nd maps are powerful abstractions. Their combination, Hierarchical Graph Maps, provide effective tools to process a graph that is too large to fit on the screen. They provide hierarchical visual indices (i.e. maps) that guide navigation and visualization. Hierarchical graph maps deal in a unified manner with both the screen and I/O bottlenecks. This line of thinking adheres to the Visual Information Seeking Mantra: Overview first, zoom and filter, then details on demand (Information Visualization: dynamic queries, star field displays and lifelines, in www.cr.umd.edu, 1997). We highlight the main tasks behind the computation of Graph Maps and provide several examples. The techniques have been used experimentally in the navigation of graphs defined on vertex sets ranging from 100 to 250 million vertices. r 2004 Elsevier Ltd. All rights reserved.