Two-Tone Pseudo Coloringfor Multiple Variables

OverviewGoal: Visualization of multivariate data

Approach: Combine advantages of● Two-Tone Pseudo Coloring (TTPC)● TableLens● Self-Organizing Maps (SOM)

Challenges:● TTPC supports only 1-D data● TTPC's efficiency decreases for high-frequency data● Improve readability of TTPC

Visual Layout and MappingTabular layout:

● Relies on the well-known TableLens approach● Larger number of data rows can be represented

Color Coding:● Makes use of TTPC to color-code each table cell● Allows for more variables to be visualized within the TableLensSOM Sorting

● Generate SOM with number of neurons and training phases estimated based on number of variables and data rows● Apply SOM to sort the data with respect to all or user-selected variables

● High frequencies in visual representation are reduced● Clusters may be identified

● Side effect: hierarchical data structure can be used to drive interface for information drill-down

TableLens, Rao & Card, 1994 Two-Tone Pseudo Coloring, Saito et al., 2005

Improve Readability● Color scale has major impact on efficiency of TTPC● Key to comprehensibility: segmentation of color scale● Simple heuristics help to generate easier interpretable color scales

Mathias John, Christian Tominski, & Heidrun SchumannUniversity of Rostock, Germany

Basic color segment computation Heuristics applied

Data with high frequencies

SOM Sorting