Querying and Creating Visualizations by Analogy

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]  Jonas Holmerin,et al.  Clique Is Hard to Approximate within n1-o(1) , 2000, ICALP.

[2]  Clifford Stein,et al.  Introduction to algorithms. Chapter 16. 2nd Edition , 2001 .

[3]  William J. Schroeder,et al.  The Visualization Toolkit , 2005, The Visualization Handbook.

[4]  David H. Laidlaw,et al.  The application visualization system: a computational environment for scientific visualization , 1989, IEEE Computer Graphics and Applications.

[5]  Jarke J. van Wijk,et al.  The value of visualization , 2005, VIS 05. IEEE Visualization, 2005..

[6]  Amy Nicole Langville,et al.  Google's PageRank and beyond - the science of search engine rankings , 2006 .

[7]  Ken Brodlie,et al.  Visualization in grid computing environments , 2004, IEEE Visualization 2004.

[8]  Luis Ibáñez,et al.  The ITK Software Guide , 2005 .

[9]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[10]  Michael Gertz,et al.  A Model and Framework for Visualization Exploration , 2007, IEEE Transactions on Visualization and Computer Graphics.

[11]  Dennis Shasha,et al.  Algorithmics and applications of tree and graph searching , 2002, PODS.

[12]  T. J. Jankun-Kelly,et al.  Visualization Exploration and Encapsulation via a Spreadsheet-Like Interface , 2001, IEEE Trans. Vis. Comput. Graph..

[13]  C.R. Johnson,et al.  SCIRun: A Scientific Programming Environment for Computational Steering , 1995, Proceedings of the IEEE/ACM SC95 Conference.

[14]  Johan Håstad,et al.  Clique is hard to approximate within n/sup 1-/spl epsiv// , 1996, Proceedings of 37th Conference on Foundations of Computer Science.

[15]  Moshé M. Zloof Query-by-Example: A Data Base Language , 1977, IBM Syst. J..

[16]  Clifford Stein,et al.  Introduction to Algorithms, 2nd edition. , 2001 .

[17]  Eric A. Bier,et al.  Graphical search and replace , 1988, SIGGRAPH.

[18]  Thomas Nocke,et al.  A History Mechanism for Visual Data Mining , 2004 .

[19]  Cláudio T. Silva,et al.  Managing the Evolution of Dataflows with VisTrails , 2006, 22nd International Conference on Data Engineering Workshops (ICDEW'06).

[20]  Steven K. Feiner,et al.  A history-based macro by example system , 1992, UIST '92.

[21]  Cláudio T. Silva,et al.  Tackling the Provenance Challenge one layer at a time , 2008 .

[22]  Cláudio T. Silva,et al.  VisTrails: enabling interactive multiple-view visualizations , 2005, VIS 05. IEEE Visualization, 2005..

[23]  Penny Rheingans,et al.  NIH-NSF visualization research challenges report summary , 2006, IEEE Computer Graphics and Applications.

[24]  Gene H. Golub,et al.  Matrix computations , 1983 .

[25]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[26]  Erhard Rahm,et al.  Similarity flooding: a versatile graph matching algorithm and its application to schema matching , 2002, Proceedings 18th International Conference on Data Engineering.

[27]  Nelson L. Max,et al.  A contract based system for large data visualization , 2005, VIS 05. IEEE Visualization, 2005..