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The data and modeling procedures depicted in visualizations can be incomplete, corrupt, or lacking in precision. Unfortunately quantifying, visualizing, and reasoning with uncertainty are classically complicated problems. Accounting for uncertainty, through the data-to-decision pipeline, is necessary to ...

The data and modeling procedures depicted in visualizations can be incomplete, corrupt, or lacking in precision. Unfortunately quantifying, visualizing, and reasoning with uncertainty are classically complicated problems. Accounting for uncertainty, through the data-to-decision pipeline, is necessary to reason about the data effectively.

Ongoing research from numerous fields has attempted to develop methods to help people make more effective decisions under uncertainty. Visualizations offer a unique opportunity to capitalize on the visual and perceptual systems to guide individuals through challenging
uncertain judgments. However, visualizations can also introduce additional complications as the appropriate visualization technique for each type of uncertainty, data, and context is far from resolved. Different users (e.g., experts, policymakers, the general public, or students) may vary in the type of uncertainty that best supports their understanding of the data. Different visualizations of uncertainty might be more appropriate for time-sensitive decisions, and others may evoke critical consideration of the data.

There are many open research questions, and this research topic invites high-quality papers that report recent and emerging research developments in the field of uncertainty visualization. Potential authors are invited to submit original contributions of experimental, theoretical, or computational research on uncertainty visualization.

Topics include, but are not limited to:
- Uncertainty visualization evaluations
- Uncertainty visualization techniques
- Biases in uncertainty visualization
- Domain applications of uncertainty visualization
- Theoretical models of uncertainty visualization
- Cognitive processing of uncertainty visualization
- Influence of data types on the uncertainty visualization technique
- Uncertainty quantification for visualizations
- Holistic decision-making with uncertainty visualizations
- Different users of uncertainty visualizations (experts, policymakers, risk managers, the
general public, students)
- The influence of uncertainty visualizations on individual differences
- Learning and memory using uncertainty visualizations
- Training in the use of uncertainty visualization
- Uncertainty visualization in the media or education in contexts
- Reviews, state-of-the-art summaries, and cross-domain language recommendations

Keywords: uncertainty visualization, decision making


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