Lost in Magnitudes: Exploring Visualization Designs for Large Value Ranges

TL;DR

This paper investigates visualization designs for large value ranges called OMVs, proposing a systematic design space, deriving guidelines, and empirically testing two effective visualizations that improve interpretation confidence.

Contribution

It introduces a comprehensive design space for OMV visualizations, derives guidelines, and empirically validates two designs that outperform existing methods.

Findings

The proposed visualizations facilitate better quantitative comparisons.

They increase user confidence in interpreting large value ranges.

Guidelines help in designing effective OMV visualizations.

Abstract

We explore the design of visualizations for values spanning multiple orders of magnitude; we call them Orders of Magnitude Values (OMVs). Visualization researchers have shown that separating OMVs into two components, the mantissa and the exponent, and encoding them separately overcomes limitations of linear and logarithmic scales. However, only a small number of such visualizations have been tested, and the design guidelines for visualizing the mantissa and exponent separately remain under-explored. To initiate this exploration, better understand the factors influencing the effectiveness of these visualizations, and create guidelines, we adopt a multi-stage workflow. We introduce a design space for visualizing mantissa and exponent, systematically generating and qualitatively evaluating all possible visualizations within it. From this evaluation, we derive guidelines. We select two visualizations that align with our guidelines and test them using a crowdsourcing experiment, showing they facilitate quantitative comparisons and increase confidence in interpretation compared to the state-of-the-art.