A semantic web-based approach for generating parametric models using RDF

Farhad Sadeghineko*, Bimal Kumar, Warren Chan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)
157 Downloads (Pure)


Semantic-rich 3D parametric models, like Building Information Models (BIMs) are becoming the main information source during the entire lifespan of an asset. The use of BIM in existing buildings has been hampered by the challenges surrounding the limitations of existing technologies for developing retrofit models. Some progress has been recently made in generating non-parametric models from the Point Cloud Data (PCD). However, a proper fully developed parametric model is still some way away. In this paper, challenges are addressed by reviewing the state-of-the-art before presenting our approach. The aim of our approach is to apply the Semantic Web Technologies for generating parametric models using PCD as primary data. The Semantic Web as a set of standards and technologies is used for providing an appropriate framework for storing, sharing, and reusing the semantics of information on the web. Building elements are recognized in PCD, and the concept of Resource Description Framework (RDF) as a Semantic Web technology and a standard model for interchanging the data on the web is then used to markup detected elements. The RDF data is then standardized to Industry Foundation Classes (IFC) as an open standard building data model to generate the parametric model of the asset utilizing BIM software that supports IFC. Some parts of this ongoing research are performed manually, and the future work is to implement the process automatically. Primary results are quite promising and should be of interest to the modeling of all kinds of assets, in particular, Historical Building Information Modelling (HBIM).
Original languageEnglish
Title of host publicationAdvanced Computing Strategies for Engineering
Subtitle of host publication25th EG-ICE International Workshop 2018
EditorsIan F.C. Smith, Bernd Domer
Place of PublicationSwitzerland
PublisherSpringer Nature
Number of pages17
ISBN (Electronic)9783319916385
ISBN (Print)9783319916378
Publication statusPublished - 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • building information modelling (BIM)
  • semantic web
  • resource description framework (RDF)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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