Putting Data on the Map
Stephen Kobouorov, Professor of Computer Science, University of Arizona
Relational data sets are often visualized with graphs: objects become the graph vertices and relations become the graph edges. Graph drawing algorithms aim to present such data in an effective and aesthetically appealing way. We describe map representations, which provide a way to visualize relational data with the help of conceptual maps as a data representation metaphor. While graphs often require considerable effort to comprehend, a map representation is more intuitive, as most people are familiar with maps and standard map interactions via zooming and panning. Map-based visualization allows us to explicitly group related vertices into countries" and to present additional information with contour and heatmap overlays. The graph-to-map (GMap) algorithmic framework will be discussed, including applications, such as our Maps of Computer Science (MoCS), as well as experimental results on the effectiveness of the approach.
Stephen Kobourov is a Professor of Computer Science at the University of Arizona. He completed BS degrees in Mathematics and Computer Science at Dartmouth College in 1995, and a PhD in Computer Science at Johns Hopkins University in 2000. He has worked as a Research Scientist at AT&T Research Labs, a Hulmboldt Fellow at the University of Tübingen in Germany, and a Distinguished Fulbright Chair at Charles University in Prague.