Visualization plays a crucial role in molecular and structural biology. It has been successfully
applied to a variety of tasks, including structural analysis and interactive drug design. While …

As more people rely on visualization to inform their personal and collective decisions,
researchers have focused on a broader range of audiences, including “novices.” But …

Causal inference is a statistical paradigm for quantifying causal effects using observational
data. It is a complex process, requiring multiple steps, iterations, and collaborations with …

Understanding how helpful a visualization is from experimental results is difficult because
the observed performance is confounded with aspects of the study design, such as how …

Coronavirus pandemic was declared by the World Health Organization on March 11, 2020.
Misinformation and social inequality have hindered nations from preparing for …

Visualization for machine learning (VIS4ML) research aims to help experts apply their prior
knowledge to develop, understand, and improve the performance of machine learning …

Designing a visualization is often a process of iterative refinement where the designer
improves a chart over time by adding features, improving encodings, and fixing mistakes …

In contrast to objectively measurable aspects (such as accuracy, reading speed, or
memorability), the subjective experience of visualizations has only recently gained …

Microservice-based systems are exposed to transient behavior caused, for example, by
(frequent) deployments, failures, or self-adaption. The potential complexity of transient …

Software faults are costly to find and remove from programs. It is better to avoid inserting the
faults in the first place. The authors identify requirements‐related faults that can arise during …