Structure-aware Fisheye Views for Efficient Large Graph Exploration

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2019
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Wang, Yunhai
Wang, Yanyan
Zhang, Haifeng
Sun, Yinqi
Fu, Chi-Wing
Sedlmair, Michael
Chen, Baoquan
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Zusammenfassung

Traditional fisheye views for exploring large graphs introduce substantial distortions that often lead to a decreased readability of paths and other interesting structures. To overcome these problems, we propose a framework for structure-aware fisheye views. Using edge orientations as constraints for graph layout optimization allows us not only to reduce spatial and temporal distortions during fisheye zooms, but also to improve the readability of the graph structure. Furthermore, the framework enables us to optimize fisheye lenses towards specific tasks and design a family of new lenses: polyfocal, cluster, and path lenses. A GPU implementation lets us process large graphs with up to 15,000 nodes at interactive rates. A comprehensive evaluation, a user study, and two case studies demonstrate that our structure-aware fisheye views improve layout readability and user performance.

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004 Informatik
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Graph Visualization, Focus+Context Technique, Structure-aware Zoom, Graph Layout Technique
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ISO 690WANG, Yunhai, Yanyan WANG, Haifeng ZHANG, Yinqi SUN, Chi-Wing FU, Michael SEDLMAIR, Baoquan CHEN, Oliver DEUSSEN, 2019. Structure-aware Fisheye Views for Efficient Large Graph Exploration. In: IEEE Transactions on Visualization and Computer Graphics. 2019, 25(1), pp. 566-575. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2018.2864911
BibTex
@article{Wang2019-01Struc-43139,
  year={2019},
  doi={10.1109/TVCG.2018.2864911},
  title={Structure-aware Fisheye Views for Efficient Large Graph Exploration},
  number={1},
  volume={25},
  issn={1077-2626},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  pages={566--575},
  author={Wang, Yunhai and Wang, Yanyan and Zhang, Haifeng and Sun, Yinqi and Fu, Chi-Wing and Sedlmair, Michael and Chen, Baoquan and Deussen, Oliver}
}
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