UNCERTAINTY VISUALIZATION AND DECISION MAKING: DOES VISUALIZING UNCERTAIN INFORMATION CHANGE DECISIONS?

S.A. Deitrick

Arizona State University, School of Geographical Sciences, Tempe, AZ

stephanie.deitrick@asu.edu

As the volume and richness of geographic data increases, the need for visualizing these data in an informative and consistent manner becomes more acute. In particular, the accuracy and suitability of information being displayed, such as if the data are from multiple sources or contain some inherent uncertainty, are becoming a greater concern. The accuracy and timeliness of the data are particularly important in situations where visualization is used to support decision-making. The incorporation of uncertainty information into GIS applications is thus a vital component for the critical examination of spatial data used in decision support.

The importance of quantifying and representing uncertainty in geographic data is well recognized in geography. Many techniques have been developed for representing uncertainty, and there have been many participant-based empirical studies evaluating the effectiveness of specific techniques. Speed and accuracy of response are often typical dependent variables in these empirical studies. However, there is little empirical evidence to suggest that uncertainty visualization influences, or results in, different decisions. Through a human-subjects experiment, this research evaluates whether specific uncertainty visualization methods, including texture and value, influence decisions and a users’ confidence in those decisions. This research differs from previous studies in that it focuses on whether decisions change based on the inclusion of uncertainty information.

The results of this study indicate that uncertainty visualization may effect decisions, but that the degree of influence may be governed first and foremost by the decision task and not solely by the specific visualization technique used to communicate uncertainty information. The results of this research will support future research into whether the type of decision task should inform the methods for visualizing uncertainty in decision support applications.