Color is an integral part of all kinds of data visualization. Though its role in communication and analysis for information visualization has been thoroughly investigated, there is still work to be done to understand its complex role in scientific visualization. While many components of color are quantifiable, color relationships and the complex dynamics produced by different types of data require an artistic approach, one that relies on color theory in order to produce visualizations that are easier to read, parse, communicate with, and analyze. The aim of this ongoing project is to investigate the dimensions of scientists’ needs—especially those who work consistently with large, simulated, and multivariate datasets—and to provide guidance, software, and pre-made color sets and maps to improve visualizations across the board.
Much of this work is housed under a separate domain, SciVisColor.org.
Here you can find a collection of custom, hand-made colormaps, the ColorMoves application, in-depth tutorials and instructions for different types of color projects, and a list of publications.
SciVisColor is a hub for research and resources related to color in scientific visualization. Sciviscolor draws on expertise from the arts, computer science, data science, geoscience, mathematics, and the scientific visualization community to create tools and guides that enhance scientists’ ability to extract knowledge from their data.
ParaView Default Colormap
We built a new default colormap for ParaView, the widely used scientific visualization software.
Below are the colorpoints and the .xml file.
More detail can be found in IEEE Computer Graphics & Applications, Vis Viewpoints, May/June 2024.
As the complexity of scientific data and the needs to communicate the science have grown, the requirements for visualization design and use have become more sophisticated. We increasingly need
more effective ways of communicating the science across multiple audiences, including non-experts in the field. The challenges of enriching the representation have moved from the more naive ideas of making it ”aesthetically attractive” to more profound constructs of visual language: how to enhance nuances in the data, and how to support more expressive visualizations that elicit different cognitive
and communicative affect to tell the science story. In this paper, we describe how artistic color techniques drawn from paintings can be operationally applied to produce more evocative and informative
scientific visualization.
Color, drawn from nature, describing nature
Parsing the detail and complexity of the world draws on evolved traits of our visual systems: top-down and bottom-up attentional processing, strategic visual grouping, exploration, value assignment, and hierarchical determinants. As many of these tasks rely on color, we’re able to perceive minute differences in natural hues, especially green.
Pine needles, prairie grasses, mesquite bushes, cacti, moss, juniper trees: each reflect distinct shades of green which vary drastically, even within the same plant. Primary hues are much less common in nature than secondary or tertiary hues, and are employed sparingly by flora and fauna alike to contrast with a largely analogous backdrop and to signal danger, spread seeds, or attract a mate or pollinator.
When disembodied and decontextualized from their sources, do these myriad greens continue to index their botanical origins? Devoid of form, do they possess the same agency, retrieve the same memories, produce the same sense of Place?
Decoding a scientific visualization, or any other kind of information-dense visual scene, draws on the same color-based evolved capabilities to accomplish similar analysis and decision-making tasks. Color contributes to the experience of the image; another datapoint that provides information and subtext for the “text” of the visualization, producing a set of relationships specific to that image.
By appropriating the earth’s palette, we might strategically leverage our innate sense-making operations to compose richer, more effective, and less cacophonous visualizations—a fruitful avenue which remains untapped thus far in both scientific and geographic communities.
The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps
A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to describe different concepts or the same rule is described by varying nomenclature. These ambiguities stand in the way of collaborative work, the design of experiments to assess the characteristics of colormaps, and automated colormap generation. In this paper, we review current and historical guidelines for colormap design. We propose a specified taxonomy and provide unambiguous mathematical definitions for the most common design rules.
Colormapping resources and strategies for organized intuitive environmental visualization
Visualizations benefit from the use of intuitive organized color application, enabling a clearer understanding and communication. In this paper, we apply the concept of semantic color association to the generation of thematic colormaps for the environmental sciences in combination with principals of artistic color theory to expand feature resolution and create visual hierarchies within a visualization. In particular, we provide sets of color scales, colormaps and color organization guidance for semantically aligned water, atmosphere, land, and vegetation visualization. Strategies for directing attention via saturation levels and saturation sets of colormaps enable deployment of these techniques. All are publicly available online and accompanied by tools and strategy guidance.
ColorMoves: Real-time Interactive Colormap Construction for Scientific Visualization
This article presents ColorMoves, an interactive tool that promotes exploration of scientific data through artist-driven color methods in a unique and transformative way. We discuss the power of contrast in scientific visualization, the design of the ColorMoves tool, and the tools application in several science domains. READ MORE
Environmental Visualization: Moving Beyond the Rainbows
Pseudo-coloring is a well-established, fundamental tool for visualizing scientific data. As the size and density of data grows, increasingly more discriminatory power is required to extract optimum feature resolution. The environmental community, in particular, relies heavily on this technology to dissect and interpret a huge variety of visual data. These scientists often turn to traditional rainbow colormaps, despite their well-documented deficiencies in rendering dense detail. A popular default, the desaturated rainbow’s non-monotonically varying luminance range misrepresents data. Despite increasing overall feature resolution, this variance creates hue simultaneity and vibration, introducing false artifacts, hindering exploration of swaths of data and impeding analysis [13, 21, 26]. Drawing on artistic color theory, we hypothesized the desaturated rainbow could be improved by increasing luminance ranges, decreasing saturation, and employing hue-cycling to boost discriminatory power. These adjusted maps exhibit algorithmically corroborated higher feature resolve, a primary objective of all scientists interviewed, without distorting data in discordant false coloring. Our studies indicate that our maps are preferred by these domain scientists, thereby providing a potential alternative for effective, human-centric colormapping. READ MORE
Visualizing Science: How Color Determines What We See
Color strongly influences the way we perceive information, especially when that information is dense, multidimensional, and nuanced—as is often the case in scientific data sets. Choosing colors to visually represent data can thus be hugely important in interpreting and presenting scientific results accurately and effectively. READ MORE
Associated Publications
- Affective Palettes for Scientific Visualization: Grounding Environmental Data in the Natural World
- Colormapping resources and strategies for organized intuitive environmental visualization
- The Making of Continuous Colormaps
- ColorMoves: An Interactive Tool that Visualizes Scientific Data in a Colorful, Artistic, and Transformative Way
- ColorMoves: Real-time Interactive Colormap Construction for Scientific Visualization
- Art, Affect and Color: Creating Engaging Expressive Scientific Visualization
- Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations
- Employing Color Theory to Visualize Volume-rendered Multivariate Ensembles of Asteroid Impact Simulations
- Enabling Crosscutting Visualization for Geoscience
- Toward an Improved Colormapping Workflow: New Task-Driven Tools and Techniques for High-Level Colormapping Applications in Scientific Visualization
- A Symphony of Color and Shape: Visualizing the complexity of science without the cacophony
- Visualizing Science: How Color Determines What We See
- Using Close Reading as a Method for Evaluating Visualizations
- Environmental Visualization: Moving Beyond the Rainbows
- The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps
- ColorMoves: Optimizing Color’s Potential for Exploration and Communication of Data