Semantic web of building information: Cloud based ‘real world’ building data
Semantic web of building information: Cloud based ‘real world’ building data

Authors

  • Timo Hartmann University of Twente, Engineering Technology
  • Jakob Beetz Eindhoven University of Technology, Built Environment
  • Thomas Krijnen Eindhoven University of Technology, Built Environment
  • Alexander Koutamanis TU Delft, Architecture and the Built Environment

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DOI:

https://doi.org/10.7480/spool.2014.2.934

Abstract

Information required by practicing architects, engineers, construction managers, building operators, asset managers, owners, and users becomes more and more distributed, detailed, and richer. BIG DATA is on the rise and this trend will not stop. We rather expect that this trend will further accelerate in the upcoming years as;

  • more and more sensor technologies will become widely available to access existing conditions in the built environment,
  • more and more information streams will be combined for various purposes, e.g. mobile data access information to space use in order to evaluate wireless infrastructure performance but also to establish building use patterns in post-occupancy evaluations, 
  • advanced design tools will allow for more detailed data-driven simulation of an increasing number of design alternatives in shorter time spans, and 
  • participatory efforts will involve an ever larger number of specialists and non-specialists that all provide information that needs to be accounted for during design and construction planning.

We expect that these will be key areas for research in the upcoming years. In this lighthouse project we made four important first steps to enable such research:

  • 3TU BIM Data Repository
  • Data format, standard, and dictionary map
  • Information use and exchange processes
  • Automated indexing methods

How to Cite

Hartmann, T., Beetz, J., Krijnen, T., & Koutamanis, A. (2014). Semantic web of building information: Cloud based ‘real world’ building data. SPOOL, 1(2), 37–41. https://doi.org/10.7480/spool.2014.2.934

Published

2014-11-10

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