Colormapping Strategies for Large Multivariate Data in Scientific Applications

Series: HPC Best Practices Webinars

In order for scientific visualizations to effectively convey insights of computationally-driven research, as well as to better engage the public in science, visualizations must effectively and affectively facilitate the exploration of information. The presenter and her team employ a transdisciplinary approach, that includes insights from artistic color theory, perceptual science, the visualization community, and domain scientists, to move beyond basic default colormaps. While color has always been utilized and studied as a component of scientific data visualization, it has been demonstrated that its full potential for discovery and communication of scientific data remains untapped.

The webinar will discuss how effective color use can reveal structures, relationships, and hierarchies between variables within a visualization, as well as practical strategies and workflows for tailor color application to the goals of the visualization. The presenter’s work is documented and freely available for use at, a hub for research and resources related to color in scientific visualization. SciVisColor provides tools and strategies that allow scientists to use color as a tool to better understand and communicate their data. Users can explore and download colormaps, color sets, and ColorMoves an interactive interface for using color in scientific visualization above.

The webinar will introduce concepts that can help developers make design decisions when writing simulation codes, to make better use of scientific visualization tools and visualize results more effectively.


Presenter Bio

Francesca Samsel, trained as an artist, is a Research Scientist at the Texas Advanced Computing Center, University of Texas at Austin focusing on multidisciplinary collaborations with visualization teams and domain scientists Her research investigates applying artistic approaches and expertise to real-world visualization challenges. A regular collaborator with the Data Science at Scale and Climate, Ocean Sea Ice, Modeling teams at Los Alamos National Laboratory, she also works closely with the Interactive Visualization Lab at the University of Minnesota, focusing strategies and tools to assist scientists in extracting a greater depth of knowledge from their data and communicating more effectively to their peers and affectively to the public. Visualization collaborations have been recognized by multiple Best Scientific Visualization and Data Analytics Awards at Supercomputing and over 40 publications. As Co-Editor of Art on Graphics, IEEE Computer Graphics and Applications she promotes work that demonstrates the value melding of art, science and technology. Funded by the NSF and DOE, she is a regular presenter at conferences across disciplines including AGU Fall Meeting, IEEE Vis, SIG CHI, Euro Graphics and the College Art Association. She holds a BFA from the California College of Arts and an MFA from the University of Washington.