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.