# Combined MvdXML and Semantic Technologies for Green Construction Code Checking
## 2 Research Background
### Code-Checking Approaches in Construction Industry
#### 2.3.2 Code Checking Based on Semantic Web  
There are some building codes computerizing systems based on ontology-based approaches and semantic web information. Ontology-based approaches focus on formalizing conformance requirements, which are conducted under knowledge extraction and semantic mapping [29]. Semantic web information is about how to enhance the IFC model using description language, which is based on a logic theory. [PERSON] et al. took advantage of the logical basis of Resource Description Framework (RDF), using semantic web technologies to support data interoperability and integrate relationshipsbetween semantic information and model information [30; 31]. The semantic web was built in a semantic network on the World Wide Web (WWW). In semantic web, objects and logical relationships between objects are displayed by graph. The Resource Description Framework (RDF) is a standard model for data interchange on the web [32; 33]. RDF is used for representing the graph structure, which provides expressions and statements to describe relationships between resources. RDF extends the linking structure of the web to use Unique Resource Identifiers (URIs) to name the relationship between things, as well as the two ends of the link. Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications. RDF is used in Web Ontology Language (OWL) to describe more complex ontologies [34; 35]. The ontological approach was also adopted by International Code Council (ICC) through the development of SMARTCodes in 2006. ICC establishes an International Energy Conservation Code (IECC) dictionary, which is a method of communication between regulations and building models [36]. In addition to IECC, [PERSON] et al. proposed a new system that supports geospatial data retrieval from multiple and complementary sources [37]. The system uses the SQWRL to support inference with complex queries and to enable combination of complementary and heterogeneous data. [PERSON] et al. explored an ontology-based semantic modeling approach of regulation constraints and proposed a meta model for construction quality inspection and evaluation, i.e., CQIECntology. Based on CQIEontology, the regulation constraints were modeled into OWL axioms and SWRL rules. Using these OWL axioms and SWRL rules, the regulation provisions imposed on construction quality inspection can be translated into a set of inspection tasks, before being associated with the specific construction tasks [38]. [PERSON] et al. extracted information from construction safety regulations and represented constrain rules with SWRL. The construction safety-checking processes were implemented in the JESS (Java Expert Shell System) engine [39]. [PERSON] et al. took advantage of the strength of BIM, ontology, and semantic web technology to establish an ontology-based framework for construction risk knowledge management in a BIM environment [40]. [PERSON] et al. proposed an ontology-based framework which would help accurately recognize domain knowledge and appropriate requirements for developing reusable concept modules [41]. [PERSON] et al. proposed a pragmatic method to check real-world-scale BIM models, which transforms BIM models into a well-defined OWL model. Rules were formalized by a structured natural language (SNL) designed intentionally to describe building regulations. The checking engine was based on Simple Protocol and RDF Query Language (SPARQL) queries on OWL models, which can effectively improve the time efficiency and deal with large-scale applications [42]. [PERSON] et al. combined the ifCOWL ontology with SWRL rules and performed a more intuitive and flexible extraction of building views than the MVD approach [43]. The objective of this study was to propose an approach to organize, store, and re-use green construction knowledge.