GraphView  with F. van Ham and N. Krishnan.
We describe ASKGraphView, a nodelinkbased graph visualization system that allows clustering and interactive navigation of large graphs, ranging in size up to 16 million edges. The system uses a scalable architecture and a series of increasingly sophisticated clustering algorithms to construct a hierarchy on an arbitrary, weighted undirected input graph. By lowering the interactivity requirements we can scale to substantially bigger graphs. The user is allowed to navigate this hierarchy in a top down manner by interactively expanding individual clusters. ASKGraphView also provides facilities for filtering and coloring, annotation and cluster labeling. "Ask Graph View", IEEE Transaction on Visualization and Computer Graphics, Vol 12. No 5, 2006 

Graph Axes  with C. Tominski and H. Schumann.
We present two novel radial visual arrangements: the TimeWheel and the MultiComb. They are part of an interactive framework called VisAxes which can be used for multidimentional data browsing and analysis. "Axes Based Visualizations", Symposium in Applied Computing'04 

Graph Sketches  with Irene Finocchi and Jeffrey L. Korn.
We introduce the notion of Graph Sketches. They can be thought of as visual indices that guide the navigation of a multigraph too large to fit on the available display. We adhere to the Visual InformationSeeking Mantra: Overview first, zoom and filter, then details on demand. Graph Sketches are incorporated into MGV, an integrated visualization and exploration system for massive multidigraph navigation. We highlight the main algorithmic and visualization tasks behind the computation of Graph Sketches and illustrate several application scenarios. Graph Sketches will be used to guide the navigation of multidigraphs defined on vertex sets with sizes ranging from 100 to 250 million vertices. "Graph Sketches", IEEE Symposium on Information Vizualization 2001 

MGV with Jeffrey L. Korn.
MGV, an integrated visualization and exploration system for massive multidigraph navigation. It adheres to the Visual InformationSeeking Mantra: overview first, zoom and filter, then details on demand. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a predetermined tree $T$. MGV builds an outofcore graph hierarchy and provides mechanisms to plug in arbitrary visual representations for each graph hierarchy slice. Navigation from one level to another of the hierarchy corresponds to the implementation of a drilldown interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixeloriented 2D and 3D maps, statistical displays, color maps, multilinked views, and a zoomable label based interface. This makes the association of geographic information and graph data very natural. To automate the creation of the vertex set hierarchy for MGV, we use the notion of graph sketches. They can be thought of as visual indices that guide the navigation of a multigraph too large to fit on the available display. MGV follows the clientserver paradigm and it is implemented in C and Java3D. We highlight the main algorithmic and visualization techniques behind the tools and, along the way, point out several possible application scenarios. Our techniques are being applied to multigraphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices. "A System for Visualizing Massive Multidigraphs", IEEE Transactions on Visualization and Computer Graphics 8(1): 2138 (2002) 

Visualizing Massive MultiDigraphs  with Jeffrey Korn.
MGV is an integrated visualization and exploration system for massive multidigraph navigation. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a predetermined tree T. MGV builds an outofcore graph hierarchy and provides mechanisms to plug in arbitrary visual representations for each graph hierarchy slice. Navigation from one level to another of the hierarchy corresponds to the implementation of a drilldown interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixeloriented 2D and 3D maps, statistical displays, multilinked views, and a zoomable label based interface. This makes the association of geographic information and graph data very natural. MGV follows the clientserver paradigm and it is implemented in C and Java3D. We highlight the main algorithmic and visualization techniques behind the tools and point out along the way several possible application scenarios. Our techniques are being applied to multigraphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices. "Visualizing Massive MultiDigraphs", IEEE Symposium on Information Vizualization 2000 

Graph Surfaces  with Shankar Krishnan.
A broad spectrum of massive data sets can be modeled as dynamic weighted multidigraphs with sizes ranging from tens of gigabytes to petabytes. The sheer size of these data repositories brings with it interesting visualization and computational challenges. We introduce the notion of graph surfaces as a metaphor that allows the integration of visualization and computation over these data sets. By using outofcore algorithms we build a hierarchy of graph surfaces that represents a virtual geography for the data set. In order to provide the user with navigation control and interactive response, we incorporate a number of geometric techniques from 3D computer graphics like terrain triangulation and mesh simplification. We highlight the main algorithmic ideas behind the tools and formulate some novel mathematical problems that have surfaced along the way. < "Postcript"> "Graph Surfaces", In Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems(P. M. Pardalos, Editor), pp. 116, 1999, Kluwer Academic Publishers. 

LargeScale Network Visualization  with E. Koutsofios, E. Gansner and S. North
A multidisciplinary project investigating visualization and analysis for AT&T’s network and service businesses. SIGGRAPH Newsletter, August 1999 
An Interpreted Algorithm Animation System  with C. Smith.
We present the main elements of a novel algorithm animation system. Algorithms are expressed in a language that resembles textbook settheoretical descriptions. An animation editor allows a user to express animations via a graphical interface. A language mechanism for binding algorithmic operations to animation actions is provided. By using our own interpreted programming language, more flexible ways to map conceptuallevel algorithmic operations to animation actions are possible than with more conventional animation approaches. < "Postcript"> "An Interpreted Algorithm Animation System", Proc. ICCI'94, 15691588 1994 Int. Conf. on Computing and Information, 1994 
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