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A Taxonomy and Survey of dynamic graph visualization

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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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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dynamic graph visualization with Multiple Visual Metaphors 15

Dynamic Graph Visualization with Multiple Visual Metaphors

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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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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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InvestLens: A Visual Analytics Approach to Inspecting the dynamics of Venture Capital Investment Network 39

InvestLens: A Visual Analytics Approach to Inspecting the Dy...

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IEEE 39th International Conference on Data Engineering (ICDE)

作者： Tian, Yun Liu, Jia Zhang, Xinyi Yang, Xingsheng Ke, Zhaoru Zhang, Chenyang Liao, Ling Hong, Suting Zhang, Haipeng Li, Quan ShanghaiTech Univ Sch Informat Sci & Technol Shanghai Peoples R China Univ Illinois Dept Comp Sci Champaign IL USA ABC CA Fund Management Co Ltd Shanghai Peoples R China ShanghaiTech Univ Sch Entrepreneurship & Management Shanghai Peoples R China

ISBN: (纸本)9798350322446

Venture capital (VC) plays an important role in the development of Western economies, fostering innovation and renewal in the broader economy and revealing the dynamics of different frontier industries over time. However, discovering information about industry changes through VC data has been a challenge for partners and research scholars. Researchers have applied many statistical and empirical methods to explore trends and network relationships in VC, but they are often unable to explain how entities in such networks evolve, a difficulty created by the large, heterogeneous, and dynamic nature of VC data. To help them identify industry changes, we designed InvestLens, an interactive visual analytics system to explore the VC syndication network. It identifies the overall pattern and dynamic network evolution of VC and reveals the evolution of related industries. Two case studies and interviews with domain experts validate the validity of InvestLens.

关键词： venture capital investments heterogeneous network embedding dynamic graph visualization

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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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dynamic graph exploration by interactively linked node-link diagrams and matrix visualizations

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Visual Computing for Industry,Biomedicine,and Art 2021年第1期4卷 219-232页

作者： Michael Burch Kiet Bennema ten Brinke Adrien Castella Ghassen Karray Sebastiaan Peters Vasil Shteriyanov Rinse Vlasvinkel Eindhoven University of Technology 5600MB EindhovenThe Netherlands

The visualization of dynamic graphs is a challenging task owing to the various properties of the underlying relational data and the additional time-varying *** sparse and small graphs,the most efficient approach to such visualization is node-link diagrams,whereas for dense graphs with attached data,adjacency matrices might be the better *** graphs can contain both properties,being globally sparse and locally dense,a combination of several visual metaphors as well as static and dynamic visualizations is *** this paper,a visually and algorithmically scalable approach that provides views and perspectives on graphs as interactively linked node-link and adjacency matrix visualizations is *** the novelty of this technique,insights such as clusters or anomalies from one or several combined views can be used to influence the layout or reordering of the other ***,the importance of nodes and node groups can be detected,computed,and visualized by considering several layout and reordering properties in combination as well as different edge properties for the same set of *** an additional feature set,an automatic identification of groups,clusters,and outliers is provided over time,and based on the visual outcome of the node-link and matrix visualizations,the repertoire of the supported layout and matrix reordering techniques is extended,and more interaction techniques are provided when considering the dynamics of the graph ***,a small user experiment was conducted to investigate the usability of the proposed *** usefulness of the proposed tool is illustrated by applying it to a graph dataset,such as e co-authorships,co-citations,and a Comprehensible Perl Archive Network distribution.

关键词： dynamic graph visualization Node-link diagrams Adjacency matrices Layouts Reorderings

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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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Immersive Analytics of Large dynamic Networks via Overview and Detail Navigation 2

Immersive Analytics of Large Dynamic Networks via Overview a...

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2nd IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Sorger, Johannes Waldner, Manuela Knecht, Wolfgang Arleo, Alessio Complex Sci Hub Vienna Austria TU Wien Vienna Austria

ISBN: (纸本)9781728156040

Analysis of large dynamic networks is a thriving research field, typically relying on 2D graph representations. The advent of affordable head mounted displays sparked new interest in the potential of 3D visualization for immersive network analytics. Nevertheless, most solutions do not scale well with the number of nodes and edges and rely on conventional fly- or walk-through navigation. In this paper, we present a novel approach for the exploration of large dynamic graphs in virtual reality that interweaves two navigation metaphors: overview exploration and immersive detail analysis. We thereby use the potential of state-of-the-art VR headsets, coupled with a web-based 3D rendering engine that supports heterogeneous input modalities to enable ad-hoc immersive network analytics. We validate our approach through a performance evaluation and a case study with experts analyzing medical data.

关键词： Immersive Network Analytics Web-Based visualization dynamic graph visualization

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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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