ABSTRACT
Scatterplots provide a visual representation of bivariate data (or 2D embeddings of multivariate data) that allows for effective analyses of data dependencies, clusters, trends, and outliers. Unfortunately, classical scatterplots suffer from scalability issues, since growing data sizes eventually lead to overplotting and visual clutter on a screen with a fixed resolution, which hinders the data analysis process. We propose an algorithm that compensates for irregular sample distributions by a smooth transformation of the scatterplot's visual domain. Our algorithm evaluates the scatterplot's density distribution to compute a regularization mapping based on integral images of the rasterized density function. The mapping preserves the samples' neighborhood relations. Few regularization iterations suffice to achieve a nearly uniform sample distribution that efficiently uses the available screen space. We further propose approaches to visually convey the transformation that was applied to the scatterplot and compare them in a user study. We present a novel parallel algorithm for fast GPU-based integral-image computation, which allows for integrating our de-cluttering approach into interactive visual data analysis systems.
ABSTRACT
We present an interactive visual analysis tool for analyzing the spread of wildfires and what influences their evolution. Multiple time-varying 3-D scalar and vector fields are investigated and related to each other to identify causes of atypical fire spread. We present a visual analysis approach that allows for a comparative analysis of multiple runs of a simulation ensemble on different levels of detail. Overview visualizations combined with volume renderings and flow visualizations provide an intuitive understanding of the fire spread.
ABSTRACT
The analysis of multirun oceanographic simulation data imposes various challenges ranging from visualizing multifield spatio-temporal data over properly identifying and depicting vortices to visually representing uncertainties. We present an integrated interactive visual analysis tool that enables us to overcome these challenges by employing multiple coordinated views of different facets of the data at different levels of aggregation.
