Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs

Cakmak, Eren; Schlegel, Udo; Jäckle, Dominik; Keim, Daniel A.; Schreck, Tobias

doi:10.1109/tvcg.2020.3030398

Cited by 12 publications

(8 citation statements)

References 47 publications

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“…The approaches enable users to analyze relationships and clusters across scales to identify similar network topologies. For example, Multiscale Snapshots [56] utilizes graph embeddings with multiple visual metaphors to semi-automatically analyze temporal states and trends in dynamic graphs. The two approaches display various temporal scales using different visual representations at all analysis levels.…”

Section: Multiscale Visual Analyticsmentioning

confidence: 99%

Multiscale Visualization: A Structured Literature Analysis

Cakmak

Jäckle

Schreck

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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Multiscale visualizations are typically used to analyze multiscale processes and data in various application domains, such as the visual exploration of hierarchical genome structures in molecular biology. However, creating such multiscale visualizations remains challenging due to the plethora of existing work and the expression ambiguity in visualization research. Up to today, there has been little work to compare and categorize multiscale visualizations to understand their design practices. In this work, we present a structured literature analysis to provide an overview of common design practices in multiscale visualization research. We systematically reviewed and categorized 122 published journal or conference papers between 1995 and 2020. We organized the reviewed papers in a taxonomy that reveals common design factors. Researchers and practitioners can use our taxonomy to explore existing work to create new multiscale navigation and visualization techniques. Based on the reviewed papers, we examine research trends and highlight open research challenges.

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Section: Multiscale Visual Analyticsmentioning

confidence: 99%

Multiscale Visualization: A Structured Literature Analysis

Cakmak

Jäckle

Schreck

et al. 2022

IEEE Trans. Visual. Comput. Graphics

Self Cite

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“…With the increasing scale of dynamic graph data, traditional sequential node-link and matrix-based diagrams fail to display all the graphs in a plane which is space limited (e.g., computer and mobile screen, etc). To address above problems, researches design many techniques to visualizing dynamic graphs such as graph animation [1,11,32], parallel-based node-link diagram [5,14], graph snapshots [6,43], graph navigation [19,25], graph projection [13], set-based graph [34], graph clustering [17,47], and hypergraph visualization [29,41]. For example, animating the graphs according to the timestamps in dynamic graph evolution analysis and structure analysis can reduce the showing space, transferring the time for space [1].…”

Section: Dynamic Graph Visualizationmentioning

confidence: 99%

“…In recent years, integrating visual analytic methods becomes a popular selection for researchers in analyzing dynamic graphs. Many dynamic graph visualization works focus on animating graph topology [11,32], encoding graph elements in effective visual manners [2,54], providing overview of timestamps [6,18], comparing the topology structures [19], etc. However, current dynamic graph visualization works still have a gap in helping users analyze the large-scale and time-intensive dynamic graph data with subtle changes such as basketball player networks in a competition.…”

Section: Introductionmentioning

confidence: 99%

DGSVis: Visual Analysis of Hierarchical Snapshots in Dynamic Graph

Chang¹

2022

Preprint

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s1 d average player speed average link distance average link stabiliity Fig. 1. The system interface of DGSVis includes (a) a matrix to provide an overview of basketball player networks, (b) a scatter plot to offer a projection based on the vector of basketball player networks, (c) a mix of the line chart and node-link diagram to integrate a additional event information, (d) a tree diagram to present a snapshot generation operation flow, (e) a node-link diagram to display the details of snapshots on the field, and (f) combined line charts to show players' detailed attributes.

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“…Specifically, the support for dynamic hypergraphs with many time steps is very limited. One could, for example, explore how novel concepts in dynamic networks visualizations beyond animations [9] are applicable to hypergraphs. Further, there is no established benchmark dataset for hypergraph visualizations, no established performance metrics, and only a limited discussion [16,39] on specific tasks.…”

Section: Future Directionsmentioning

confidence: 99%

Towards a Survey on Static and Dynamic Hypergraph Visualizations

Fischer,

Frings,

Keim

et al. 2021

Preprint

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Leveraging hypergraph structures to model advanced processes has gained much attention over the last few years in many areas, ranging from protein-interaction in computational biology to image retrieval using machine learning. Hypergraph models can provide a more accurate representation of the underlying processes while reducing the overall number of links compared to regular representations. However, interactive visualization methods for hypergraphs and hypergraph-based models have rarely been explored or systematically analyzed. This paper reviews the existing research landscape for hypergraph and hypergraph model visualizations and assesses the currently employed techniques. We provide an overview and a categorization of proposed approaches, focusing on performance, scalability, interaction support, successful evaluation, and the ability to represent different underlying data structures, including a recent demand for a temporal representation of interaction networks and their improvements beyond graph-based methods. Lastly, we discuss the strengths and weaknesses of the approaches and give an insight into the future challenges arising in this emerging research field.

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Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs

Cited by 12 publications

References 47 publications

Multiscale Visualization: A Structured Literature Analysis

Multiscale Visualization: A Structured Literature Analysis

DGSVis: Visual Analysis of Hierarchical Snapshots in Dynamic Graph

Towards a Survey on Static and Dynamic Hypergraph Visualizations

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