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Why we use bad color maps and what you can do about it

Human Vision and Electronic Imaging 2016, HVEI 2016

Moreland, Kenneth D.

We know the rainbow color map is terrible, and it is emphatically reviled by the visualization community, yet its use continues to persist. Why do we continue to use a this perceptual encoding with so many known flaws? Instead of focusing on why we should not use rainbow colors, this position statement explores the rational for why we do pick these colors despite their flaws. Often the decision is influenced by a lack of knowledge, but even experts that know better sometimes choose poorly. A larger issue is the expedience that we have inadvertently made the rainbow color map become. Knowing why the rainbow color map is used will help us move away from it. Education is good, but clearly not sufficient. We gain traction by making sensible color alternatives more convenient. It is not feasible to force, a color map on users. Our goal is to supplant the rainbow color map as a common standard, and we w ill find that even those wedded to it will migrate away.

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TYPE Conference Poster YEAR 2016
ScopusOSTI

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Meredith, Jeremy M.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

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TYPE Other Report YEAR 2015
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Results 101–125 of 313
Results 101–125 of 313