Visual Analytics and Imaging Laboratory (VAI Lab)
Computer Science Department, Stony Brook University, NY

An Interactive Visual Analytics Framework for
Multi-Field Data in a Geo-Spatial Context

Abstract: Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multifield visualization problem, where the geo-space provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivariate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixed-window brushing and correlation-enhanced display. We conceived our system with a team of climate researchers, who already made a few important discoveries using it. This demonstrates our system’s great potential to enable scientific discoveries, possibly also in other domains where data have a geospatial reference.

Teaser: Some screenshots of our system:

(Left) An overview of particle compositions and size changes along the flight. The flight track is marked as a red line and each of the one-minute-spaced data points is superimposed as a grey ellipse. The polygon selection tool is used to outline several interesting areas (indicated by yellow polygons and labeled in red) and the corresponding distriibution iconsare drawn nearby. (Right) Changes in particle composition as a function of altitude. We zoom into the flight’s spiral ascent, where the aircraft climbed from a few hundred meters to an altitude of about 7000 m. The pie charts clearly illustrate that particle compositions change significantly with altitude and that the
changes are not monotonic.

Video: Watch to see the system in action:


Paper: Z. Zhang, X. Tong, K. McDonnell, A. Zelenyuk, D. Imre, K. Mueller. "An Interactive Visual Analytics Framework for Multi-Field Data in a Geo-Spatial Context," Tsinghua Science and Technology on Visualization and Computer Graphics, 18(2), April, 2013.pdf

Funding: NSF grant IIS 1117132, a Brookhaven National Lab LDRD grant, and by the US Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.