# Evaluating Ordering Strategies of Star Glyph Axes

## TL;DR

This paper empirically evaluates how different ordering strategies of star glyph axes affect visual clustering tasks, finding that dissimilarity-based layouts outperform similarity-based ones, especially in cluttered scenarios.

## Contribution

It provides the first systematic user study comparing similarity and dissimilarity-based star glyph orderings for clustering tasks.

## Key findings

- Dissimilarity-based layouts improve clustering accuracy.
- Users show higher confidence with dissimilarity-based arrangements.
- Clutter amplifies the benefits of dissimilarity ordering.

## Abstract

Star glyphs are a well-researched visualization technique to represent multi-dimensional data. They are often used in small multiple settings for a visual comparison of many data points. However, their overall visual appearance is strongly influenced by the ordering of dimensions. To this end, two orthogonal categories of layout strategies are proposed in the literature: order dimensions by similarity to get homogeneously shaped glyphs vs. order by dissimilarity to emphasize spikes and salient shapes. While there is evidence that salient shapes support clustering tasks, evaluation, and direct comparison of data-driven ordering strategies has not received much research attention. We contribute an empirical user study to evaluate the efficiency, effectiveness, and user confidence in visual clustering tasks using star glyphs. In comparison to similarity-based ordering, our results indicate that dissimilarity-based star glyph layouts support users better in clustering tasks, especially when clutter is present.