OCAD University Open Research Repository

CIVDDD collaborative research in big data analytics and visualization

Whitmer, Barbara (2013) CIVDDD collaborative research in big data analytics and visualization. In: Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research.

Full text not available from this repository.
Official URL: http://dl.acm.org/citation.cfm?id=2555523.2555560

Abstract

The Centre for Innovation in Information Visualization and Data-Driven Design (CIVDDD) is a Big Data research project collaboration funded by the Ontario Research Fund — Research Excellence (ORF-RE). Research collaborators in the project include York University, OCAD University, the University of Toronto, and private sector partners (PSPs) to develop the next generation of data discovery, design, analytics, and visualization techniques for new computational tools, representational strategies, and interfaces. As the preeminent research hub for information analytics and scientific visualization in Ontario, CIVDDD has fifteen research teams in the four theme areas of Bioinformatics and Medical Applications, Interactive Visualization, Textual Visualization, and Scientific Visualization. The Workshop included a brief overview of CIVDDD research by the Principal Investigator Dr. Amir Asif, followed by three CIVDDD team presentations and demonstrations related to CASCON 2013 themes. These included: Graph Analytics and Biological Network Structures (Big Data and Cloud Computing), Social Media Data Visualization (Social Computing), and Dynamic Carbon Mapping in Urban Environments (Mobile Computing). Each Workshop presentation contained academic researchers and their private sector partner research collaborators. Each presentation was followed by a demonstration of the research application or visualization, and Q&A. An open discussion concluded the Workshop.

Item Type: Conference/Workshop Item (Paper)
Date Deposited: 28 Jun 2016 00:50
Last Modified: 02 Aug 2021 08:42
URI: https://openresearch.ocadu.ca/id/eprint/1000

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