This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Querying and Creating Visualizations by Analogy
November/December 2007 (vol. 13 no. 6)
pp. 1560-1567
While there have been advances in visualization systems, particularly in multi-view visualizations and visual exploration, the process of building visualizations remains a major bottleneck in data exploration. We show that provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions. We describe an implementation of these techniques in VisTrails, a publicly-available, open-source system.

[1] L. Bavoil, S. Callahan, P. Crossno, J. Freire, C. Scheidegger, C. Silva, and H. Vo, VisTrails: Enabling interactive, multiple-view visualizations. In Proceedings of IEEE Visualization, pages 135–142, 2005.
[2] S. Brin and L. Page, The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30 (1–7): 107–117, 1998.
[3] K. Brodlie, D. Duce, J. Gallop, M. Sagar, J. Walton, and J. Wood, Visualization in grid computing environments. In Proceedings of IEEE Visualization, pages 155–162, 2004.
[4] S. Callahan, J. Freire, E. Santos, C. Scheidegger, C. Silva, and H. Vo., Managing the evolution of dataflows with VisTrails. In IEEE Workshop on Workflow and Data Flow for Scientific Applications (SciFlow), 2006.
[5] H. Childs, E. S. Brugger, K. S. Bonnell, J. S. Meredith, M. Miller, B. J. Whitlock, and N. Max, A contract-based system for large data visualization. In Proceedings of IEEE Visualization, pages 190–198, 2005.
[6] T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms, chapter 26. MIT Press, 2001.
[7] E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design Patterns: Elements of reusable object-oriented software, chapter 5. Addison-Wesley, 1995.
[8] G. H. Golub and C. F. V. Loan, Matrix computations. Johns Hopkins University Press, Baltimore, MD, USA, 3rd. edition, 1996.
[9] J. Hastad, Clique is hard to approximate within n1-∈. Acta Mathematica, 182: 105–142, 1999.
[10] L. Ibanez, W. Schroeder, L. Ng, and J. Cates, The ITK Software Guide. Kitware, Inc. ISBN 1-930934-15-7, 2nd. edition, 2005.
[11] IBM. OpenDX. http://www.research.ibm.comdx.
[12] T. Jankun-Kelly and K.-L. Ma, Visualization exploration and encapsulation via a spreadsheet-like interface. IEEE Transactions on Visualization and Computer Graphics, 7 (3): 275–287, July/September 2001.
[13] T. Jankun-Kelly, K.-L. Ma, and M. Gertz, A model and framework for visualization exploration. IEEE Transactions on Visualization and Computer Graphics, 13 (2): 357–369, March/April 2007.
[14] G. Kindlmann Teem. http:/teem.sourceforge.net.
[15] Kitware. ParaView. http:/www.paraview.org.
[16] M. Kreuseler, T. Nocke, and H. Schumann, A history mechanism for visual data mining. In Proceedings of IEEE Information Visualization Symposium, pages 49–56, 2004.
[17] D. Kurlander and E. A. Bier, Graphical search and replace. In Proceedings of SIGGRAPH 1988, pages 113–120, 1988.
[18] D. Kurlander and S. Feiner, A history-based macro by example system. In Proceedings of UIST 1992, pages 99–106, 1992.
[19] A. N. Langville and C. D. Meyer, Google's PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press, 2006.
[20] H. Lieberman, editor. Your Wish is My Command: Programming by Example. Morgan Kaufmann, 2001.
[21] S. Melnik, H. Garcia-Molina, and E. Rahm, Similarity flooding: A versatile graph matching algorithm and its application to schema matching. In Proceedings of the 18th International Conference on Data Engineering, pages 117–128, 2002.
[22] Mercury Computer Systems. Amira. http:/www.amiravis.com.
[23] T. Munzner, C. Johnson, R. Moorhead, H. Pfister, P. Rheingans, and T. S. Yoo, NIH-NSF visualization research challenges report summary. IEEE Computer Graphics and Applications, 26 (2): 20–24, 2006.
[24] S. G. Parker and C. R. Johnson, SCIRun: a scientific programming environment for computational steering. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Supercomputing), 1995.
[25] Provenance challenge. http://twiki.ipaw.info/bin/viewChallenge .
[26] C. Scheidegger, D. Koop, E. Santos, H. Vo, S. Callahan, J. Freire, and C. Silva, Tackling the provenance challenge one layer at a time. Concurrency and Computation: Practice and Experience, 2007. To appear.
[27] W. Schroeder, K. Martin, and B. Lorensen, The Visualization Toolkit. Kitware Inc, 2007.
[28] D. Shasha, J. T.-L. Wang, and R. Giugno, Algorithmics and applications of tree and graph searching In Proceedings of the ACM Symposium on Principles of Database Systems, 2002.
[29] C. Upson, J. Thomas Faulhaber, D. Kamins, D. Laidlaw, D. Schlegel, J. Vroom, R. Gurwitz, and A. van Dam, The application visualization system: A computational environment for scientific visualization. IEEE Computer Graphics and Applications, 9 (4): 30–42, 1989.
[30] J. J. van Wijk, The value of visualization. In Proceedings of IEEE Visualization, pages 79–86, 2005.
[31] M. Zloof, Query-by-example: a data base language. IBM Systems Journal, 16 (4): 324–343, 1977.

Index Terms:
visualization systems, query-by-example, analogy
Citation:
Carlos Scheidegger, Huy Vo, David Koop, Juliana Freire, Claudio Silva, "Querying and Creating Visualizations by Analogy," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1560-1567, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70584
Usage of this product signifies your acceptance of the Terms of Use.