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 …

Knowledge of human perception has long been incorporated into visualizations to enhance
their quality and effectiveness. The last decade, in particular, has shown an increase in …

We describe a method for assessing the visualization literacy (VL) of a user. Assessing how
well people understand visualizations has great value for research (eg, to avoid confounds) …

When making an inference or comparison with uncertain, noisy, or incomplete data,
measurement error and confidence intervals can be as important for judgment as the actual …

Color is frequently used to encode values in visualizations. For color encodings to be
effective, the map** between colors and values must preserve important differences in the …

There is a need for solutions which assist users to understand long time-series data by
observing its changes over time, finding repeated patterns, detecting outliers, and effectively …

A common challenge faced by many domain experts working with time series data is how to
identify and compare similar patterns. This operation is fundamental in high-level tasks, such …

Many real-world datasets are incomplete due to factors such as data collection failures or
misalignments between fused datasets. Visualizations of incomplete datasets should allow …

Many visualization tasks require the viewer to make judgments about aggregate properties
of data. Recent work has shown that viewers can perform such tasks effectively, for example …

The visual system can make highly efficient aggregate judgements about a set of objects,
with speed roughly independent of the number of objects considered. While there is a rich …