Uncertainty is a normal part of everyday life. It appears in the environment around us from the weather to the stock market, internally to some degree in almost every plan or decision we make, and is inherent in our daily communication, both verbal and visual. The form this uncertainty takes is often qualitative or unquantified and so fits poorly with the initial issues of representation, computability, and efficiency often the driving forces in initial visualizations of information. Understanding what may assist in visualizing uncertainty is the subject of this research. Initially I provide a literature review of existing work in uncertainty visualization. This review continues with an exploration of heuristic evaluation specifically on uncertainty visualization but then looks deeper at the process of heuristic evaluation itself. Moving toward user constraints and cognitive tasks I coalesce existing work relating to reasoning under uncertainty. From this I propose further linking and integrating the uncertainty visualizations into the process of reasoning which encompasses all visualization tasks. The second half of the dissertation turns to investigate uncertainty visualization in specific domains. In the first domain, results of research into visualizing temporal uncertainty in archaeological reconstructions are provided. This is followed by visualizations developed for uncertainty in rock property modelling in the seismic domain. The final domain of evidence-based medical diagnosis is explored with an observational study, participatory design of new visual support, and a final evaluation. Finally I present a framework for assisting with the development of visualizations dealing with uncertainty by breaking out several important factors and cognitive tasks to consider based on generalizing and applying the practical and theoretical developments. In summary my contributions include specific visualizations for particular application domains along with more general aspects relating to evaluation, applicability of cognitive theory, and a framework to aid uncertainty visualization.
@PhdThesis{ zuk:2008:VU,
author = {Torre D. Zuk},
title = {Visualizing Uncertainty},
school = {Department of Computer Science, University of Calgary},
year = {2008},
}