Color is one of the most powerful tools in data visualization, helping to reveal patterns, emphasize structure, and guide interpretation. Yet, the effectiveness of a visualization is often compromised by the choice of color map—a decision frequently made by default rather than design. Traditional color maps like "jet" or "rainbow" remain popular, but they introduce serious drawbacks: perceptual non-uniformity, misleading gradients, and poor accessibility for individuals with color vision deficiencies (CVD). These issues can distort patterns, introduce visual artifacts, and lead to incorrect conclusions.

This presentation explores the advantages of scientifically designed, perceptually uniform color maps. Rooted in principles of human vision, these color maps maintain consistent luminance and hue transitions, reducing distortion and enhancing the readability of complex data. Crucially, they also support better accessibility by accommodating the most common forms of CVD.

We will begin by unpacking key concepts in color perception and how they affect the interpretation of visual data. Using clear visual comparisons, we’ll contrast flawed traditional color maps with perceptually optimized alternatives, revealing how poor color choices can mask or exaggerate patterns. Emphasis will be placed on how subtle changes in gradient or luminance can dramatically alter the meaning conveyed by a visualization.

Real-world case studies will be presented from fields such as:

Medical imaging, where color distinctions can influence diagnostic accuracy;

Fluid dynamics, where fine gradient shifts reveal important flow features.

Through these examples, we’ll highlight how perceptually uniform color maps lead to clearer, more accurate, and more inclusive visualizations.

In addition to the conceptual overview, this talk will provide practical, hands-on guidance. Attendees will learn how to identify effective color maps, avoid common pitfalls, and incorporate scientifically derived palettes—such as Batlow, Acton, and Navia developed by Fabio Crameri—into their workflows. These color maps are specifically designed to be perceptually uniform, color vision deficiency–friendly, and optimized for scientific communication.

By the end of the session, participants will understand the impact of color choices on data interpretation and walk away with actionable strategies to improve the clarity, accuracy, and accessibility of their own visualizations.

This presentation is ideal for scientists, engineers, data analysts, and visualization designers seeking to communicate their data more effectively—no background in color theory required