Hierarchical focus+context heterogeneous network visualization

Lei Shi, Qi Liao, Hanghang Tong, Yifan Hu, Yue Zhao, Chuang Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

Aggregation is a scalable strategy for dealing with large network data. Existing network visualizations have allowed nodes to be aggregated based on node attributes or network topology, each of which has its own advantages. However, very few previous systems have the capability to enjoy the best of both worlds. This paper presents OnionGraph, an integrated framework for exploratory visual analysis of large heterogeneous networks. OnionGraph allows nodes to be aggregated based on either node attributes, topology, or a mixture of both. Subsets of nodes can be flexibly split and merged under the hierarchical focus+context interaction model, supporting sophisticated analysis of the network data. Node aggregations that contain subsets of nodes are displayed with multiple concentric circles, or the onion metaphor, indicating how many levels of abstraction they contain. We have evaluated the OnionGraph tool in two real-world cases. Performance experiments demonstrate that on a commodity desktop, OnionGraph can scale to million-node networks while preserving the interactivity for analysis.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE Pacific Visualization Symposium, PacificVis 2014
PublisherIEEE Computer Society
Pages89-96
Number of pages8
ISBN (Print)9781479928736
DOIs
StatePublished - Jan 1 2014
Event2014 7th IEEE Pacific Visualization Symposium, PacificVis 2014 - Yokohama, Kanagawa, Japan
Duration: Mar 4 2014Mar 7 2014

Publication series

NameIEEE Pacific Visualization Symposium
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773

Other

Other2014 7th IEEE Pacific Visualization Symposium, PacificVis 2014
CountryJapan
CityYokohama, Kanagawa
Period3/4/143/7/14

Keywords

  • Graph visualization
  • heterogeneous network
  • visual exploration

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Software

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  • Cite this

    Shi, L., Liao, Q., Tong, H., Hu, Y., Zhao, Y., & Lin, C. (2014). Hierarchical focus+context heterogeneous network visualization. In Proceedings - 2014 IEEE Pacific Visualization Symposium, PacificVis 2014 (pp. 89-96). [6787141] (IEEE Pacific Visualization Symposium). IEEE Computer Society. https://doi.org/10.1109/PacificVis.2014.44