Graph sketches
Irene Finocchi2001
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Abstract
Abstract We introduce the notion of Graph Sketches. They can be thought of as visual indices that guide the navigation of a multi-graph too large to fit on the available display. We adhere to the Visual Information-Seeking Mantra: Overview first, zoom and filter, then details on demand. Graph Sketches are incorporated into MGV, an integrated visualization and exploration system for massive multi-digraph navigation.
Related papers
MGV: a system for visualizing massive multidigraphs
IEEE Transactions on Visualization and Computer Graphics, 2002
We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. It adheres to the Visual Information-Seeking 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 ¢ . MGV builds an out-of-core 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 drill-down interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixel-oriented 2D and 3D maps, statistical displays, color maps, multi-linked 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 multi-graph too large to fit on the available display. MGV follows the client-server paradigm and it is implemented in C and Java-3D. 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 multi-graphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices 1 .
Visualizing massive multi-digraphs
IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings, 2000
We describe MGV, an integrated visualization and exploration system for massive multi-digraph 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 out-of-core 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 drill-down interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixel-oriented 2D and 3D maps, statistical displays, multi-linked 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 Java-3D. 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 multi-graphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices.
Navigation and Interaction in Graph Visualizations
Revista de Informática Teórica e Aplicada, 2008
Graphs are widely utilized in many fields and several applications require their visualization. Graph visualization is based on techniques for graph drawing, interaction and navigation in such a way that helps the user in finding and manipulating information efficiently. These techniques, which can be two or three-dimensional, depending on the spatial metaphor used to represent the graph, can be combined in many different ways in order to fit a particular application's needs. This paper presents an overview of the field of graph visualization.
Graph Visualization and Navigation in Information Visualization:A Survey
IEEE Transactions on Visualization and Computer Graphics, 2000
This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective.
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Ninth International Conference on Information Visualisation (IV'05), 2005
Visualising large graphs faces the challenges of both data complexity and visual complexity. This paper presents a framework for visualising large graphs that reduces data complexity using the clustered graph model and provides users with navigational approaches for browsing clustered graphs. A key design task of such a system is to define a strategy for generating logical abstractions of a clustered graph during navigation. An appropriate abstraction strategy should represent a clustered graph well and avoid visual overload. The semantic fisheye view of a clustered graph is proposed for such a purpose. Two case studies were investigated, and the experiment results show that during navigation the first-order fisheye view of a clustered graph conserves visual complexity at a constant level.
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Lecture Notes in Computer Science, 2005
Compound-fisheye views are introduced as a method for the display and interaction with large graphs. The method relies on a hierarchical clustering of the graph, and a generalization of the traditional fisheye view, together with a treemap representation of the cluster tree.
Methods for Software Visualization of Large Graph Data Structures
International Journal on Advanced Science, Engineering and Information Technology
In this paper, three different methods for software visualization of large graph structures, respectively Rectangle, Intersection and Combined are presented. The basic concepts for using software development environments are outlined. Their capabilities for visual designing and event-oriented programming are discussed. A brief analysis of the basic features of the environment used to develop the ClipRect Monitor application is made. The main functions of this software are also presented. All experimental results in this study are generated with this application. According to the methodology, six graphs are prepared to determine the effectiveness of the three methods. The number of vertices and the edges of these graphs are proportional to the size of the drawing area (canvas). The drawing areas are also six and have different sizes, such that each subsequent area has a height and width twice the size of the previous one. Besides, for all areas, the width/height ratio is exactly 16:9. This ratio is widely used in monitors as well as laptops, mobile phones and tablets. The largest drawing area that the ClipRect Monitor application scanned during the experiments is 128 000 x 72 000 pixels. This scan is performed for graph G_6 with 1 415 vertices and 100 000 edges. The visualization area is diagonally positioned relative to the drawing area. For each visualization area, each of the three methods, respectively Rectangle, Intersection and Combined is performed. The Combined method executes the Rectangle method first and then the Intersection method. The results show that the Intersection method was the slowest compared to the other two methods in terms of the number of edges of the graph that are analyzed. When the visualization area is internal to the drawing area, the Rectangle method performs better than the Combined method. The Rectangle method gives the best result in terms of time for analysis and drawing of the edges of the graph. The Combined method combines the characteristics of the other two methods. This method is optimal in terms of the time of analysis of the need to draw the edges of the graph relative to the number of drawn edges.
CGV—An interactive graph visualization system
2009
Previous work on graph visualization has yielded a wealth of efficient graph analysis algorithms and expressive visual mappings. To support the visual exploration of graph structures, a high degree of interactivity is required as well.
Skeletal Images as Visual Cues in Graph Visualization
Eurographics, 1999
The problem of graph layout and drawing is fundamental to many aproaches to the visualization of relational information structures. As the data set grows, the visualization problem is compounded by the need to reconcile the user's need for orientation cues with the danger of information overload. Put simply: How can we limit the number of visual elements on the screen so as not to overwhelm the user yet retain enough information that the user is able to navigate and explore the data set confidently? How can we provide orientational cues so that a user can understand the location of the current viewpoint in a large data set? These are problems inherent not only to graph drawing but information visualization in general. We propose a method which extracts the significant features of a directed acyclic graph as the basis for navigation 1 .
ASK-GraphView : A Large Scale Graph Visualization System
We describe ASK-GraphView, a node-link-based 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. ASK-GraphView also provides facilities for filtering and coloring, annotation and cluster labeling.
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IV Workshop on Information Visualization and Analysis in Social Networks - Brazilian Symposium on Databases, 2008
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Information and Computation/information and Control, 2000
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