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Big Data in Civil Eng. 2015 : Special Issue of Automation in Construction - ELSEVIER: Big Data in Civil Engineering


When Apr 10, 2015 - Jan 31, 2016
Where N/A
Submission Deadline Sep 1, 2015
Notification Due Dec 1, 2015
Final Version Due Jan 15, 2016
Categories    big data   data mining   civil engineering

Call For Papers

Special Issue of "Automation in Construction":


Guest Editors:
Amir H. Alavi
Department of Civil and Environmental Engineering, Michigan State University, USA.

Amir H. Gandomi
Department of Civil Engineering, The University of Akron, USA.

Scope and Aims:
Recently, Big Data concept has received remarkable attention for tackling complex engineering problems. Among the engineering fields, Big Data analytics is notably impacting the Civil Engineering domain. The operation and maintenance of Civil Engineering systems are now undergoing noticeable transformation as a result of huge amount of information provided by emerging testing and monitoring systems. The key role of Big Data in this transformation is well-understood. Despite the significance of the Big Data technologies to process large-scale data, current Civil Engineering information systems are still lacking in successful implementation of them. This special issue strives to review the development and key applications of new Big Data tools and methods in Civil Engineering area. This special issue can serve as a valid reference for a successful application of Big Data to challenging Civil Engineering problems.

Topics of interest in Civil Engineering domain include (but not limited to):

• Construction Management
• Structural Engineering and Health Monitoring
• Environmental Engineering
• Highway and Transportation Engineering
• Hydraulics and Water Power Engineering
• Materials Science and Engineering
• Geotechnical Engineering
• Earthquake Engineering
• Coastal and Harbor Engineering
• Tunnel Engineering
• Surveying and Geo-Spatial Engineering
• Geomatics, Geosciences, Remote Sensing, Geographical Information systems (GIS)
• Information Technology (IT) in Civil Engineering

In particular, contributions in the following themes are welcome:
• Innovative Algorithms, Software Solutions and Methodologies for Data Collection and Analysis of Big Data
• New Tools and Methods for Deploying and Managing Uncertainty and Risk in Big Data
• Big Data Case Studies
• Security and Privacy of Big Data
• Data-Driven Optimal Planning and Scheduling

Topics of interest in Big Data Processing include, but are not limited to:

• Data Mining
• Pattern Recognition
• Machine Learning
• Classification
• Cluster Analysis
• Data Fusion and Integration
• Time Series Analysis
• Visualisation
• Ensemble Learning
• Optimization
• Predictive Modeling
• Signal Processing
• Spatial Analysis
• Outliers Identification
• Missing Data Imputation
• Cloud Computing

Call for papers: April 2015
Deadline for submission of manuscripts: September 01, 2015
Review period: September 01- December 01, 2015
Revision and re-review (if required) January 15, 2016
Final decision due: January 31, 2016

Final compilation and submission of Editorial/Introduction: February 29, 2016
Publication of the special issue: March/April 2016

Submission Format and Guideline
All submitted papers must be clearly written in excellent English and contain only original work, which has not been published by or is currently under review for any other journal or conference. Papers must not exceed 25 pages (one-column, at least 11pt fonts) including figures, tables, and references. A detailed submission guideline is available as “Guide to Authors” at:

All papers to be published in this special issue should contain discussion and conclusions pertaining to the implications of the presented research on the construction industry in general, and on construction processes in particular.
All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select “SI:BIG DATA IN CIVIL ENG” when they reach the “Article Type” step in the submission process. The EES website is located at:

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