An iterative reference mapping approach for BIM IFCXML classified content compression

Abstract

Industry Foundation Classes (IFC) and Industry Foundation Classes XML (IFCXML) are widely accepted data frameworks and formats for information storage and exchange among building information models (BIM). IFCXML are comprehensive and compatible with the major BIM platforms; however, many studies suggest their complex structure often results in redundancy and inflexibility. Researchers have proposed various IFC compression methods to reduce file size and restructure data organization, such as partial model extraction, Solibri IFC Optimizer, and ACC4IFC. However, simplification often results in missing information or data leakage, and there has never been a compressor specific to IFCXML. To overcome these issues, this study proposed a conservative compression method that removes duplicated information while maintaining the data structure of IFCXML through an iterative reference mapping method. Based on the data structure and geometry of IFCXML, the algorithm identified three kinds of duplicate information: independent entity duplication (IED), cross-reference entity duplication (CED), and property-set entity duplication (PED). To validate the proposed compressing method, this study conducted a validation test on six typical BIM models and benchmarked with other existing compressors (Solibri IFC Optimizer and ACC4IFC). The outcomes suggested that the proposed model could compress IFCXML files by 18%-59% without losing information.