in analyzing 88 IFC files generated from different systems to demonstrate the potential use of the proposed metrics.