A Perceptual Visualization Assistant for Multi-Dimensional Data Visualization
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2001-09-14
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This thesis describes a perceptual visualization assistant (ViA) designed to help usersconstruct perceptually salient visualizations to display high dimensional data stored in amulti-dimensional dataset. ViA focuses on (1) how to construct visualizations in an application-independent manner, (2) how to produce visualizations that support effectiveexploration, discovery, and analysis, and (3) how to allow users to participate in this processto guarantee the resulting visualizations respect context and user preferences. Tosolve these issues we propose guidelines based on studies of human vision and human perception.Evaluation engines built from these guidelines will be used to evaluate the dataattribute to visual feature mappings in a given visualization. The results (evaluationweights and hints for improvement) will be used by a mixed-initiative search algorithm toidentify new visualizations with high potential for improvement. This allows ViA to selectivelysearch for the best possible visualizations for a user's dataset and analysis tasks.ViA allows user interaction during the search process by asking whether certain simplifyingassumptions can be made, and by allowing users to specify requirements and constraintsfor the visualizations ViA suggests. We tested ViA's abilities in two practicalapplication environments: weather data and e-commerce auction traces. Results from asubjective user questionnaire suggest that ViA's visualizations are as good or better thanexisting standards used to represent this type of data.
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Degree
MS
Discipline
Computer Science
