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Graph Analytics—Lessons Learned and Challenges Ahead
Sept.-Oct. 2011 (vol. 31 no. 5)
pp. 18-29
ASCII Text
x 
 
Pak Chung Wong, Chaomei Chen, Carsten Gorg, Ben Shneiderman, John Stasko, Jim Thomas, "Graph Analytics—Lessons Learned and Challenges Ahead," IEEE Computer Graphics and Applications, vol. 31, no. 5, pp. 18-29, Sept.-Oct., 2011.
 
 
BibTex
x
 
@article{ 10.1109/MCG.2011.72,
author = {Pak Chung Wong and Chaomei Chen and Carsten Gorg and Ben Shneiderman and John Stasko and Jim Thomas},
title = {Graph Analytics—Lessons Learned and Challenges Ahead},
journal ={IEEE Computer Graphics and Applications},
volume = {31},
number = {5},
issn = {0272-1716},
year = {2011},
pages = {18-29},
doi = {http://doi.ieeecomputersociety.org/10.1109/MCG.2011.72},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Computer Graphics and Applications
TI - Graph Analytics—Lessons Learned and Challenges Ahead
IS - 5
SN - 0272-1716
SP18
EP29
EPD - 18-29
A1 - Pak Chung Wong,
A1 - Chaomei Chen,
A1 - Carsten Gorg,
A1 - Ben Shneiderman,
A1 - John Stasko,
A1 - Jim Thomas,
PY - 2011
KW - visualization
KW - simulation
KW - modeling
KW - GreenGrid
KW - power grid analysis
KW - social networks
KW - citation analysis
KW - text analysis
KW - document analysis
KW - semantic substrates
KW - Jigsaw system
KW - CiteSpace
KW - computer graphics
KW - graphics and multimedia
VL - 31
JA - IEEE Computer Graphics and Applications
ER -
 
Pak Chung Wong, Pacific Northwest National Laboratory
Chaomei Chen, Drexel University
Carsten Gorg, University of Colorado Denver
Ben Shneiderman, University of Maryland
John Stasko, Georgia Institute of Technology
Jim Thomas, Pacific Northwest National Laboratory
Graph analytics is one of the most influential and important R&D topics in the visual analytics community. Researchers with diverse backgrounds from information visualization, human-computer interaction, computer graphics, graph drawing, and data mining have pursued graph analytics from scientific, technical, and social approaches. These studies have addressed both distinct and common challenges. Past successes and mistakes can provide valuable lessons for revising the research agenda. In this article, six researchers from four academic and research institutes identify graph analytics' fundamental challenges and present both insightful lessons learned from their experience and good practices in graph analytics research. The goal is to critically assess those lessons and shed light on how they can stimulate research and draw attention to grand challenges for graph analytics. The article also establishes principles that could lead to measurable standards and criteria for research.

1. J.J. Thomas and K.A. Cook eds., , Illuminating the Path: The Research and Development Agenda for Visual Analytics, IEEE CS Press, 2005.
2. P.C. Wong et al., "A Novel Visualization Technique for Electric Power Grid Analytics," IEEE Trans. Visualization and Computer Graphics, vol. 15, no. 3, 2009, pp. 410–423.
3. S. Milgram, "The Small-World Problem," Psychology Today, vol. 2, 1967, pp. 60–67.
4. A. Aris and B. Shneiderman, "Designing Semantic Sub-strates for Visual Network Exploration," Information Visualization J., vol. 6, no. 4, 2007, pp. 1–20.
5. B. Shneiderman and A. Aris, "Network Visualization by Semantic Substrates," IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 5, 2006, pp. 733–740.
6. J. Stasko, C. Görg, and Z. Liu, "Jigsaw: Supporting Investigative Analysis through Interactive Visualiza-tion," Information Visualization, vol. 7, no. 2, 2008, pp. 118–132.
7. C. Plaisant et al., "Evaluating Visual Analytics at the 2007 VAST Symposium Contest," IEEE Computer Graphics and Applications, vol. 28, no. 2, 2008, pp. 12–21.
8. C. Chen, "An Information-Theoretic View of Visual Analytics," IEEE Computer Graphics and Applications, vol. 28, no. 1, 2008, pp. 18–23.
9. C. Chen, "CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature," J. Am. Soc. Information Science and Technology, vol. 57, no. 3, 2006, pp. 359–377.
10. C. Chen et al., "Towards an Explanatory and Computational Theory of Scientific Discovery," J. Informetrics, vol. 3, no. 3, 2009, pp. 191–209.
11. G.M. Namata et al., "A Dual-View Approach to Interactive Network Visualization," Proc. ACM Conf. Information and Knowledge Management, ACM Press, 2007, pp. 939–942.

Index Terms:
visualization, simulation, modeling, GreenGrid, power grid analysis, social networks, citation analysis, text analysis, document analysis, semantic substrates, Jigsaw system, CiteSpace, computer graphics, graphics and multimedia
Citation:
Pak Chung Wong, Chaomei Chen, Carsten Gorg, Ben Shneiderman, John Stasko, Jim Thomas, "Graph Analytics—Lessons Learned and Challenges Ahead," IEEE Computer Graphics and Applications, vol. 31, no. 5, pp. 18-29, Sept.-Oct. 2011, doi:10.1109/MCG.2011.72
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