A Data- and Task- Oriented Design Framework for Bivariate Communication of Uncertainty

TL;DR

This paper introduces a new design framework for selecting bivariate symbols in maps that communicate uncertainty in spatio-temporal data, aiming to improve decision-making and interpretation.

Contribution

The paper presents a novel, data- and task-oriented framework guiding the choice of bivariate symbols for uncertainty visualization in maps.

Findings

Framework effectively guides symbol selection based on data and task characteristics.

Application to sediment pollution mapping demonstrates practical utility.

Enhanced interpretability of uncertainty in spatial data visualizations.

Abstract

The communication of uncertainty estimates, predictions and insights based on spatio-temporal models is important for decision-making as it impacts the utilisation and interpretation of information. Bivariate mapping is commonly used for communication of estimates and associated uncertainty; however, it is known that different visual qualities resulting from choics of symbols and consequent interaction between the display dimensions can lead to different interpretations and consequently affect resultant decisions. Characteristics of the data to be presented, such as spatial format, statistical level and continuousness, shape the range of available bivairate symbols. The subsequent utility of these bivariate symbols depends on their ability to achieve end-user's goals. In this paper we present a novel design framework, which, through consideration of both input data characteristics and potential operational tasks (as proxy to end-user goals), assists map designers in appropriate selection of bivariate symbols for the coincident presentation of spatio-temporal modelled data and associated uncertainty. The framework is showcased through application to a case study pertaining to sediment pollution in the Great Barrier Reef.