An ontology-based analysis of the industry foundation class schema for building information model exchanges

被引:66
|
作者
Venugopal, Manu [1 ]
Eastman, Charles M. [2 ]
Teizer, Jochen [3 ]
机构
[1] Autodesk Inc, San Rafael, CA 94903 USA
[2] Georgia Inst Technol, Coll Comp & Architecture, Atlanta, GA 30332 USA
[3] RAPIDS Construct Safety & Technol Lab, Ettlingen, Germany
关键词
Building Information Modeling (BIM); Product or process modeling; Model view definitions (MVD); Industry Foundation Class (IFC); Ontology; Semantic Exchange Modules (SEM); REPRESENTATION;
D O I
10.1016/j.aei.2015.09.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Robust knowledge sharing frameworks between different stakeholders in a building project is of high priority. Industry Foundation Classes (IFC) provides a rich schema for interoperability through object-based transactions. However, IFC lacks semantic clarity in mapping entities and relationships, resulting in multiple definitions to map the same information between different federated models. The objective of this research is to examine IFC from a perspective of an ontological framework, which can make the IFC definitions more formal, consistent and unambiguous. Different methods of ontological approaches to engineering knowledge are reviewed. Various issues such as the need for a logical framework, the current semantic approaches in the AEC/FM industry, and advantages of building an ontology structure are addressed. A comparative study of the ontology and segments of the existing IFC schema definition are performed. This exercise reveals the ambiguous nature of current IFC definitions and proposes reforms such that data exchanges would be more semantically robust. An ontology would structure the overall interoperability of BIM tools by providing a formal and consistent taxonomy and classification structure for extending IFC and for defining subsets as model view definitions (MVD). (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:940 / 957
页数:18
相关论文
共 50 条
  • [41] Ontology-based design information extraction and retrieval
    Li, Zhanjun
    Ramani, Karthik
    AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2007, 21 (02): : 137 - 154
  • [42] The Information Systems Modeling with an Ontology-Based ERD
    Luo, Dershing
    PACIFIC ASIA CONFERENCE ON INFORMATION SYSTEMS 2005, SECTIONS 1-8 AND POSTER SESSIONS 1-6, 2005, : 1447 - 1455
  • [43] A hybrid ontology-based information extraction system
    Gutierrez, Fernando
    Dou, Dejing
    Fickas, Stephen
    Wimalasuriya, Daya
    Zong, Hui
    JOURNAL OF INFORMATION SCIENCE, 2016, 42 (06) : 798 - 820
  • [44] Ontology-based similarity for product information retrieval
    Akmal, Suriati
    Shih, Li-Hsing
    Batres, Rafael
    COMPUTERS IN INDUSTRY, 2014, 65 (01) : 91 - 107
  • [45] The Research and Application of Ontology-Based Information Retrieval
    Wulamu, Aziguli
    Zhou, Yuchao
    Zhang, Dezheng
    Li, Hui
    Rui, Haike
    PROCEEDINGS OF THE 2014 9TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2014, : 1980 - 1984
  • [46] Ontology-based Unstructured Information Organization and Retrieval
    Zhang, Peiyun
    Xie, Rongjian
    2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 1, PROCEEDINGS, 2009, : 408 - +
  • [47] Ontology-based requirements elicitation of information system
    Zhai, Li-Li
    Zhang, Tao
    Peng, Ding-Hong
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2013, 19 (01): : 173 - 180
  • [48] ONTOLOGY-BASED APPROACH TO DATA EXCHANGES FOR ROBOT NAVIGATION ON CONSTRUCTION SITES
    Karimi, Sina
    Iordanova, Ivanka
    St-Onge, David
    JOURNAL OF INFORMATION TECHNOLOGY IN CONSTRUCTION, 2021, 26 : 546 - 565
  • [49] Towards an Ontology-based Soil Information System
    Shu, Yanfeng
    Liu, Qing
    21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015), 2015, : 1462 - 1468
  • [50] An Industry-Oriented Ontology-Based Knowledge Model for Batch Process Automation
    Lepuschitz, Wilfried
    Lobato-Jimenez, Alvaro
    Gruen, Andreas
    Hoebert, Timon
    Merdan, Munir
    2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2018, : 1568 - 1573