Abstract

Interactive exploration plays a critical role in large graph visualization. Existing techniques, such as zoom-and-pan on a 2D plane and hyperbolic browser facilitate large graph exploration by showing both the details of a focal area and its surrounding context that guides the exploration process. However, existing techniques for large graph exploration are limited in either providing too little context or presenting graphs with too much distortion. In this paper, we propose a novel focus+context technique, iSphere, to address the limitation. iSphere maps a large graph onto a Riemann Sphere that better preserves graph structures and shows greater context information. We conduct extensive experiment studies on different graph exploration tasks under various conditions. The results show that iSphere performs the best in task completion time compared to the baseline techniques in link and path exploration tasks. This research also contributes to understanding large graph exploration on small screens.

Original languageEnglish (US)
Title of host publicationCHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Pages2916-2927
Number of pages12
Volume2017-May
ISBN (Electronic)9781450346559
DOIs
StatePublished - May 2 2017
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 - Denver, United States
Duration: May 6 2017May 11 2017

Other

Other2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
CountryUnited States
CityDenver
Period5/6/175/11/17

Fingerprint

Visualization
Experiments

Keywords

  • Focus+context
  • Graph exploration
  • Graph visualization

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Du, F., Cao, N., Lin, Y. R., Xu, P., & Tong, H. (2017). iSphere: Focus+Context sphere visualization for interactive large graph exploration. In CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire (Vol. 2017-May, pp. 2916-2927). Association for Computing Machinery. https://doi.org/10.1145/3025453.3025628

iSphere : Focus+Context sphere visualization for interactive large graph exploration. / Du, Fan; Cao, Nan; Lin, Yu Ru; Xu, Panpan; Tong, Hanghang.

CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May Association for Computing Machinery, 2017. p. 2916-2927.

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

Du, F, Cao, N, Lin, YR, Xu, P & Tong, H 2017, iSphere: Focus+Context sphere visualization for interactive large graph exploration. in CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. vol. 2017-May, Association for Computing Machinery, pp. 2916-2927, 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017, Denver, United States, 5/6/17. https://doi.org/10.1145/3025453.3025628
Du F, Cao N, Lin YR, Xu P, Tong H. iSphere: Focus+Context sphere visualization for interactive large graph exploration. In CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May. Association for Computing Machinery. 2017. p. 2916-2927 https://doi.org/10.1145/3025453.3025628
Du, Fan ; Cao, Nan ; Lin, Yu Ru ; Xu, Panpan ; Tong, Hanghang. / iSphere : Focus+Context sphere visualization for interactive large graph exploration. CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May Association for Computing Machinery, 2017. pp. 2916-2927
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