Texture-based edge bundling: A web-based approach for interactively visualizing large graphs

Jieting Wu; Lina Yu; Hongfeng Yu

doi:10.1109/BigData.2015.7364046

Texture-based edge bundling: A web-based approach for interactively visualizing large graphs

Jieting Wu, Lina Yu, Hongfeng Yu

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

Directly visualizing a large graph as a node-link diagram often incurs visual clutter. Edge bundling can effectively address this issue and concisely reveal the main graph structure with reduced visual clutter. Although researchers have devoted noticeable efforts to develop acceleration methods, it remains a challenging task to efficiently conduct edge bundling on devices with a limited computing capacity, such as ubiquitous smart mobile devices. We present a new method for visualizing a node-link diagram based on force-directed edge bundling. We use textures to encode the data of lines and forces, and employ shaders to conduct the iterative line refinement on GPUs. We name this method as Texture-Based Edge Bundling (TBEB) as the major steps are done using textures. We demonstrate the high performance of TBEB using standard graphics cards. TBEB makes it feasible to interactively visualize large graphs on web-based platforms.

Original language	English (US)
Title of host publication	Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
Editors	Feng Luo, Kemafor Ogan, Mohammed J. Zaki, Laura Haas, Beng Chin Ooi, Vipin Kumar, Sudarsan Rachuri, Saumyadipta Pyne, Howard Ho, Xiaohua Hu, Shipeng Yu, Morris Hui-I Hsiao, Jian Li
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2501-2508
Number of pages	8
ISBN (Electronic)	9781479999255
DOIs	https://doi.org/10.1109/BigData.2015.7364046
State	Published - Dec 22 2015
Event	3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States Duration: Oct 29 2015 → Nov 1 2015

Publication series

Name	Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Other

Other	3rd IEEE International Conference on Big Data, IEEE Big Data 2015
Country/Territory	United States
City	Santa Clara
Period	10/29/15 → 11/1/15

Keywords

GPU computing
edge bundling
graph visualization
mobile devices
network visualization

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems
Software

Access to Document

10.1109/BigData.2015.7364046

Cite this

Wu, J., Yu, L., & Yu, H. (2015). Texture-based edge bundling: A web-based approach for interactively visualizing large graphs. In F. Luo, K. Ogan, M. J. Zaki, L. Haas, B. C. Ooi, V. Kumar, S. Rachuri, S. Pyne, H. Ho, X. Hu, S. Yu, M. H.-I. Hsiao, & J. Li (Eds.), Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015 (pp. 2501-2508). Article 7364046 (Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2015.7364046

Texture-based edge bundling: A web-based approach for interactively visualizing large graphs. / Wu, Jieting; Yu, Lina; Yu, Hongfeng.
Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. ed. / Feng Luo; Kemafor Ogan; Mohammed J. Zaki; Laura Haas; Beng Chin Ooi; Vipin Kumar; Sudarsan Rachuri; Saumyadipta Pyne; Howard Ho; Xiaohua Hu; Shipeng Yu; Morris Hui-I Hsiao; Jian Li. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2501-2508 7364046 (Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wu, J, Yu, L & Yu, H 2015, Texture-based edge bundling: A web-based approach for interactively visualizing large graphs. in F Luo, K Ogan, MJ Zaki, L Haas, BC Ooi, V Kumar, S Rachuri, S Pyne, H Ho, X Hu, S Yu, MH-I Hsiao & J Li (eds), Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015., 7364046, Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015, Institute of Electrical and Electronics Engineers Inc., pp. 2501-2508, 3rd IEEE International Conference on Big Data, IEEE Big Data 2015, Santa Clara, United States, 10/29/15. https://doi.org/10.1109/BigData.2015.7364046

Wu J, Yu L, Yu H. Texture-based edge bundling: A web-based approach for interactively visualizing large graphs. In Luo F, Ogan K, Zaki MJ, Haas L, Ooi BC, Kumar V, Rachuri S, Pyne S, Ho H, Hu X, Yu S, Hsiao MHI, Li J, editors, Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2501-2508. 7364046. (Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015). doi: 10.1109/BigData.2015.7364046

Wu, Jieting ; Yu, Lina ; Yu, Hongfeng. / Texture-based edge bundling : A web-based approach for interactively visualizing large graphs. Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. editor / Feng Luo ; Kemafor Ogan ; Mohammed J. Zaki ; Laura Haas ; Beng Chin Ooi ; Vipin Kumar ; Sudarsan Rachuri ; Saumyadipta Pyne ; Howard Ho ; Xiaohua Hu ; Shipeng Yu ; Morris Hui-I Hsiao ; Jian Li. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2501-2508 (Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015).

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abstract = "Directly visualizing a large graph as a node-link diagram often incurs visual clutter. Edge bundling can effectively address this issue and concisely reveal the main graph structure with reduced visual clutter. Although researchers have devoted noticeable efforts to develop acceleration methods, it remains a challenging task to efficiently conduct edge bundling on devices with a limited computing capacity, such as ubiquitous smart mobile devices. We present a new method for visualizing a node-link diagram based on force-directed edge bundling. We use textures to encode the data of lines and forces, and employ shaders to conduct the iterative line refinement on GPUs. We name this method as Texture-Based Edge Bundling (TBEB) as the major steps are done using textures. We demonstrate the high performance of TBEB using standard graphics cards. TBEB makes it feasible to interactively visualize large graphs on web-based platforms.",

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AB - Directly visualizing a large graph as a node-link diagram often incurs visual clutter. Edge bundling can effectively address this issue and concisely reveal the main graph structure with reduced visual clutter. Although researchers have devoted noticeable efforts to develop acceleration methods, it remains a challenging task to efficiently conduct edge bundling on devices with a limited computing capacity, such as ubiquitous smart mobile devices. We present a new method for visualizing a node-link diagram based on force-directed edge bundling. We use textures to encode the data of lines and forces, and employ shaders to conduct the iterative line refinement on GPUs. We name this method as Texture-Based Edge Bundling (TBEB) as the major steps are done using textures. We demonstrate the high performance of TBEB using standard graphics cards. TBEB makes it feasible to interactively visualize large graphs on web-based platforms.

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KW - network visualization

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Texture-based edge bundling: A web-based approach for interactively visualizing large graphs

Abstract

Publication series

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Keywords

ASJC Scopus subject areas

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