Visualization and visual analysis play important roles in exploring, analyzing, and
presenting scientific data. In many disciplines, data and model scenarios are becoming …

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 …

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 …

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

This paper presents the state of the art in the area of topology‐based visualization. It
describes the process and results of an extensive annotation for generating a definition and …

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 …

We present a method to interactively explore multiple attributes in trajectory data using
density maps, ie, images that show an aggregate overview of massive amounts of data. So …

Graph visualization is an important field in information visualization that is centered on the
graphical display of graph-structured data. Yet real world data is rarely just graph-structured …

In this paper we present World Lines as a novel interactive visualization that provides
complete control over multiple heterogeneous simulation runs. In many application areas …