Visual Analytics Methods to Support Sensemaking under Ambiguity in Avalanche Forecasting

Analysis of complex systems involves much more than what is evident in data alone. Background knowledge and experience are used to inform interpretation. Often this results in ambiguity, a state where multiple potential interpretations must be considered and evaluated. When analysis is shared these challenges are compounded by the complexity of communication. Ambiguity is common in avalanche forecasting. Simon Fraser University and Avalanche Canada are conducting research investigating how novel visual analytics methods can better address the ambiguities that avalanche forecasters face in their work. Drawing the domains visual analytics, human computer interaction, and complex systems engineering this research project will utilize a lab and field-based mixed methods approach to design, develop, and evaluate visual analytics technologies aimed to support reasoning under ambiguity in avalanche forecasting.

Intern: 
Stan Nowak
Faculty Supervisor: 
Lyn Bartram
Province: 
British Columbia
Partner University: