Collaborative work in the construction industry has always been one of the problems solved by BIM (Building Information Modeling) technology. The integration of IFC (Industry Foundation Classes) data as a general building information standard is one of the indispensable functions in collaborative work. The most practical approach of merging IFC data depends on GUID (Global Universal Identifier) comparison at present. However, GUID is not stable in current applications and often changes when exported. The intact representation of relationships between IFC entities is an essential prerequisite for proper association of IFC entities in IFC mergence. This paper proposes a graph‐based method for IFC data merging. The IFC data are represented as a graphical data structure, which completely preserves the relationship between IFC entities. IFC mergence is accomplished by associating other data with an isomorphic graph that is obtained by mining the IFC graph. The feasibility of the method is proven by a program, and the method can ignore the impacts of GUID and other factors.

Compliance checking is a very important step in engineering construction. With the development of information technology, automated compliance checking (ACC) has been paid more and more attention by researchers. One of the most important steps in automated compliance checking is the representation of the code information. However, the relationship constraint is often ignored in the code information and spatial geometric relationship is challenging to represent. The general code representation method does not have enough ability to identify the situation that does not meet the checking conditions because it is easy to cause semantic ambiguity in the checking results. This paper proposes a code representation method, and the building code information is represented in five parts. Relationships in the engineering domain and spatial relationships can be represented in constraint mode; different spatial relationship constraint-checking methods are also explicated. Constraint subject and constraint item can distinguish checking conditions and requirements, which supports semantic checking results. The mapping between the building information ontology and the code concepts is established, which can be used to automatically generate reasoning rules for compliance checking. Finally, the proposed method is verified by the representation of the China Metro Design Code and the application of the actual Metro model.

The Industry Foundation Classes (IFC) standard has been widely implemented as an open data standard in the architecture, engineering, and construction (AEC) industry. IFC enables robust information representation and facilitates cross-disciplinary collaboration, serving as a critical data foundation for future intelligent development in the engineering field. However, current IFC research topics remain relatively fragmented, and there are still several challenges in the practical implementation of IFC. Therefore, this paper provides a comprehensive review of IFC research over the past two decades. The research progress is systematically summarized in three key areas: IFC applications, interoperability, and data processing. Through this review, the limitations in IFC development have been discussed, and future research directions are proposed. This paper aims to provide a comprehensive perspective on addressing data-related challenges in the AEC industry and contributes to facilitating the deep integration of emerging technologies such as artificial intelligence within the AEC domain.

The growing complexity of railway infrastructure projects has created greater demand for knowledge-driven and collaborative design approaches. However, existing digital design approaches mainly focus on data exchange and model representation, while challenges remain, including semantic inconsistencies in multidisciplinary information, insufficient formalization of engineering knowledge, and limited reuse of parametric components. To address these issues, this study proposes an ontology-based, knowledge-driven framework for railway infrastructure design by integrating semantic modeling, rule-based reasoning, and IFC-based parametric component generation. First, a modular Railway Survey and Design Ontology (RSDO) is developed to provide a unified semantic representation of multidisciplinary engineering entities, spatial relationships, components, attributes, and measurement units. Existing ontologies, including BOT, BPO, and QUDT, are reused and extended to improve semantic interoperability across the railway survey and design stages. Second, a rule-transformation approach is proposed to convert engineering standards and expert knowledge into executable SWRL reasoning rules and SPARQL queries, thereby enabling rule-based design decision support and semantic retrieval of engineering knowledge. Third, a strategy for constructing an IFC-based parametric component library is established, incorporating knowledge-driven parametric generation to support reusable and software-independent component modeling. A tunnel portal design case study is conducted to demonstrate and validate the proposed framework. The results demonstrate that the framework can integrate heterogeneous survey and design information, infer design-related knowledge through semantic reasoning, and generate IFC-based parametric components containing both geometric and semantic information. The proposed framework provides a knowledge-driven approach to automated design decision-making and knowledge reuse in railway infrastructure design.