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Enhancing Uncertainty Communication in Time Series Predictions: Insights and Recommendations

arXiv 2408.12365 ↗First posted 22 Aug 2024cs.HC cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 29 references that are in the map. First posted on arXiv 22 Aug 2024.

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References · 3

  1. 2019Why Authors Don't Visualize Uncertaintycited by 4
  2. 2022Using Processing Fluency as a Metric of Trust in Scatterplot Visualizationscited by 1
  3. 2023ESID: Exploring the Design and Development of a Visual Analytics Tool for Epidemiological Emergenciescited by 1

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