Enhancing Uncertainty Communication in Time Series Predictions: Insights and Recommendations

TL;DR

This paper investigates how different visualization techniques and user characteristics influence the perception and communication of uncertainty in time series forecasts, aiming to improve dashboard design and decision-making.

Contribution

It provides new insights into how uncertainty is perceived in various line chart variants and how user traits affect uncertainty estimation, informing better visualization practices.

Findings

Different chart variants impact uncertainty estimation accuracy.

User characteristics significantly influence perception of uncertainty.

Recommendations for designing clearer uncertainty visualizations.

Abstract

As the world increasingly relies on mathematical models for forecasts in different areas, effective communication of uncertainty in time series predictions is important for informed decision making. This study explores how users estimate probabilistic uncertainty in time series predictions under different variants of line charts depicting uncertainty. It examines the role of individual characteristics and the influence of user-reported metrics on uncertainty estimations. By addressing these aspects, this paper aims to enhance the understanding of uncertainty visualization and for improving communication in time series forecast visualizations and the design of prediction data dashboards.As the world increasingly relies on mathematical models for forecasts in different areas, effective communication of uncertainty in time series predictions is important for informed decision making. This study explores how users estimate probabilistic uncertainty in time series predictions under different variants of line charts depicting uncertainty. It examines the role of individual characteristics and the influence of user-reported metrics on uncertainty estimations. By addressing these aspects, this paper aims to enhance the understanding of uncertainty visualization and for improving communication in time series forecast visualizations and the design of prediction data dashboards.