Likert scales are often used in visualization evaluations to produce quantitative estimates of
subjective attributes, such as ease of use or aesthetic appeal. However, the methods used to …

With data comes uncertainty, which is a widespread and frequent phenomenon in data
science and analysis. The amount of information available to us is growing exponentially …

Algorithmic transparency entails exposing system properties to various stakeholders for
purposes that include understanding, improving, and contesting predictions. Until now, most …

Controversial understandings of the coronavirus pandemic have turned data visualizations
into a battleground. Defying public health officials, coronavirus skeptics on US social media …

Clear presentation of uncertainty is an exception rather than rule in media articles, data-
driven reports, and consumer applications, despite proposed techniques for communicating …

There is much excitement about the opportunity to harness the power of large language
models (LLMs) when building problem-solving assistants. However, the standard …

Visualizations have a potentially enormous influence on how data are used to make
decisions across all areas of human endeavor. However, it is not clear how this power …

While uncertainty is present in most data analysis pipelines, reasoning with uncertainty is
challenging for novices and experts alike. Fortunately, researchers are making significant …

It has been widely suggested that a key goal of visualization systems is to assist decision
making, but is this true? We conduct a critical investigation on whether the activity of …

Organizations often collect private data and release aggregate statistics for the public's
benefit. If no steps toward preserving privacy are taken, adversaries may use released …