Effectively designed data visualizations allow viewers to use their powerful visual systems to
understand patterns in data across science, education, health, and public policy. But …

This paper provides an overview of uncertainty visualization in general, along with specific
examples of applications in bioinformatics. Starting from a processing and interaction …

The prevalence of inadequate SARS-COV-2 (COVID-19) responses may indicate a lack of
trust in forecasts and risk communication. However, no work has empirically tested how …

One of the most familiar data visualizations, the length or height of the rectangular bars in
bar and column charts depict the value of your data. The rectangles can be arranged along …

Automated vehicles are expected to improve safety, mobility, and inclusion. User
acceptance is required for the successful introduction of this technology. One essential …

As uncertainty visualizations for general audiences become increasingly common,
designers must understand the full impact of uncertainty communication techniques on …

Community science (also often referred to as citizen science) provides a unique opportunity
to address questions beyond the scope of other research methods whilst simultaneously …

Today's AI systems for medical decision support often succeed on benchmark datasets in
research papers but fail in real-world deployment. This work focuses on the decision making …

Recent developments in critical information visualization have brought the field's attention to
political, feminist, ethical, and rhetorical aspects of data visualization. However, less work …

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and
the government standards arising from them both call for trustworthy AI. In response, we …