VisLink: Revealing Relationships Amongst Visualizations

Contributors

Christopher Collins, Gerald Penn, Sheelagh Carpendale

Abstract

We have developed VisLink, a method by which visualizations and the relationships between them can be interactively explored. Our approach uses multiple 2D layouts, drawing each one in its own plane. These planes can then be placed and re-positioned in 3D space: side by side, in parallel, or in chosen placements that provide favoured views. Relationships, connections, and patterns between visualizations can be revealed and explored using a variety of interaction techniques including spreading activation and search filters.

We have also devised a formalism for understanding and comparing methods of mutli-relationship visualization, and analyze how the most popular methods (compound graphs, coordinated multiple views, Semantic Substrates) compare to VisLink. VisLink readily generalizes to support multiple visualizations, empowers inter-representational queries, and enables the reuse of the spatial variables, thus supporting efficient information encoding and providing for powerful visualization bridging.

Ongoing research is investigating the application of VisLink to real analysis scenarios in various data domains. We are also extending the capability for powerful inter-visualization queries.

Publications

  • C. Collins and S. Carpendale, “VisLink: Revealing Relationships Amongst Visualizations,” IEEE Trans. on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization (InfoVis)), vol. 13, iss. 6, 2007.
    [Bibtex] [PDF] [DOI]
    @article{COL2007c,
      author =  {Christopher Collins and Sheelagh Carpendale},
      title =      {VisLink: Revealing Relationships Amongst Visualizations},
      journal =  {IEEE Trans. on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization (InfoVis))},
      year = 2007,
      volume = 13,
      number = 6,
      month =   {Nov./Dec.},
      publisher =   {IEEE},
      doi = {10.1109/TVCG.2007.70521}
    }

PDF of PowerPoint presentation from InfoVis 2007

Media

 


Acknowledgements

 

Research

ThreadReconstructor: Modeling Reply-Chains to Untangle Conversational Text through Visual Analytics

Detecting Negative Emotion for Mixed Initiative Visual Analytics

EduApps – Supporting Non-Native English Speakers to Overcome Language Transfer Effects

Metatation: Annotation as Implicit Interaction to Bridge Close and Distant Reading

DataTours: A Data Narratives Framework

Perceptual Biases in Font Size as a Data Encoding

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework

Abbreviating Text Labels on Demand

NEREx: Named-Entity Relationship Exploration in Multi-Party Conversations

ConToVi: Multi-Party Conversation Exploration using Topic-Space Views

PhysioEx: Visual Analysis of Physiological Event Streams

Using Visual Analytics of Heart Rate Variation to Aid in Diagnostics

Off-Screen Desktop

PivotSlice

Reading Comprehension on Mobile Devices

#FluxFlow: Visual Analysis of Anomalous Information Spreading on Social Media

Optimizing Hierarchical Visualizations with the Minimum Description Length Principle

Lexichrome

SentimentState: Exploring Sentiment Analysis on Twitter

Facilitating Discourse Analysis with Interactive Visualization

DimpVis

Glidgets

TandemTable

Simple Multi-Touch Toolkit

Exploring Text Entities with Descriptive Non-photorealistic Rendering

Investigating the Semantic Patterns of Passwords

Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations

Parallel Tag Clouds to Explore Faceted Text Corpora

VisLink: Revealing Relationships Amongst Visualizations

DocuBurst: Visualizing Document Content using Language Structure

Tabletop Text Entry Techniques

Lattice Uncertainty Visualization: Understanding Machine Translation and Speech Recognition

WordNet Visualization

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