Data analysis on complicated construction data sources: vision, research, and recent developments

Authors:
Lucio Soibelman;Jianfeng Wu;Carlos Caldas;Ioannis Brilakis;Ken-Yu Lin
Affiliations:
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA;Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA;Department of Civil, Architecture and Environmental Engineering, University of Texas at Austin, Austin, TX;Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI;Ming-Jian Power Corporation, Taipei, Taiwan
Venue:
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Year:
2006

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Abstract

Compared with construction data sources that are usually stored and analyzed in spreadsheets and single data tables, data sources with more complicated structures, such as text documents, site images, web pages, and project schedules have been less intensively studied due to additional challenges in data preparation, representation, and analysis. In this paper, our definition and vision for advanced data analysis addressing such challenges are presented, together with related research results from previous work, as well as our recent developments of data analysis on text-based, image-based, web-based, and network-based construction sources. It is shown in this paper that particular data preparation, representation, and analysis operations should be identified, and integrated with careful problem investigations and scientific validation measures in order to provide general frameworks in support of information search and knowledge discovery from such information-abundant data sources.