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49
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, statetransition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs ..."
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Cited by 322 (3 self)
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This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as web browsing, statetransition 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. Index TermsInformation visualization, graph visualization, graph drawing, navigation, focus+context, fisheye, clustering. 1
Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data
 IEEE Transactions on Visualization and Computer Graphics
, 2006
"... Abstract—A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., nonhierarch ..."
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Cited by 139 (9 self)
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Abstract—A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., nonhierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a Bspline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations.
Multilevel Visualization of Clustered Graphs
, 1997
"... Clustered graphs are graphs with recursive clustering structures over the vertices. This type of structure appears in many systems. Examples include CASE tools, management information systems, VLSI design tools, and reverse engineering systems. Existing layout algorithms represent the clustering str ..."
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Cited by 81 (2 self)
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Clustered graphs are graphs with recursive clustering structures over the vertices. This type of structure appears in many systems. Examples include CASE tools, management information systems, VLSI design tools, and reverse engineering systems. Existing layout algorithms represent the clustering structure as recursively nested regions in the plane. However, as the structure becomes more and more complex, two dimensional plane representations tend to be insufficient. In this paper, firstly, we describe some two dimensional plane drawing algorithms for clustered graphs; then we show how to extend two dimensional plane drawings to three dimensional multilevel drawings. We consider two conventions: straightline convex drawings and orthogonal rectangular drawings; and we show some examples. 1 Introduction Graph drawing algorithms are widely used in graphical user interfaces of software systems. As the amount of information that we want to visualize becomes larger, we need more structure ...
StraightLine Drawing Algorithms for Hierarchical Graphs and Clustered Graphs
 Algorithmica
, 1999
"... Hierarchical graphs and clustered graphs are useful nonclassical graph models for structured relational information. Hierarchical graphs are graphs with layering structures; clustered graphs are graphs with recursive clustering structures. Both have applications in CASE tools, software visualizatio ..."
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Cited by 59 (12 self)
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Hierarchical graphs and clustered graphs are useful nonclassical graph models for structured relational information. Hierarchical graphs are graphs with layering structures; clustered graphs are graphs with recursive clustering structures. Both have applications in CASE tools, software visualization, and VLSI design. Drawing algorithms for hierarchical graphs have been well investigated. However, the problem of straightline representation has not been solved completely. In this paper, we answer the question: does every planar hierarchical graph admit a planar straightline hierarchical drawing? We present an algorithm that constructs such drawings in linear time. Also, we answer a basic question for clustered graphs, that is, does every planar clustered graph admit a planar straightline drawing with clusters drawn as convex polygons? We provide a method for such drawings based on our algorithm for hierarchical graphs.
A Space of Presentation Emphasis Techniques for Visualizing Graphs
 In Graphics Interface'94
, 1994
"... The graph topovisual formalism has been shown to be wellsuited to the task of visualizing complex relations on a set of elements. Unfortunately, most visual formalisms do not scale very well. This observation is particularly true of graphs, which even when handdrawn by an artist, are seldom meani ..."
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Cited by 48 (2 self)
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The graph topovisual formalism has been shown to be wellsuited to the task of visualizing complex relations on a set of elements. Unfortunately, most visual formalisms do not scale very well. This observation is particularly true of graphs, which even when handdrawn by an artist, are seldom meaningful when the number of nodes or links exceeds a very modest threshold  typically only a few hundred elements. This severe limitation has prompted many researchers to seek alternative visualization techniques that may eliminate, or, at the very least, raise this threshold. In this paper we analyze these recent efforts, describe an abstract space of presentation emphasis techniques, and locate the current approaches within this space. The contributions of this paper are several: (1) a significant portion of recent work is collected and reviewed; (2) a common set of criteria and a taxonomy of graph views are proposed; these, (3) permit a more direct comparison of previous work; which helps ...
A Multidimensional Approach to ForceDirected Layouts of Large Graphs
, 2000
"... Abstract. We present a novel hierarchical forcedirected method for drawing large graphs. The algorithm produces a graph embedding in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higherdimensional embedding into a two or thr ..."
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Cited by 36 (5 self)
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Abstract. We present a novel hierarchical forcedirected method for drawing large graphs. The algorithm produces a graph embedding in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higherdimensional embedding into a two or three dimensional subspace of E. Projecting highdimensional drawings onto two or three dimensions often results in drawings that are “smoother ” and more symmetric. Among the other notable features of our approach are the utilization of a maximal independent set filtration of the set of vertices of a graph, a fast energy function minimization strategy, efficient memory management, and an intelligent initial placement of vertices. Our implementation of the algorithm can draw graphs with tens of thousands of vertices using a negligible amount of memory in less than one minute on a midrange PC. 1
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 multidigraph navigation. ..."
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Cited by 30 (7 self)
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We describe MGV, an integrated visualization and exploration system for massive multidigraph navigation.
Architecture Recovery of Web Applications
, 2002
"... Web applications are the legacy software of the future. Developed under tight schedules, with high employee turn over, and in a rapidly evolving environment, these systems are often poorly structured and poorly documented. Maintaining such systems is problematic. This paper presents an approach to r ..."
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Cited by 29 (6 self)
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Web applications are the legacy software of the future. Developed under tight schedules, with high employee turn over, and in a rapidly evolving environment, these systems are often poorly structured and poorly documented. Maintaining such systems is problematic. This paper presents an approach to recover the architecture of such systems, in order to make maintenance more manageable. Our lightweight approach is flexible and retargetable to the various technologies that are used in developing web applications. The approach extracts the structure of dynamic web applications and shows the interaction between their various components such as databases, distributed objects, and web pages. The recovery process uses a set of specialized extractors to analyze the source code and binaries of web applications. The extracted data is manipulated to reduce the complexity of the architectural diagrams. Developers can use the extracted architecture to gain a better understanding of web applications and to assist in their maintenance. Keywords Web Applications, Software Architecture, Reverse Engineering, Architecture Recovery, Redocumentation. 1
A Fast MultiDimensional Algorithm for Drawing Large Graphs
 In Graph Drawing’00 Conference Proceedings
, 2000
"... We present a novel hierarchical forcedirected method for drawing large graphs. The algorithm produces a graph embedding in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higherdimensional embedding into a two or three dimensi ..."
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Cited by 28 (4 self)
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We present a novel hierarchical forcedirected method for drawing large graphs. The algorithm produces a graph embedding in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higherdimensional embedding into a two or three dimensional subspace of E. Projecting highdimensional drawings onto two or three dimensions often results in drawings that are "smoother" and more symmetric. Among the other notable features of our approach are the utilization of a maximal independent set filtration of the set of vertices of a graph, a fast energy function minimization strategy, e#cient memory management, and an intelligent initial placement of vertices. Our implementation of the algorithm can draw graphs with tens of thousands of vertices using a negligible amount of memory in less than one minute on a midrange PC. 1 Introduction Graphs are common in many applications, from data structures to networks, from software engineering...
A multiperspective software visualization environment
 In Proc. of CASCON’2000
, 2000
"... This paper describes a multiperspective software visualization environment, SHriMP, which combines single view and multiview techniques to support software exploration at both the architectural and source code levels. SHriMP provides three different views: a primary nested view and two subsidiary ..."
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Cited by 26 (5 self)
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This paper describes a multiperspective software visualization environment, SHriMP, which combines single view and multiview techniques to support software exploration at both the architectural and source code levels. SHriMP provides three different views: a primary nested view and two subsidiary views. The primary nested view employs fisheye views of nested graphs, provides contextual cues, and supports general exploration activities. In SHriMP, subsidiary views exist as a searching tool and a relation tracer. These views complement each other and allow programmers to examine a software system from multiple perspectives.