GrouseFlocks: Steerable Exploration of Graph Hierarchy Space

Daniel Archambault, Tamara Munzner, and David Auber

IEEE Transactions on Visualization and Computer Graphics 14(4):900-913 (July/August) 2008
PDF | Abstract | Figures | Source



Several previous systems allow users to interactively explore a large input graph through cuts of a superimposed hierarchy. This hierarchy is often created using clustering algorithms or topological features present in the graph. However, many graphs have domain-specific attributes associated with the nodes and edges which could be used to create many possible hierarchies providing unique views of the input graph. GrouseFlocks is a system for the exploration of this graph hierarchy space. By allowing users to see several different possible hierarchies on the same graph, the system helps users investigate graph hierarchy space instead of a single, fixed hierarchy. GrouseFlocks provides a simple set of operations so that users can create and modify their graph hierarchies based on selections. These selections can be made manually or based on patterns in the attribute data provided with the graph. It provides feedback to the user within seconds, allowing interactive exploration of this space.



datasets and source for GrouseFlocks are available, including a Tulip distribution. If you would like, a precompiled version that works on most Linux distributions is also available.