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 ways to interact with them via zooming and
panning. Map-based visualization allows us to explicitly group clusters of related vertices as
"countries" and to present additional information with contour and heatmap overlays. We consider
map representations of the DBLP bibliography server. Words and phrases from paper titles are the
cities in the map, and countries are created based on word and phrase similarity, calculated using
co-occurence. With the help of heatmaps, we can visualize the profile of a particular conference or
journal over a base map of all computer science. Similarly, we can create heatmap profiles for
individual researchers or research groups such as a department. Alternatively, a specific journal
or conference can be used to generate the base map and then a series of heatmap overlays can show
the evolution of research topics in the field over the years. As before, individual researchers or
research groups can be visualized using heatmap overlays but this time over the journal or
conference base map. Finally, visual abstracts can be generated from research papers, providing a
snapshot view of the topics in the paper.
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Stephen Kobourov is a Professor of Computer Science at the University of Arizona. He
completed a BS degree in Mathematics and Computer Science at Dartmouth College in 1995, and a PhD
in Computer Science at Johns Hopkins University in 2000. He worked for a year at the
University of Botswana as a Fulbright Scholar and for two years at the University of Tübingen as a
Humboldt Fellow. He has also worked as a Research Scientist at AT&T Research Labs.