Visualization Symposium, IEEE Pacific (2011)

Hong Kong, China

Mar. 1, 2011 to Mar. 4, 2011

ISBN: 978-1-61284-935-5

pp: 171-178

ABSTRACT

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 rates. We present a line kernel for representing streaming data, we discuss how the concept of KDE can be adapted to enable a continuous representation of the distribution of a dependent variable of a 2D domain. We propose to automatically adapt the kernel bandwith of KDE to the viewport settings, in an interactive visualization environment that allows zooming and panning. We also present a GPU-based realization of KDE that leads to interactive frame rates, even for comparably large datasets. Finally, we demonstrate the usefulness of our approach in the context of three application scenarios - one studying streaming ship traffic data, another one from the oil & gas domain, where process data from the operation of an oil rig is streaming in to an on-shore operational center, and a third one studying commercial air traffic in the US spanning 1987 to 2008.

INDEX TERMS

interactive systems, cartography, data visualisation, GPU-based realization, interactive visualization, streaming data, kernel density estimation, scatterplot-like visualization, zooming, panning, Kernel, Data visualization, Bandwidth, Estimation, Histograms, Marine vehicles, Pixel, G.3 [Mathematics of Computing]: Probability and Statistics—Time series analysis, I.3.3 [Computing Methodologies]: Computer Graphics—Picture/Image Generation

CITATION

"Interactive visualization of streaming data with Kernel Density Estimation,"

*2011 IEEE Pacific Visualization Symposium (PacificVis)(PACIFICVIS)*, Hong Kong, 2011, pp. 171-178.

doi:10.1109/PACIFICVIS.2011.5742387