Analyzing task-based user study data to determine colormap efficiency
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Domain scientists need colormaps to visualize their data and are especially useful for identifying areas of interest, like in ocean data to identify eddies or characterize currents. However, traditional Rainbow colormap performs poorly for understanding details, because of the small perceptual range. In order to assist domain scientists in recognizing and identifying important details in their data, different colormaps need to be applied to allow higher perceptual definition. Visual artist Francesca Samsel used her understanding of color theory to create new colormaps to improve perception. While domain scientists find the new colormaps to be useful, we implemented a rigorous and quantitative study to determine whether or not the new colormaps have perceptually more colors. Color count data from one of these studies will be analyzed in depth in order to determine whether or not the new colormaps have more perceivable colors and what affects the number of perceivable colors.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- Contributing Organization:
- Workforce Development for Teachers and Scientists (WDTS), Science Undergraduate Laboratory Internships Program (SULI)
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1210206
- Report Number(s):
- LA-UR--15-25715
- Country of Publication:
- United States
- Language:
- English
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