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Proceedings Paper

An evaluation of methods for encoding multiple 2D spatial data
Author(s): Mark A. Livingston; Jonathan Decker; Zhuming Ai
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Paper Abstract

Datasets over a spatial domain are common in a number of fields, often with multiple layers (or variables) within data that must be understood together via spatial locality. Thus one area of long-standing interest is increasing the number of variables encoded by properties of the visualization. A number of properties have been demonstrated and/or proven successful with specific tasks or data, but there has been relatively little work comparing the utility of diverse techniques for multi-layer visualization. As part of our efforts to evaluate the applicability of such visualizations, we implemented five techniques which represent a broad range of existing research (Color Blending, Oriented Slivers, Data-Driven Spots, Brush Strokes, and Stick Figures). Then we conducted a user study wherein subjects were presented with composites of three, four, and five layers (variables) using one of these methods and asked to perform a task common to our intended end users (GIS analysts). We found that the Oriented Slivers and Data-Driven Spots performed the best, with Stick Figures yielding the lowest accuracy. Through analyzing our data, we hope to gain insight into which techniques merit further exploration and offer promise for visualization of data sets with ever-increasing size.

Paper Details

Date Published: 24 January 2011
PDF: 12 pages
Proc. SPIE 7868, Visualization and Data Analysis 2011, 78680C (24 January 2011); doi: 10.1117/12.872576
Show Author Affiliations
Mark A. Livingston, U.S. Naval Research Lab. (United States)
Jonathan Decker, U.S. Naval Research Lab. (United States)
Zhuming Ai, U.S. Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 7868:
Visualization and Data Analysis 2011
Pak Chung Wong; Jinah Park; Ming C. Hao; Chaomei Chen; Katy Börner; David L. Kao; Jonathan C. Roberts, Editor(s)

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