Ian T. Ruginski

Non-expert interpretations of hurricane forecast uncertainty visualizations

Uncertainty represented in visualizations is often ignored or misunderstood by the non-expert user. The National Hurricane Center displays hurricane forecasts using a track forecast cone, depicting the expected track of the storm and the uncertainty in the forecast. Our goal was to test whether different graphical displays of a hurricane forecast containing uncertainty would influence a decision about storm characteristics. Participants viewed one of five different visualization types. Three varied the currently used forecast cone, one presented a track with no uncertainty, and one presented an ensemble of multiple possible hurricane tracks. Results show that individuals make different decisions using uncertainty visualizations with different visual properties, demonstrating that basic visual properties must be considered in visualization design and communication.

Uncertainty Visualization by Representative Sampling from Prediction Ensembles

Data ensembles are often used to infer statistics to be used for a summary display of an uncertain prediction. In a spatial context, these summary displays have the drawback that when uncertainty is encoded via a spatial spread, display glyph area increases in size with prediction uncertainty. This increase can be easily confounded with an increase in the size, strength or other attribute of the phenomenon being presented. We argue that by directly displaying a carefully chosen subset of a prediction ensemble, so that uncertainty is conveyed implicitly, such misinterpretations can be avoided. Since such a display does not require uncertainty annotation, an information channel remains available for encoding additional information about the prediction. We demonstrate these points in the context of hurricane prediction visualizations, showing how we avoid occlusion of selected ensemble elements while preserving the spatial statistics of the original ensemble, and how an explicit encoding of uncertainty can also be constructed from such a selection. We conclude with the results of a cognitive experiment demonstrating that the approach can be used to construct storm prediction displays that significantly reduce the confounding of uncertainty with storm size, and thus improve viewers’ ability to estimate potential for storm damage.

The influence of different graphical displays on nonexpert decision making under uncertainty.

Understanding how people interpret and use visually presented uncertainty data is an important yet seldom studied aspect of data visualization applications. Current approaches in visualization often display uncertainty as an additional data attribute without a well-defined context. Our goal was to test whether different graphical displays (glyphs) would influence a decision about which of 2 weather forecasts was a more accurate predictor of an uncertain temperature forecast value. We used a statistical inference task based on fictional univariate normal distributions, each characterized by a mean and standard deviation. Participants viewed 1 of 5 different glyph types representing 2 weather forecast distributions. Three of these used variations in spatial encoding to communicate the distributions and the other 2 used nonspatial encoding (brightness or color). Four distribution pairs were created with different relative standard deviations (uncertainty of the forecasts). We found that there was a difference in how decisions were made with spatial versus nonspatial glyphs, but no difference among the spatial glyphs themselves. Furthermore, the effect of different glyph types changed as a function of the variability of the distributions. The results are discussed in the context of how visualizations might improve decision making under uncertainty.

Effects of ensemble and summary displays on interpretations of geospatial uncertainty data

Ensemble and summary displays are two widely used methods to represent visual-spatial uncertainty; however, there is disagreement about which is the most effective technique to communicate uncertainty to the general public. Visualization scientists create ensemble displays by plotting multiple data points on the same Cartesian coordinate plane. Despite their use in scientific practice, it is more common in public presentations to use visualizations of summary displays, which scientists create by plotting statistical parameters of the ensemble members. While prior work has demonstrated that viewers make different decisions when viewing summary and ensemble displays, it is unclear what components of the displays lead to diverging judgments. This study aims to compare the salience of visual features – or visual elements that attract bottom-up attention – as one possible source of diverging judgments made with ensemble and summary displays in the context of hurricane track forecasts. We report that salient visual features of both ensemble and summary displays influence participant judgment. Specifically, we find that salient features of summary displays of geospatial uncertainty can be misunderstood as displaying size information. Further, salient features of ensemble displays evoke judgments that are indicative of accurate interpretations of the underlying probability distribution of the ensemble data. However, when participants use ensemble displays to make point-based judgments, they may overweight individual ensemble members in their decision-making process. We propose that ensemble displays are a promising alternative to summary displays in a geospatial context but that decisions about visualization methods should be informed by the viewer’s task.

Investigating Insight Generation and Decision Making with Visualizations in Real and Virtual Environments

Visualizing data has been touted as a method to reduce cognitive workload by externalizing cognitive processes and utilizing the human perceptual systems ability to recognize patterns [1-4]. The current study investigated whether displaying sociocultural data in an immersive 3D virtual environment improved insight generation and decision making over traditional 2D visualizations. Participants were given 10 minutes to interact with visualizations representing sociocultural information and decide where a possible future threat in a fictional city may occur using either a 2D tabletop map in the real world or the same map represented in 3D in an immersive virtual environment. Visualizations included information either highly correlated with previous incidents (i.e., government building locations and bus routes) and information not highly correlated (i.e., religious centers, income for areas, park locations, and flood zones). Success required identifying which variables were highly correlated with previous incidents, and thus predicted where a future threat may occur. Initial results indicate that in the 3D virtual environment, successful participants gave their final decision about 90 seconds faster than unsuccessful participants. Throughout the simulation, previous incident and government building location visualizations were highly utilized (for both, 85% of total duration), however, successful participants used the bus routes longer (12%) compared to unsuccessful participants. Further, the current trend suggests that successful participants avoided using irrelevant visualization information compared to unsuccessful participants. Ongoing work will compare these results to the 2D table-top display.

Anxiety Influences the Perceptual-Motor Calibration of Visually Guided Braking to Avoid Collisions

ABSTRACT We investigated whether anxiety influences perceptual-motor calibration in a braking to avoid a collision task. Participants performed either a discrete braking task (Experiment 1) or a continuous braking task (Experiment 2), with the goal of stopping before colliding with a stop sign. Half of participants performed the braking task after an anxiety induction. We investigated whether anxiety reduced the frequency of crashing and if it influenced the calibration of perception (visual information) and action (brake pressure) dynamically between-trials in Experiment 1 and within-trials in Experiment 2. In the discrete braking task, anxious participants crashed less often and made larger corrective adjustments trial-to-trial after crashing, suggesting that the influence of anxiety on behavior did not occur uniformly, but rather dynamically with anxiety amplifying the reaction to previous crashes. However, when performing continuous braking, anxious participants crashed more often, and their within-trial adjustments of deceleration were less related to visual information compared to controls. Taken together, these findings suggest that the timescale and nature of the task mediates the influence of anxiety on the performance of goal-directed actions.