Challenges of Big Data in the Age of Building Information Modeling: A High-Level Conceptual Pipeline. Boton, C., Halin, G., Kubicki, S., & Forgues, D. In Cooperative Design, Visualization, and Engineering, of Lecture Notes in Computer Science, pages 48–56, Marjoque, Espagne, September, 2015. Springer International Publishing.
Challenges of Big Data in the Age of Building Information Modeling: A High-Level Conceptual Pipeline [link]Paper  doi  abstract   bibtex   
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.
@inproceedings{boton_challenges_2015,
	address = {Marjoque, Espagne},
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Challenges of {Big} {Data} in the {Age} of {Building} {Information} {Modeling}: {A} {High}-{Level} {Conceptual} {Pipeline}},
	copyright = {©2015 Springer International Publishing Switzerland},
	isbn = {978-3-319-24131-9 978-3-319-24132-6},
	shorttitle = {Challenges of {Big} {Data} in the {Age} of {Building} {Information} {Modeling}},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-24132-6_6},
	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.},
	language = {en},
	urldate = {2016-04-19},
	booktitle = {Cooperative {Design}, {Visualization}, and {Engineering}},
	publisher = {Springer International Publishing},
	author = {Boton, Conrad and Halin, Gilles and Kubicki, Sylvain and Forgues, Daniel},
	editor = {Luo, Yuhua},
	month = sep,
	year = {2015},
	doi = {10.1007/978-3-319-24132-6_6},
	keywords = {Architecture, engineering and construction, Artificial Intelligence (incl. Robotics), BIM, Big data, Computer Communication Networks, Computer-Aided Engineering (CAD, CAE) and Design, Database Management, Information Systems Applications (incl. Internet), Information Visualization, Information pipeline, User Interfaces and Human Computer Interaction, pratiques BIM},
	pages = {48--56}
}

Downloads: 0