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 …

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 …

This state of the art report focuses on glyph-based visualization, a common form of visual
design where a data set is depicted by a collection of visual objects referred to as glyphs. Its …

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 new method to visualize from an ensemble of flow fields the statistical
properties of streamlines passing through a selected location. We use principal component …

Visualization is a valuable approach to the exploration and communication of large data
sets. In different domains these data sets may contain an unavoidable amount of uncertainty …

We report on results of a series of user studies on the perception of four visual variables that
are commonly used in the literature to depict uncertainty. To the best of our knowledge, we …

One of the greatest challenges for today's visualization and analysis communities is the
massive amounts of data generated from state of the art simulations. Traditionally, the …

We present a novel approach for visualizing the positional and geometrical variability of
isosurfaces in uncertain 3D scalar fields. Our approach extends recent work by Pöthkow and …

Artificial intelligence (AI) is changing many industries as intelligent systems assist humans
with algorithmic decision making, machine learning, computer vision, natural language …