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Dalhousie University

Project Leader(s): 

Dr. Jon Grant , Dalhousie University

Project team: 
Dr. Mike Dowd, Dalhousie University
Funding period: 
April 1, 2021 - March 31, 2021

Coastal resources are essential for their ability to provide ecosystem services valued by society including food, shoreline protection, flood control, recreation, and water purification (Costanza et al. 1997). This research project seeks to utilize mathematical and statistical techniques to predict the distribution of essential marine habitat and aid in its conservation. The research team is attempting to represent living biomass and associated ecosystems via quantitative descriptions of the physical and geological variables perceived to shape their habitat space.

Project Leader(s): 

Dr. John McHugh, Dalhousie University

Project team: 
Dr. William A. Aiello, University of British Columbia
Dr. José Fernandez, Simon Fraser University
Dr. Sudhakar Ganti, University of Victoria
Dr. Michael McAllister, Dalhousie Unversity
Dr. Michael L. McGuire, University of Victoria
Dr. Stephen Neville, University of Victoria
Dr. Alejandro Quintero, École Polytechnique de Montréal
Dr. Jean-Marc Robert, École de technologie superieure
Dr. Nur Zincir-Heywood, Dalhousie University
Non-academic participants: 
Funding period: 
April 1, 2021 - August 30, 2021
Project Leader(s): 

Dr. Jeannette Janssen , Dalhousie University & Dr. Evangelos Milios , Dalhousie University

Project team: 
Dr. Bill Aiello, University of British Columbia
Dr. Anthony Bonato, Ryerson University
Dr. Allan Borodin, University of Toronto
Dr. Hugh, Chipman, Acadia University
Dr. Malcolm Heywood, Dalhousie University
Dr. Nauzer Kalyaniwalla, Dalhousie University
Dr. Nur Zincir-Heywood, Dalhousie University
Funding period: 
September 1, 2021 - March 31, 2021

The development of the Internet and the World Wide Web has changed the way in which we gather information. No longer is information only available as in a library, with items catalogued in an orderly manner. More and more often, information is presented as it is in the World Wide Web: as a mass of items with interconnecting links. This research team aims to extract information from such web-like collections by considering both the content of the items and the link structure that connects them, and the interaction of both components.