Kristin Potter is an NLR scientist who specializes in data visualization. Her research is focused on methods to improve visualization techniques by adding qualitative information regarding reliability to the data display. This work includes researching statistical measures of uncertainty, error, and confidence levels, and translating the semantic meaning of these measures into visual metaphors. 

Potter has over 15 years of experience in visualization creation, design, and deployment spanning multiple disciplines—including atmospheric sciences, materials modeling, geographical mapping, and the humanities. Prior to joining NLR in 2017, Potter worked as a research-computing consultant at the University of Oregon, providing visualization services, computational training and education, and other support to researchers across campus. She also worked as a research scientist at the University of Utah on projects related to the visualization of uncertainty and error in data. While pursuing her Ph.D., Potter's dissertation work focused on the visual representation of variability within ensemble suites of simulations covering multiple parameter settings and initial conditions. Her master's work developed the use of sketch-based methods for conveying levels of reliability in architectural renderings. 

Potter works in NLR's Insight Center on high-dimensional data visualization techniques and web-based deployment of visualization applications. She is also interested in topics related to decision-making, performance visualization, method evaluation, and application specific techniques. 

Uncertainty visualization 

High-dimensional data analysis

Information visualization