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Erschienen in:
Cooperative Team Work Analysis and Modeling: A Bayesian Network Approach Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Challenges of Big Data in the Age of Building Information Modeling: A High-Level Conceptual Pipeline

verfasst von : Conrad Boton, Gilles Halin, Sylvain Kubicki, Daniel Forgues

Erschienen in: Cooperative Design, Visualization, and Engineering

Verlag: Springer International Publishing

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Abstract

N-dimensional BIM models integrate many aspects of Architecture, Engineering and Construction (AEC) projects information. These models are well structured and allow users to practically query them, however they are more and more combined with other data sources, provided e.g. by Geographic Information Systems (GIS), Building Automation Systems (BAS) or Facility Management (FM) systems. Construction project managers are facing an important challenge related to making meaningful deduction from these heterogeneous data sets. In this context the current data mining approaches are showing their limitations. Big Data is then gradually getting a reality in the construction industry. This paper characterizes AEC project management data following the conceptual definition of Big Data and proposes a high-level conceptual pipeline aiming at bridging the gap between BIM-based related visualization works and information visualization domain.

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Vorheriges Kapitel Dynamic Content and User Identification in Social Semantic Tagging Systems
Nächstes Kapitel SMART: Design and Evaluation of a Collaborative Museum Visiting Application
Fußnoten
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Metadaten
Titel
Challenges of Big Data in the Age of Building Information Modeling: A High-Level Conceptual Pipeline
verfasst von
Conrad Boton
Gilles Halin
Sylvain Kubicki
Daniel Forgues
Copyright-Jahr
2015
Buch
Cooperative Design, Visualization, and Engineering

Print ISBN: 978-3-319-24131-9

Electronic ISBN: 978-3-319-24132-6

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-24132-6_6

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