ISSN:
 2380-6966

eISSN:
 2380-6974

All Issues

Volume 2, 2017

Volume 1, 2016





Big Data & Information Analytics

Open Access Articles

Introduction: Special issue on computational intelligence methods for big data and information analytics
Yang Yu
2017, 2(1): i-ii doi: 10.3934/bdia.201701i +[Abstract](2893) +[HTML](240) +[PDF](131.8KB)
Abstract:
Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM)
Jimmy Huang, Ali Asgary and Jianhong Wu
2016, 1(1): v-v doi: 10.3934/bdia.2016.1.1v +[Abstract](3121) +[PDF](92.0KB)
Abstract:
Professors Jimmy Huang, Ali Asgary and Jianhong Wu from York University in Canada have received $1, 650,000 through the Natural Sciences and Engineering Research Council of Canada's (NSERC) Collaborative Research and Training Experience (CREATE) Grants over six years to lead the industry program titled ``Computational Approaches for Advanced Disaster, Emergency and Rapid Response Simulation (ADERSIM)". The proposed Advanced Disaster, Emergency, and Rapid Response Simulation NSERC CREATE industry stream program will enhance Canada's capacities in public safety and emergency management through innovative training, research, and development of professionals in state-of-the-art simulations and emergency management information systems.

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A new training program in data analytics & visualization
James H. Elder
2016, 1(1): i-iii doi: 10.3934/bdia.2016.1.1i +[Abstract](2503) +[PDF](145.5KB)
Abstract:
The growing appreciation for the role of Big Data in addressing important problems and societal needs has led to many welcome developments, including the new journal we are celebrating with its inaugural issue today. In Toronto, an interdisciplinary network of faculty has been working together on big data problems for a number of years through the Centre for Information Visualization and Data-Driven Design (CIVDDD). Founded and Led by Nick Cercone (York) and supported by the Ontario provincial government, this network has brought together researchers in data analytics and visualization from York University, OCAD University and the University of Toronto with industry partners to tackle challenging Big Data problems. A key emphasis of CIVDDD is the importance of fusing analytics with powerful visualization methods that allow the full value of the data to be extracted.

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