Using Sound to Represent Uncertainty in Future Climate Projections for the United Kingdom

Abstract

This paper compares different visual and sonic methods of representing uncertainty in spatial data. When handling large volumes of spatial data, users can be limited in the amount that can be displayed at once due to visual saturation (when no more data can be shown visually without obscuring existing data). Using sound in combination with visual methods may help to represent uncertainty in spatial data and this example uses the UK Climate Predictions 2009 (UKCP09) dataset; where uncertainty has been included for the first time. Participants took part in the evaluation via a web-based interface which used the Google Maps API to show the spatial data and capture user inputs. Using sound and vision together to show the same variable may be useful to colour blind users. Previous awareness of the data set appears to have a significant impact (p < 0.001) on participants ability to utilise the sonification. Using sound to reinforce data shown visually results in increased scores (p = 0.005) and using sound to show some data instead of vision showed a significant increase in speed without reducing effectiveness (p = 0.033) with repeated use of the sonification.