TreeMatrix: A Hybrid Visualization of Compound Graphs

Rufiange, Sébastien; McGuffin, Michael; Fuhrman, Christopher

doi:10.1111/j.1467-8659.2011.02087.x

Cited by 36 publications

(30 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous work have explored the possibility of combining techniques to visualize a network at one moment in time [21,33]. A paper [18] also explored the usefulness of hybrids in the context of dynamic networks by nesting representations inside a different one.…”

Section: Hybrid Visualizationsmentioning

confidence: 99%

“…However, matrices can be more scalable, even for dense networks. Since they are complementary in some ways, combining them may be useful (as shown in TreeMatrix [33] and NodeTrix [21]). Elastic Hierarchies [43] also aims to combine advantages of node-link diagrams and treemaps for visualizing trees.…”

Section: Taxonomy Of Hybrid Visualizations With Focal and Context Regmentioning

confidence: 99%

See 1 more Smart Citation

DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation

Rufiange

McGuffin

2013

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Fig. 1. Given a dynamic graph defined over a series of time slices, our DiffAni hybrid visualization displays it as a sequence of consecutive tiles. Each tile may show one or more time slices, and there are three kinds of tiles: diff tiles (indicated with a solid border and two time slice numbers below them, e.g., the left-most tile), animation tiles (indicated with a dashed border and two time slice numbers below them, e.g., the tile covering time slices 2 to 3), and small multiple tiles (indicated with a solid border and a single time slice number below them, e.g., the right-most tile). Nodes and edges are colored in red if they are being removed, or green if they are being added, over time slices. The radial menu above is being used to convert a diff tile into two small multiple ("SM") tiles.Abstract-Visualization of dynamically changing networks (graphs) is a significant challenge for researchers. Previous work has experimentally compared animation, small multiples, and other techniques, and found trade-offs between these. One potential way to avoid such trade-offs is to combine previous techniques in a hybrid visualization. We present two taxonomies of visualizations of dynamic graphs: one of non-hybrid techniques, and one of hybrid techniques. We also describe a prototype, called DiffAni, that allows a graph to be visualized as a sequence of three kinds of tiles: diff tiles that show difference maps over some time interval, animation tiles that show the evolution of the graph over some time interval, and small multiple tiles that show the graph state at an individual time slice. This sequence of tiles is ordered by time and covers all time slices in the data. An experimental evaluation of DiffAni shows that our hybrid approach has advantages over non-hybrid techniques in certain cases.

show abstract

Section: Hybrid Visualizationsmentioning

confidence: 99%

Section: Taxonomy Of Hybrid Visualizations With Focal and Context Regmentioning

confidence: 99%

DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation

Rufiange

McGuffin

2013

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…Fekete et al [15] combined treemaps and node-links to represent additional relationships among data entities. TreeMatrix by Rufiange et al [45] combines adjacency matrices, node-link and arc diagrams, nested inclusion, and icicle diagrams to visualize compound graphs. They all offer a hybrid layouts to represent multiple types of data relations.…”

Section: Hybrid Visualizationmentioning

confidence: 99%

Exploring the Possibilities of Embedding Heterogeneous Data Attributes in Familiar Visualizations

Loorak

Périn

Collins³

et al. 2017

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-Heterogeneous multi-dimensional data are now sufficiently common that they can be referred to as ubiquitous. The most frequent approach to visualizing these data has been to propose new visualizations for representing these data. These new solutions are often inventive but tend to be unfamiliar. We take a different approach. We explore the possibility of extending well-known and familiar visualizations through including Heterogeneous Embedded Data Attributes (HEDA) in order to make familiar visualizations more powerful. We demonstrate how HEDA is a generic, interactive visualization component that can extend common visualization techniques while respecting the structure of the familiar layout. HEDA is a tabular visualization building block that enables individuals to visually observe, explore, and query their familiar visualizations through manipulation of embedded multivariate data. We describe the design space of HEDA by exploring its application to familiar visualizations in the D3 gallery. We characterize these familiar visualizations by the extent to which HEDA can facilitate data queries based on attribute reordering. Permanent repository link

show abstract

“…Two common representations used in social network analysis are node-link (JIANU et al, 2014) diagrams and adjacency matrix views (KANG et al, 2014). Hybrids of the two have also been proposed (RUFIANGE et al, 2012). These approaches organize elements according to the linkage structure of the graph creating a combination of these visual techniques and even others.…”

Section: Introductionmentioning

confidence: 99%

DocGenealogy – Visualizing the doctoral advisors and mentors genealogic tree

Fernandes¹,

Carvalho²

2018

Abakos

View full text Add to dashboard Cite

ResumoDocGenealogy é um projeto de mineração de dados que permite a visualização e a exploração do relacionamento de assessoria / orientação de doutorados por meio de um grafo interativo. A Wikipedia é conhecida por sua natureza colaborativa informal, com base em uma forma livre e não estrutural de produzir informações. Esse é um dos seus pontos fortes, na verdade, a abertura a todo tipo de colaborações. A DocGenealogy utiliza os dados disponíveis da Wikipedia sobre assessoria e orientação para doutorados para descobrir e rastrear as relações existentes entre conselheiros ou mentores e seus alunos. O ponto de partida do processo de mineração de dados é sempre um cientista bem conhecido. Esse processo continua, até encontrar os conselheiros e mentores relacionados com renome co-relacionados, sendo construído iterativamente o grafo de relacionamento. Além disso, o DocGenealogy também mostra visualmente como as pessoas estão distribuídas por alma mater e área de conhecimento. O objetivo principal do trabalho é avaliar a eficácia de técnicas orientadas ao grafo na interpretação dos dados das infoboxes da Wikipedia. Palavras

show abstract

TreeMatrix: A Hybrid Visualization of Compound Graphs

Cited by 36 publications

References 33 publications

DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation

DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation

Exploring the Possibilities of Embedding Heterogeneous Data Attributes in Familiar Visualizations

DocGenealogy – Visualizing the doctoral advisors and mentors genealogic tree

Contact Info

Product

Resources

About