The VCG tool allows the visualization of graphs that occur typically as data structures in programs. We describe the functionality of the VCG tool, its layout algorithm and its heuristics. Our main emphasis in the selection of methods is to achieve a very good performance for the layout of large graphs. The tool supports the partitioning of edges and nodes into edge classes and nested subgraphs, the folding of regions, and the management of priorities of edges. The algorithm produces good drawings and runs reasonably fast even on very large graphs.

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and Demo) Michael Himsolt Universitat Passau, 94032 Passau, GERMANY himsolt@fmi.uni-passau.de Abstract. GraphEd is an extensible graph editor. Its powerful object oriented user interface supports all operations that are necessary for the convenient construction and manipulation of graphs. Graph grammars can be used as a macro system to create structured graphs. GraphEd's modular structure and the application interface support the easy integration of algorithm modules which are written in C, or can run external programs. The user may construct graphs interactively, select algorithms from a menu, and view the results of an algorithm directly on screen. Several graph layout algorithms assist the user to tidy graph drawings, and help the programmer to visualize results or debug complex algorithms. Actual applications range from standard graph algorithms over graph drawing algorithms, algorithm animation and combinatorial algorithms to front ends for circuit design systems. 1 Introduction...

Abstract—Despite extensive research, it is still difficult to produce effective interactive layouts for large graphs. Dense layout and occlusion make food webs, ontologies, and social networks difficult to understand and interact with. We propose a new interactive Visual Analytics component called TreePlus that is based on a tree-style layout. TreePlus reveals the missing graph structure with visualization and interaction while maintaining good readability. To support exploration of the local structure of the graph and gathering of information from the extensive reading of labels, we use a guiding metaphor of “Plant a seed and watch it grow. ” It allows users to start with a node and expand the graph as needed, which complements the classic overview techniques than can be effective at- but often limited to- revealing clusters. We describe our design goals, describe the interface, and report on a controlled user study with 28 participants comparing TreePlus with a traditional graph interface for six tasks. In general, the advantage of TreePlus over the traditional interface increased as the density of the displayed data increased. Participants also reported higher levels of confidence in their answers with TreePlus and most of them preferred TreePlus.

Abstract. The rapidly developing field of diagrammatic knowledge representation and reasoning is surveyed. The origins and rationale of the field, basic principles and methodologies, as well as selected applications are discussed. Closely related areas, like visual languages, data presentation, and visualization are briefly introduced as well. Basic sources of material for further study are indicated. Key words: diagrammatic representation, diagrammatic reasoning, visual languages, diagrams, visual programming, data presentation, visualization, knowledge representation, computer graphics, qualitative physics, geometry theorem proving. 1.

The WorldWide Web is a huge, growing repository of information on a wide range of topics. It is also becoming important, commercially and sociologically, as a place of human interaction within different communities. In this paper we present an experimental study of the structure of the Web. We analyze link topologies of various communities, and patterns of mirroring of content, on 1997 and 1999 snapshots of the Web. Our results give insight into patterns of interaction within communities and how they evolve, as well as patterns of data replication. We also describe the techniques we have developed for performing complex processing on this large data set, and our experiences in doing so. We present new algorithms for finding partial and complete mirrors in URL hierarchies; these are also of independent interest for search and redirection. In order to study and visualize link topologies of different communities, we have developed techniques to compact these large link graphs w...

Abstract. We present almost linear area bounds for drawing complete trees on the octagonal grid. For 7-ary trees we establish an upper and lower bound of Θ(n 1.129) and for ternary trees the bounds of O(n 1.048) and Θ(n), where the latter needs edge bends. We explore the unit edge length and area complexity of drawing unordered trees on k-grids with k ∈ {4, 6, 8} and generalize the N P-hardness results of the orthogonal and hexagonal grid to the octagonal grid. 1

Agraph is a simple, powerful, elegant abstraction with broad applicability in computer science and many related fields. Algorithms that operate on graphs see heavy use in both theoretical and practical contexts. Graphs have a very natural visual representation as nodes and connecting links arranged in space. Seeing this structure explicitly can aid tasks in many domains. Many people automatically sketch such a picture when thinking about small graphs, often including simple annotations. The pervasiveness of visual representations of small graphs testifies to their usefulness. On the other hand, although many large data sets can be expressed as graphs, few such visual representations exist. What causes this discrepancy? For one thing, graph layout poses a hard problem, 1 one that current tools just can’t overcome. Conventional systems often falter when handling hundreds of edges, and none can handle more than a few thousand edges. 2 Drawing graphs as nodes connected by links is visually compelling but computationally difficult. Hyperbolic space and spanning trees can reduce visual clutter, speed up layout, and provide fluid interaction. However, nonvisual manipulation of graphs with 50,000 edges is commonplace, and much larger instances exist. We can consider the Web as an extreme example of a graph with many millions of nodes and edges. Although many individual Web sites stay quite small, a significant number have more than 20,000 documents. The Unix file system reachable from a single networked workstation might include more than 100,000 files scattered across dozens of gigabytes worth of remotely mounted disk drives. Computational complexity is not the only reason that software to visually manipulate large graphs has lagged behind software to computationally manipulate them. Many previous graph layout systems have focused on fine-tuning the layout of relatively small graphs in support of polished presentations. A graph drawing system that focuses on the interactive browsing of large graphs

Visualizing and exploring network data has been a challenging problem for HCI (Human-Computer Interaction) Information Visualization researchers due to the complexity of representing networks (graphs). Research in this area has concentrated on improving the visual organization of nodes and links according to graph drawing aesthetics criteria, such as minimizing link crossings and the longest link length. Semantic substrates offer a different approach by which node locations represent node attributes. Users define semantic substrates for a given dataset according to the dataset characteristics and the questions, needs, and tasks of users. The substrates are typically 2-5 non-overlapping rectangular regions that meaningfully lay out the nodes of the network, based on the node attributes. Link visibility filters are provided to enable users to limit link visibility to those within or across regions. The reduced clutter and visibility of only selected links are designed to help users find meaningful relationships. This dissertation presents 5 detailed case studies (3 long-term and 2 shortterm) that report on sessions with professional users working on their own datasets using successive versions of the NVSS (Network Visualization by Semantic Substrates,

Graphs are a very commonly used information structure, and have been applied to a broad range of fields from computer science to biology. There are several important issues to consider when designing graph visualizations. One of the most difficult problems researchers face is how to visualize large graphs. While an algorithm may produce good layouts for graphs of several hundred nodes, it may not scale well to several thousand nodes. And, as the size of the graph increases, performance will degrade rapidly, making it difficult to build an interactive system. Label readability will also suffer, hindering users ’ abilities to understand the graph data and perform many tasks. Finally, even if a system can lay out and display large graphs, the cognitive demands placed on the user by the visualization may be overwhelming. This dissertation describes and applies several design principles to various graph visualization domains to address these issues. Tightly-coupled and highly customized views were used for graph visualization in a novel way. A new tree layout approach to graph visualization was proposed with appropriate visualization and interaction techniques. When visualizing graphs as trees, a guiding metaphor