Uncertainty Cognition
We live in an uncertain world. From weather events to financial markets, every day we are confronted with uncertainty. However, even experts have difficulty reasoning with uncertainty. Visualizations allow our visual systems to identify patterns in data that would otherwise go unnoticed. Visualizations can also help us focus on relevant data when making probabilistic judgments. Unfortunately, visualizing the uncertainty in complex phenomena such as hurricane forecasts can introduce new problems, as evidenced by the confusion associated with Hurricane Dorian's path. We study state-of-the-art uncertainty visualizations, along with the cognitive processes that lead to misunderstandings of forecast data.
- Topics
- uncertainty visualization, measuring cognitive effort, theoretical models of decision making with visualizations, mental models of data, rainbow color maps, effects of binning continuous data, hurricane forecasting, hazard maps, metaphors
Featured Media
Publications
2022
Best Paper Award at VIS 2022. Multiple Forecast Visualizations (MFVs): Trade-offs in Trust and Performance in Multiple COVID-19 Forecast Visualizations
Padilla, L., Fygenson, R., Castro, S., & Bertini, E. (2022). To be presented at VIS 2020.
Impact of COVID-19 forecast visualizations on pandemic risk perceptions.
Citation: Padilla, L., Hosseinpour, H., Fygenson, R., Howell, J., Chunara, R., & Bertini, E. (2022). Impact of COVID-19 forecast visualizations on pandemic risk perceptions. Scientific reports, 12(1), 1-14.
2021
Examining Effort in 1D Uncertainty Communication Using Individual Differences in Working Memory and NASA-TLX.
Citation: Spencer C Castro, Helia Hosseinpour, P Samuel Quinan, Lace Padilla (2021 in press). IEEE VIS 2021.
Multiple Hazard Uncertainty Visualization Challenges and Paths Forward.
Citation: Padilla, L. M., Dryhurst, S., Hosseinpour, H., & Kruczkiewicz, A. (2021). Multiple Hazard Uncertainty Visualization Challenges and Paths Forward. Frontiers in Psychology, 12, 1993.
A review of uncertainty visualization errors: Working memory as an explanatory theory.
Citation: Padilla, L., Castro, S. C., & Hosseinpour, H. (2021). A review of uncertainty visualization errors: Working memory as an explanatory theory. In K. D. Federmeier (Ed.), The psychology of learning and motivation (Vol. 74, pp. 275–315). Psychology of Learning and Motivation. Academic Press. doi:https://doi.org/10.1016/bs.plm.2021.03.001
Uncertainty Visualization (book chapter)
Citation: Padilla, Kay, & Hullman (in press). Uncertainty Visualization. To appear in, Handbook of Computational Statistics and Data Science.
Mapping the Landscape of COVID-19 Crisis Visualizations
Citation: Zhang, Y., Sun, Y., Padilla, L., Barua, S., Bertini, E., & Parker, A. G. (2021). Mapping the Landscape of COVID-19 Crisis Visualizations. To apprear in CHI 2021.
Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations
Citation: Padilla, L. M., Powell, M., Kay, M., & Hullman, J. (2021). Uncertain about uncertainty: How qualitative expressions of forecaster confidence impact decision-making with uncertainty visualizations. Frontiers in Psychology, 11.
2020
Using Behavioral Insights to Improve Disaster Preparedness, Early Warning and Response Mechanisms in Haiti (English)
Citation: Llopis Abella, Jimena; Perge, Emilie Bernadette; Afif, Zeina; Soto Orozco, Claudia Ruth; Padilla, Lace M; Hsu, Jessica. 2020.Using Behavioral Insights to Improve Disaster Preparedness, Early Warning and Response Mechanisms in Haiti (English). eMBeD brief. Washington, D.C. : World Bank Group.
The Powerful Influence of Marks: Visual and Knowledge-Driven Processing in Hurricane Track Displays
Citation:Padilla, L. M., Creem-Regehr, S. H., & Thompson, W. (2020). The powerful influence of marks: Visual and knowledge-driven processing in hurricane track displays. Journal of Experimental Psychology: Applied, 26(1), 1.
2018
Visualizing uncertain tropical cyclone predictions using representative samples from ensembles of forecast tracks
Citation: Liu, L., Padilla, L., Creem-Regehr, S., & House, D. (2018). Visualizing uncertain tropical cyclone predictions using representative samples from ensembles of forecast tracks. IEEE transactions on visualization and computer graphics.
*Downloads: Supplementary Materials, Visualization technique code, and User study analysis R code + data
*Downloads: Supplementary Materials, Visualization technique code, and User study analysis R code + data
2017
Effects of Ensemble and Summary Displays on Interpretations of Geospatial Uncertainty Data
Citation: Padilla, L., Ruginski, I., Creem-Regehr, S. H. (2017). Effects of Ensemble and Summary Displays on Interpretations of Geospatial Uncertainty Data. Cognitive Research: Principles and Implications,2(1), 40. https://doi.org/10.1186/s41235-017-0076-1.
*Downloads: Data
*Downloads: Data
Uncertainty Visualization by Representative Sampling from Prediction Ensembles
Citation: Liu, L., Boone, A. P., Ruginski, I. T., Padilla, L., Hegarty, M., Creem-Regehr, S. H., ... & House, D. H. (2017). Uncertainty Visualization by Representative Sampling from Prediction Ensembles. IEEE transactions on visualization and computer graphics, 23(9), 2165-2178.
2016
Non-expert interpretations of hurricane forecast uncertainty visualizations
Citation: Ruginski, I. T., Boone, A. P., Padilla, L., Liu, L., Heydari, N., Kramer, H. S., ... & Creem-Regehr, S. H. (2016). Non-expert interpretations of hurricane forecast uncertainty visualizations. Spatial Cognition & Computation, 16(2), 154-172.
*Downloads: Data
*Downloads: Data
2015
The influence of different graphical displays on nonexpert decision making under uncertainty
Padilla, L., Hansen, G., Ruginski, I. T., Kramer, H. S., Thompson, W. B., & Creem-Regehr, S. H. (2015). The influence of different graphical displays on nonexpert decision making under uncertainty. Journal of Experimental Psychology: Applied, 21(1), 37.