Generic Language for Partial Model Extraction from an IFC Model Based on Selection Set

• Main Authors: Xueyuan Deng, Huahui Lai, Jiayi Xu, Yunfan Zhao
• Format: Article
• Language: English
• Published: MDPI AG 2020-03-01
• Series: Applied Sciences
• Subjects: building information modeling (bim); industry foundation classes (ifc); partial model extraction; query language; selection set
• Online Access: https://www.mdpi.com/2076-3417/10/6/1968

During data sharing and exchange of building projects, the particular business task generally requires a part of the complete model. This paper adopted XML schema to develop a generic language to extract the partial model from an Industry Foundation Classes (IFC) model based on the proposed Selection Set (called PMESS). In this method, the Selection Set was used to integrate users’ requirements, which could be mapped into IFC data. To ensure the validity of the generated partial IFC models in syntax and semantics, seven rules—including three basic rules for a valid IFC file, three extraction rules based on the Selection Set, and a processing rule for redundant information—were defined. Through defining PMESS-based configuration files, the required data can be extracted and formed as a partial IFC model. Compared with the existing methods, the proposed PMESS method can flexibly extract the user-defined required information. In addition, these PMESS-based configuration files can be stored as templates and reused in other tasks, which prevents duplicated work for defining extraction requirements. Finally, a practical project was used to illustrate the utility of the proposed method.