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Interactive visualization of streaming data with Kernel Density Estimation

Ove Daae Lampe, Helwig Hauser
University of Bergen, Bergen, Norway
IEEE Pacific Visualization Symposium (PacificVis), 2011

@inproceedings{lampe2011interactive,

   title={Interactive visualization of streaming data with Kernel Density Estimation},

   author={Lampe, D. and Hauser, H.},

   booktitle={Pacific Visualization Symposium (PacificVis), 2011 IEEE},

   pages={171–178},

   organization={IEEE},

   year={2011}

}

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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.
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