Towards a Survey on Static and Dynamic Hypergraph Visualizations

Fischer, Maximilian T.; Frings, Alexander; Keim, Daniel A.; Seebacher, Daniel

doi:10.1109/vis49827.2021.9623305

Cited by 15 publications

(10 citation statements)

References 34 publications

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“…Unlike PivotPaths [DRRD12], where the partitions based on entity types are explicitly revealed spatially, VIGOR [PHE * 17] only uses color and suffers more from visual clutter. Node‐link diagrams are also used to visualize hypergraphs by introducing a new type of node to deal with the encoding of a hyperedge that can connect more than two nodes [FFKS21]. All these studies support a rich set of interactions as visual clutter increases exponentially with the increase in data in node‐link diagrams.…”

Section: Related Workmentioning

confidence: 99%

ChemoGraph: Interactive Visual Exploration of the Chemical Space

Kale

Clyde

Sun

et al. 2023

Computer Graphics Forum

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Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.

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Section: Related Workmentioning

confidence: 99%

ChemoGraph: Interactive Visual Exploration of the Chemical Space

Kale

Clyde

Sun

et al. 2023

Computer Graphics Forum

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“…Dynamic graph visualization has been researched for many years to help people get insights into dynamic graph datasets. Surveys of dynamic graph visualization are already published in diverse aspects such as visual designs [21], task taxonomy [23], community discovery [31],and topology structures [16,46] etc. While employing rational visualization techniques to support scene requirements is still a problem in dynamic graph visualization.…”

Section: Dynamic Graph Visualizationmentioning

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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“…Hypergraphs are the generalization of graphs, where links can include any number of nodes instead of only two [11], and nodes can be of any type (e.g., people, locations). The visualization of dynamic hypergraphs, that represent the evolution of relationships over time, is an active research field [22]. The three more recent visualizations are PAOHViz [55], Hyper-Matrix [21] and HyperStorylines [41].…”

Section: Visualizing Relationships Over Space and Timementioning

confidence: 99%

Geo-Storylines: Integrating Maps Into Storyline Visualizations

Hulstein

Peña-Araya

Bezerianos

2022

IEEE Trans. Visual. Comput. Graphics

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Fig. 1: Three Geo-Storyline designs showing the geo-temporal evolution of the relationships between people. The two selected people in blue moved together from north to south. (A) Coordinated Views include a map on the left and a unique Storyline timeline on the right. While scrolling, links appear between the relationship nearest to the map and the associated locations. (B) In Map Glyphs each relationship is represented by a map with the associated locations drawn in orange. (C) Time Glyphs are composed by a map on the left and a scrollable list of Storyline glyphs on the right. Each Storyline glyph contains all the relationships associated with one location. Gray lines between a location on the map and a storyline glyph indicate the correspondence between the two.

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Towards a Survey on Static and Dynamic Hypergraph Visualizations

Cited by 15 publications

References 34 publications

ChemoGraph: Interactive Visual Exploration of the Chemical Space

ChemoGraph: Interactive Visual Exploration of the Chemical Space

DGSVis: Visual Analysis of Hierarchical Snapshots in Dynamic Graph

Geo-Storylines: Integrating Maps Into Storyline Visualizations

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