Abstract

Most of our daily activities in a highly mobile digital society require timely spatial decision making. Much of such decision-making is supported by map displays on various devices with different modalities. Spatial information visualized on maps, however, is always subject to a multitude of uncertainties. If space-time decision-makers are not informed about potential uncertainties, misleading, or at worst, life-threatening outcomes might result from map-based decisions. Therefore, data uncertainties should be communicated to decision-makers, especially when they are made with limited time resources and when decision outcomes can have dramatic consequences. Thus, the current study investigates how data uncertainty visualized in maps might influence the process and outcomes of spatial decision making, especially when made under time pressure in risky situations. Although there is very little empirical evidence from prior uncertainty visualization research that considered decision time constraints, we hypothesized that uncertainty visualization would also have an effect on decision-making under time critical and complex decision contexts. Using a map-based helicopter landing scenario in mountainous terrain, we found that neither time pressure or uncertainty affected participants decision-making accuracy. However, uncertainty affected participants' decision strategies, and time pressure affected participants' response times. Specifically, when presented with two equally correct answers, participants avoided uncertainty more often at a cost of landing distance (an equally important decision criteria). We interpret our results as consistent with a loss-aversion heuristic and suggest implications for the study of decision-making with uncertainty visualizations.

Highlights

  • Data visualization is becoming more and more ubiquitous in society as a way of communicating complex phenomena to scientific experts and the general public alike

  • While our study sought to make claims about uncertainty visualization generally, we only studied one type of uncertainty visualization, which was overlaid on slope data binned according to color hue

  • Uncertainty can have many meanings and we only provided brief training with uncertainty to non-experts, which may have limited individuals understanding of uncertainty

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Summary

Introduction

Data visualization is becoming more and more ubiquitous in society as a way of communicating complex phenomena to scientific experts and the general public alike. Along with this increase in availability comes a responsibility for scientists to visualize uncertainty, which includes a consideration of the accuracy of data from a variety of sources, such as measurement error, Decisions With Map Uncertainty Visualizations natural variation, and prediction error (Skeels et al, 2010; MacEachren et al, 2012). Because uncertainty is a multi-faceted concept, there are many different uncertainties, and the visualization of uncertainties is applied in various contexts with different objectives, so there cannot be a single optimal uncertainty visualization technique This calls for evaluation of uncertainty visualization methods in specific contexts. The more uncertainty visualization techniques have developed, the more there has been a call for empirical evaluations and theoretical frameworks to test the effects uncertainty visualizations have on decision-making (Spiegelhalter et al, 2011; Kinkeldey et al, 2015a; Kay et al, 2016; Padilla et al, 2018)

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