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Rethinking Visualization: A High-Level Taxonomy

Abstract

We present a novel high-level visualization taxonomy. Our taxonomy classifies visualization algorithms rather than data. Algorithms are categorized based on the assumptions they make about the data being visualized; we call this set of assumptions the design model. Because our taxonomy is based on design models, it is more flexible than existing taxonomies and considers the user?s conceptual model, emphasizing the human aspect of visualization. Design models are classified according to whether they are discrete or continuous and by how much the algorithm designer chooses display attributes such as spatialization, timing, colour, and transparency. This novel approach provides an alternative view of the visualization field that helps explain how traditional divisions (e.g., information and scientific visualization) relate and overlap, and that may inspire research ideas in hybrid visualization areas.

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Authors
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Supplemental Material
Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Full Paper in Proceedings)
Event Title
IEEE Symposium on Information Visualization 2004 (InfoVis04)
Divisions
Visualization and Data Analysis
Subjects
Computergraphik
Event Location
Austin, Texas
Event Type
Conference
Event Dates
October 10-12
ISSN/ISBN
0-7803-8779-3
Date
October 2004
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