Research On Ontology-Based Information Retrieval Of IFC Components

With the development of BIM(Building Information Modeling)technology,large quantities of BIM data have been generated in the field of construction engineering.How to reuse these vast history BIM data is an urgent problem to solve.Although the IFC(Industry Foundation Classes)which is proposed as BIM data standard has proper architecture and is able to describe all of the information of building and construction industry,the complexities of the IFC specification and the lack of semantics lead that the management of IFC data is difficult.Therefore,this paper describes the research on ontology-based information retrieval of IFC components.First of all,an algorithm of parsing IFC schema and extracting the information of IFC components from IFC files are described.Secondly,according to the scope and purpose of the domain ontology developed in this paper,an ontology based on industry-wide standards and other knowledge is developed and an automatic ontology instantiation process is described based on data extracted from IFC files which also realizes the conversion of IFC format to RDF(Resource Description Framework)format.Then,a method of converting query language from human to SPARQL ontology query language is designed by nature language processing(NLP)to help in retrieving information from IFC files.And a method of partial IFC model extraction based on IFC ontology(IfcOWL)is also discussed to help in the reuse of retrieval results.Finally,this study establish a Web-based BIM component information retrieval platform to demonstrate and validate the application of ontology-based information retrieval of IFC components.Over all,this study proposes an information retrieval method for IFC components with the semantic advantage provided by the ontology,which can not only help people query the IFC files without understanding of the complexities of the IFC specification,but also proposes creative methodology for the research on the combination of BIM technology and semantic web technology.