Scalable Visual Analysis of Geo-Spatial Data

Daniel Keim

Abstract

Never before in history data has been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data has become increasingly difficult. Information visualization and visual analytics can help to deal with the flood ofinformation, since it combines the power of today's computers with the perceptual abilities of the human visual system. Presenting data in an interactive, graphical form often fosters new insights, encouraging the formation and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge.

There are a large number of visualization techniques that have been developed over the last two decades to support the exploration of large geo-spatial data sets. The talk provides an overview of a few novel techniques for visually analyzing large geo-spatial data sets and illustrates them using a number of applications examples. It especially discusses some of the scalability issues involved.