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 work presents a survey of the current state of the art of visualization techniques for
parallel coordinates. It covers geometric models for constructing parallel coordinates and …

Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

The goal of visualization is to effectively and accurately communicate data. Visualization
research has often overlooked the errors and uncertainty which accompany the scientific …

Most visualization techniques have been designed on the assumption that the data to be
represented are free from uncertainty. Yet this is rarely the case. Recently the visualization …

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

Quantifying uncertainty is an increasingly important topic across many domains. The
uncertainties present in data come with many diverse representations having originated …

We present a novel dynamic graph visualization technique based on node-link diagrams.
The graphs are drawn side-byside from left to right as a sequence of narrow stripes that are …

In this paper, we discuss the extension and integration of the statistical concept of Kernel
Density Estimation (KDE) in a scatterplot-like visualization for dynamic data at interactive …

In this paper we revisit the computation and visualization of equivalents to isocontours in
uncertain scalar fields. We model uncertainty by discrete random fields and, in contrast to …