We identify quantifiable rules for testing a good quality IFC file.We define classifications of the validation rules including syntax and semantics.We outline initial list of validation rules covering all aspects of IFC testing.The validation rules include well defined rules for geometry and spatial related tests.We propose rules for automated IFC import testing. The use of IFC as a standard format in exchange processes has been increasing as the industry begins to address the need of interoperability. A current problem with the use of IFC is in the quality of product models. Much effort has addressed this issue in the form of certifications to ensure a minimum quality of exchange requirements for an IFC file. However, even with the recent increasing awareness and effort to improve the quality of IFC files, the process is still too tedious, time consuming and requires manual efforts by experts. Even if those resources are available, there is currently no clear and quantifiable definitions of what exactly is a good quality IFC file. Without such measures, the adoption of IFC as standard exchange format will be hindered and the industry will be left with only restricted alternatives that are mostly vendor dependent. This paper sets out to address this issue in two aspects: first by defining what a good quality IFC model is, and second by proposing rules that can be automated to measure with confidence the completeness and correctness of the IFC model. These two aspects will serve as a starting point toward a more comprehensive and quantifiable measures of the quality of an IFC file. This proposed goal is represented by using well defined and well documented rules collected from various projects the authors had experienced over the years. The rules include all known aspects of IFC, including geometry, which currently requires mostly manual validation. The paper also proposes a method to address import validation that is under-developed compared to the export validation.
['Wawan Solihin', 'Charles M. Eastman', 'Yong-Cheol Lee']
Toward robust and quantifiable automated IFC quality validation