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8th International Symposium on Visual Information Communication and Interaction (VINCI)

作者： Burch, Michael Univ Stuttgart VISUS Allmandring 19 D-70569 Stuttgart Germany

ISBN: (纸本)9781450334822

Visualizing dynamic graphs is challenging due to the many data dimensions to be displayed such as graph vertices and edges with their attached weights or attributes and the additional time dimension. Moreover, edge directions with multiplicities and the graph topology are also important inherent features. However, in many dynamic graph visualization techniques each graph in a sequence is treated the same way, i.e., it is visually encoded in the same visual metaphor or even in the same layout. This visualization strategy can be problematic if the graphs are changing topologically over time, i.e., if a sparse graph becomes denser and denser over time or a star pattern is changing into a dense cluster of connected vertices. Such a dynamic graph data scenario demands for a visualization approach which is able to adapt the applied visual metaphor to each graph separately. In this paper we show an idea to solve this problem by using multiple visual metaphors for dynamic graphs which are computed automatically by algorithms analyzing each individual graph based on a given repertoire of graph features. The biggest issue in this technique for the graph dynamics, however, is the preservation of the viewer's mental map at metaphor changes, i.e., to guide him through the graph changes with the goal to explore the data for time-varying patterns. To reach this goal we support the analyst by an interactive highlighting feature.

关键词： dynamic graph visualization graph visual metaphors graph algorithms graph layouts

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A Taxonomy and Survey of dynamic graph visualization

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COMPUTER graphICS FORUM 2017年第1期36卷 133-159页

作者： Beck, Fabian Burch, Michael Diehl, Stephan Weiskopf, Daniel Univ Stuttgart VISUS Stuttgart Germany Univ Trier Trier Germany

dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node-link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline-based ones. A bibliographic analysis provides insights into the organization and development of the field and its community. Finally, we identify and discuss challenges for future research. We also provide feedback from experts, collected with a questionnaire, which gives a broad perspective of these challenges and the current state of the field.

关键词： dynamic graph visualization taxonomy survey

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Parallel Edge Splatting for Scalable dynamic graph visualization

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IEEE TRANSACTIONS ON visualization AND COMPUTER graphICS 2011年第12期17卷 2344-2353页

作者： Burch, Michael Vehlow, Corinna Beck, Fabian Diehl, Stephan Weiskopf, Daniel Univ Stuttgart VISUS D-7000 Stuttgart Germany Univ Trier Dept Comp Sci D-54286 Trier Germany

We present a novel dynamic graph visualization technique based on node-link diagrams. The graphs are drawn side-by-side from left to right as a sequence of narrow stripes that are placed perpendicular to the horizontal time line. The hierarchically organized vertices of the graphs are arranged on vertical, parallel lines that bound the stripes;directed edges connect these vertices from left to right. To address massive overplotting of edges in huge graphs, we employ a splatting approach that transforms the edges to a pixel-based scalar field. This field represents the edge densities in a scalable way and is depicted by non-linear color mapping. The visualization method is complemented by interaction techniques that support data exploration by aggregation, filtering, brushing, and selective data zooming. Furthermore, we formalize graph patterns so that they can be interactively highlighted on demand. A case study on software releases explores the evolution of call graphs extracted from the JUnit open source software project. In a second application, we demonstrate the scalability of our approach by applying it to a bibliography dataset containing more than 1.5 million paper titles from 60 years of research history producing a vast amount of relations between title words.

关键词： dynamic graph visualization graph splatting software visualization software evolution

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Isoline-Enhanced dynamic graph visualization 20

Isoline-Enhanced Dynamic Graph Visualization

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20th International Conference Information Visualisation (IV)

作者： Burch, Michael Univ Stuttgart VISUS Stuttgart Germany

ISBN: (纸本)9781467389426

Static or dynamic graphs are typically visualized by either node-link diagrams, adjacency matrices, adjacency lists, or hybrids thereof. In particular, for the case of a changing graph structure a viewer wishes to be able to visually compare the graphs in a sequence. Doing such a comparison task rapidly and reliably can give support to visually analyze the dynamic graph for certain dynamic patterns. In this paper we describe a novel dynamic graph visualization that is based on the concept of smooth density fields generated by first splatting the links of a given graph in a certain layout. To further visually enhance the time-varying graph structures we add user-adaptable isolines to the resulting dynamic graph representation. The computed visual encoding of the dynamic graph is aesthetically appealing due to its smooth curves and can additionally be used to do comparisons in a long graph sequence, i.e., from an information visualization perspective it serves as an overview representation supporting to start more detailed analyses processes. To demonstrate the usefulness of the technique we explore real-world dynamic graph data by taking into account visual parameters like node-link layouts, smoothing iterations, number of isolines, and different color codings.

关键词： dynamic graph visualization Edge splatting Isolines

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Bundled visualization of dynamic graph and Trail Data

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IEEE TRANSACTIONS ON visualization AND COMPUTER graphICS 2014年第8期20卷 1141-1157页

作者： Hurter, Christophe Ersoy, Ozan Fabrikant, Sara Irina Klein, Tijmen R. Telea, Alexandru C. Univ Toulouse ENAC LII F-31055 Toulouse France Univ Groningen Fac Math & Nat Sci Inst Johann Bernoulli NL-9700 AB Groningen Netherlands Univ Groningen Fac Math & Nat Sci NL-9700 AB Groningen Netherlands Univ Zurich Dept Geog CH-8057 Zurich Switzerland Univ Groningen Dept Math & Comp Sci NL-9747 AG Groningen Netherlands

Depicting change captured by dynamic graphs and temporal paths, or trails, is hard. We present two techniques for simplified visualization of such data sets using edge bundles. The first technique uses an efficient image-based bundling method to create smoothly changing bundles from streaming graphs. The second technique adds edge-correspondence data atop of any static bundling algorithm, and is best suited for graph sequences. We show how these techniques can produce simplified visualizations of streaming and sequence graphs. Next, we show how several temporal attributes can be added atop of our dynamic graphs. We illustrate our techniques with data sets from aircraft monitoring, software engineering, and eye-tracking of static and dynamic scenes.

关键词： dynamic graph visualization edge bundling software visualization trajectories visualization eye tracking

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JOURNAL OF COMPUTER LANGUAGES 2020年 58卷

作者： Burch, Michael Eindhoven Univ Technol Eindhoven Netherlands

Software systems produce long sequences of call graphs, in particular, if the graphs are generated during runtime and not revision by revision. Visualizing, analyzing, and interacting with such long dynamic graphs with respect to different properties is a challenging task. In this article we describe an interactive visualization technique for dynamic call graphs that supports the observation of the data in vertex, edge, and time dimensions based on properties related to the graph topology, inherent vertex hierarchy, involved links, and graph -theoretic pro- blems. Moreover, we provide a time -aligned view on several dynamic graphs with the goal to compare them visually. We also provide standard node -link diagrams for individual graphs or aggregated dynamic graph subsequences as a details -on -demand technique and for supporting graph comparisons on different temporal granularities. We illustrate the usefulness of the dynamic graph visualization by applying it to the call relations at runtime of the open source software project JHotDraw. We evaluated the interactive visualization by re- flecting on the static and dynamic patterns we could identify in the dataset by changing the graph properties under exploration. Moreover, we conducted a controlled user study with 20 participants investigating three typical tasks like finding graph sequences, identifying a complete graph, and exploring the reason for a change in a shortest path algorithm. Finally, we discuss scalabilities and limitations of our approach.

关键词： dynamic graph visualization Software visualization Edge splatting Interleaving Time-dependent data

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Stable visualization of connected components in dynamic graphs

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INFORMATION visualization 2021年第1期20卷 3-19页

作者： Giacomo, Emilio Di Didimo, Walter Kaufmann, Michael Liotta, Giuseppe Univ Perugia Perugia Umbria Italy Univ Tubingen Tubingen Germany

One of the primary goals of many systems for the visual analysis of dynamically changing networks is to maintain the stability of the drawing throughout the sequence of graph changes. We investigate the scenario where the changes are determined by a stream of events, each being either an edge addition or an edge removal. The visualization must be updated immediately after each new event is received. Our main goal is to provide the user with an intuitive visualization that highlights the different connected components of the graph while preserving the user's mental map after each event. The drawing stability is measured in terms of changes in the orthogonal relationships between vertices of two consecutive drawings. We describe two different visualization models, one for the 1-dimensional space and the other for the 2-dimensional space. In both models the connected components are drawn inside rectangular regions. To validate our approach, we report the results of an experimental analysis that compares the drawing stability of the online algorithm with that of an offline algorithm that knows in advance the whole sequence of events. We also present a case study of our online algorithm on a collaboration network.

关键词： dynamic graph visualization drawing stability clustering visualization connected components arc diagrams orthogonal drawings

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Visual analytics of large dynamic digraphs

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INFORMATION visualization 2017年第3期16卷 167-178页

作者： Burch, Michael Univ Stuttgart Visualisat Res Ctr VISUS D-70569 Stuttgart Germany

In this article, we investigate the problem of visually representing and analyzing large dynamic directed graphs that consist of many vertices, edges, and time steps. With this work we do not primarily focus on graph details but more on achieving an overview about long graph sequences with the major focus to be scalable in vertex, edge, and time dimensions. To reach this goal, we first map each graph to a bipartite layout with vertices in the same order for each graph supporting a preservation of the viewer's mental map. A sequence of graphs is placed in a left-to-right reading direction. To further reduce link crossings, we draw partial links with user-definable lengths and finally apply edge splatting as a concept to emphasize graph structures by color coding the generated density fields. Time-varying visual patterns can be recognized by inspecting the changes in the color coding in certain regions in the display. We illustrate the usefulness of the approach in two case studies investigating call graphs changing during software development with 21 releases which is a rather short graph sequence but contains several thousand vertices and edges. Visual scalability in the time dimension is shown with more than 1000 graphs from a dynamic social network dataset consisting of face-to-face contacts acquired during the Hypertext 2009 conference recorded by radio-frequency identification badges.

关键词： dynamic graph visualization partial edges edge splatting visual analytics big graphs

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Community Fabric: Visualizing communities and structure in dynamic networks

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INFORMATION visualization 2022年第2期21卷 130-142页

作者： Ezell, Evan Lim, Seung-Hwan Anderson, David Stewart, Robert Univ Tennessee Knoxville TN USA Oak Ridge Natl Lab POB 2008 Oak Ridge TN 37831 USA Cadre5 Knoxville TN USA

We present Community Fabric, a novel visualization technique for simultaneously visualizing communities and structure within dynamic networks. In dynamic networks, the structure of the network is continuously evolving throughout time and these underlying topological shifts tend to lead to communal changes. Community Fabric helps the viewer more easily interpret and understand the interplay of structural change and community evolution in dynamic graphs. To achieve this, we take a new approach, hybridizing two popular network and community visualizations. Community Fabric combines the likes of the Biofabric static network visualization method with traditional community alluvial flow diagrams to visualize communities in a dynamic network while also displaying the underlying network structure. Our approach improves upon existing state-of-the-art techniques in several key areas. We describe the methodologies of Community Fabric, implement the visualization using modern web-based tools, and apply our approach to three example data sets.

关键词： dynamic graph visualization information visualization network visualization community detection dynamic networks graph drawing

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Exploring density regions for analyzing dynamic graph data

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JOURNAL OF VISUAL LANGUAGES AND COMPUTING 2018年第Feb.期44卷 133-144页

作者： Burch, Michael Univ Stuttgart VISUS Stuttgart Germany

Static or dynamic graphs are typically visualized by either node-link diagrams, adjacency matrices, adjacency lists, or hybrids thereof. In particular, for the case of a changing graph structure a viewer wishes to be able to visually compare the graphs in a sequence. Doing such a comparison task rapidly and reliably demands for visually analyzing the dynamic graph for certain dynamic patterns. In this paper we describe a novel dynamic graph visualization that is based on the concept of smooth density fields generated by first splatting the link information of a given graph in a certain layout or visual metaphor. To further visually enhance the time-varying graph structures we add user-adaptable isolines to the resulting dynamic graph representation. The computed visual encoding of the dynamic graph is aesthetically appealing due to its smooth curves and can additionally be used to do comparisons in a long graph sequence, i.e., from an information visualization perspective it serves as an overview representation supporting to start more detailed analysis processes. To demonstrate the usefulness of the technique we explore real -world dynamic graph data by taking into account visual parameters like visual metaphors, node-link layouts, smoothing iterations, number of isolines, and different color codings. In this extended work we additionally incorporate matrix and list splatting while also supporting the selection of density regions with overlaid link information. Moreover, from the selected graph the user can automatically apply region comparisons with other graphs based on global and local density properties. Such a feature is in particular useful for finding commonalities, hence serving as a special filtering function. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： dynamic graph visualization graph comparisons Edge splatting Isolines Big graphs

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