Why Shouldn't All Charts Be Scatter Plots? Beyond Precision-Driven Visualizations

TL;DR

This paper challenges the idea that scatter plots are the only effective visualization for data comparison, advocating for diverse chart types to better serve different analytical needs.

Contribution

It refutes the oversimplified view that only scatter plots are effective, encouraging broader perspectives in visualization research and practice.

Findings

Scatter plots are not always the best choice for all data comparisons.

Different visualizations can be more effective depending on the context.

The paper calls for diversified visualization strategies beyond scatter plots.

Abstract

A central concept in information visualization research and practice is the notion of visual variable effectiveness, or the perceptual precision at which values are decoded given visual channels of encoding. Formative work from Cleveland & McGill has shown that position along a common axis is the most effective visual variable for comparing individual values. One natural conclusion is that any chart that is not a dot plot or scatterplot is deficient and should be avoided. In this paper we refute a caricature of this "scatterplots only" argument as a way to call for new perspectives on how information visualization is researched, taught, and evaluated.