学位论文详细信息
Extending Building Information Modeling (BIM) interoperability to geo-spatial domain using semantic web technology
BIM;GIS;Interoperability;Semantic Web;IFC
Parvaresh Karan, Ebrahim ; Irizarry, Javier Building Construction Haymaker, John Guhathakurta, Subhro Liu, Ling Akinci, Burcu ; Irizarry, Javier
University:Georgia Institute of Technology
Department:Building Construction
关键词: BIM;    GIS;    Interoperability;    Semantic Web;    IFC;   
Others  :  https://smartech.gatech.edu/bitstream/1853/53213/1/PARVARESHKARAN-DISSERTATION-2014.pdf
美国|英语
来源: SMARTech Repository
PDF
【 摘 要 】

As Building Information Modeling (BIM) applications become more sophisticated and used within other knowledge domains, the limitations of existing data exchange and sharing methods become apparent. The integration of BIM and Geographic Information System (GIS) can offer substantial benefits to manage the planning process during the design and construction stages. Currently, building (and geospatial) data are shared between BIM software tools through a common data format, such as Industry Foundation Classes (IFC). Because of the diversity and complexity of domain knowledge across BIM and GIS systems, however, these syntactic approaches are not capable of overcoming semantic heterogeneity. This study uses semantic web technology to ensure the highest level of interoperability between existing BIM and GIS tools. The proposed approach is composed of three main steps; ontology construction, semantic integration through interoperable data formats and standards, and query of heterogeneous information sources. Because no application ontology is available to encompass all IFC classes with different attributes, we first develop an IFC-compliant ontology describing the hierarchy structure of BIM objects. Then, we can translate the building's elements and GIS data into semantic web standard formats. Once the information has been gathered from different sources and transformed into an appropriate semantic web format, the SPARQL query language is used in the last step to retrieve this information from a dataset. The completeness of the methodology is validated through a case study and two use case examples.

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