The Role of Uncertainty, Awareness, and Trust in Visual Analytics

Dominik Sacha, Hansi Senaratne, Bum Chul Kwon, Geoffrey Ellis, Daniel A. Keim
2016 IEEE Transactions on Visualization and Computer Graphics  
Action Hypothesis Finding K Insight Knowledge Uncertainty Handling and Reduction Awareness Trust Building Fig. 1: Knowledge generation model for visual analytics including uncertainty propagation and human trust building. Uncertainty originates at the data source and propagates through the system components which introduce additional uncertainties. Uncertainty awareness influences human trust building on different knowledge generation levels. Abstract-Visual analytics supports humans in
more » ... ng knowledge from large and often complex datasets. Evidence is collected, collated and cross-linked with our existing knowledge. In the process, a myriad of analytical and visualisation techniques are employed to generate a visual representation of the data. These often introduce their own uncertainties, in addition to the ones inherent in the data, and these propagated and compounded uncertainties can result in impaired decision making. The user's confidence or trust in the results depends on the extent of user's awareness of the underlying uncertainties generated on the system side. This paper unpacks the uncertainties that propagate through visual analytics systems, illustrates how human's perceptual and cognitive biases influence the user's awareness of such uncertainties, and how this affects the user's trust building. The knowledge generation model for visual analytics is used to provide a terminology and framework to discuss the consequences of these aspects in knowledge construction and though examples, machine uncertainty is compared to human trust measures with provenance. Furthermore, guidelines for the design of uncertainty-aware systems are presented that can aid the user in better decision making.
doi:10.1109/tvcg.2015.2467591 pmid:26529704 fatcat:ggxkbbx4b5ftfp2o55ao66nloy