ABSTRACT
We present GraphScape, a directed graph model of the vi- sualization design space that supports automated reasoning about visualization similarity and sequencing. Graph nodes represent grammar-based chart specifications and edges rep- resent edits that transform one chart to another. We weight edges with an estimated cost of the difficulty of interpreting a target visualization given a source visualization. We con- tribute (1) a method for deriving transition costs via a partial ordering of edit operations and the solution of a resulting lin- ear program, and (2) a global weighting term that rewards consistency across transition subsequences. In a controlled experiment, subjects rated visualization sequences covering a taxonomy of common transition types. In all but one case, GraphScape's highest-ranked suggestion aligns with subjects' top-rated sequences. Finally, we demonstrate applications of GraphScape to automatically sequence visualization presen- tations, elaborate transition paths between visualizations, and recommend design alternatives (e.g., to improve scalability while minimizing design changes).
Supplemental Material
- S. Agarwal, J. Wills, L. Cayton, G. Lickriet, D. Kriegman, and S. Belongie. 2007. Generalized Non-metric Multidimensional Scaling. JMLR W&P (AISTATS 2007) 2 (2007), 11--18.Google Scholar
- A. Anand and J. Talbot. 2016. Automatic Selection of Partitioning Variables for Small Multiple Displays. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 669--677. Google ScholarDigital Library
- D. J. Barr, R. Levy, C. Scheepers, and H. J. Tily. 2013. Random Effects Structure for Confirmatory Hypothesis Testing: Keep it Maximal. Journal of Memory and Language 68, 3 (2013), 255--278. Google ScholarCross Ref
- S. P. Callahan, J. Freire, E. Santos, C. E. Scheidegger, C. T. Silva, and H. T. Vo. 2006. Managing the Evolution of Dataflows with VisTrails. In Proc. 22nd International Conference on Data Engineering Workshops (ICDEW'06). IEEE. Google ScholarDigital Library
- W. S. Cleveland and R. McGill. 1984. Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. J. Amer. Statist. Assoc. 79 (1984), 531--554. Google ScholarCross Ref
- T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. 2009. Introduction to Algorithms (3rd ed.). MIT Press.Google Scholar
- Ç. Demiralp, M. S. Bernstein, and J. Heer. 2014. Learning Perceptual Kernels for Visualization Design. IEEE Transactions on Visualization and Computer Graphics 20, 12 (2014), 1933--1942. http: //idl.cs.washington.edu/papers/perceptual-kernels Google ScholarCross Ref
- J. Heer, J. Mackinlay, C. Stolte, and M. Agrawala. 2008. Graphical Histories for Visualization: Supporting Analysis, Communication, and Evaluation. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1189--1196. http: //idl.cs.washington.edu/papers/graphical-histories Google ScholarDigital Library
- J. Heer and G. G. Robertson. 2007. Animated Transitions in Statistical Data Graphics. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1240--1247. http: //idl.cs.washington.edu/papers/animated-transitions Google ScholarDigital Library
- J. Heer, F. B. Viégas, and M. Wattenberg. 2007. Voyagers and Voyeurs: Supporting Asynchronous Collaborative Information Visualization. In Proc. ACM Human Factors in Computing Systems (CHI). ACM, 1029--1038. http://idl.cs.washington.edu/papers/senseus/ Google ScholarDigital Library
- J. Hullman, S. Drucker, N. H. Riche, B. Lee, D. Fisher, and E. Adar. 2013. A Deeper Understanding of Sequence in Narrative Visualization. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2406--2415. Google ScholarDigital Library
- T.J. Jankun-Kelly, K.-L. Ma, and M. Gertz. 2007. A Model and Framework for Visualization Exploration. IEEE Transactions on Visualization and Computer Graphics 13, 2 (2007), 357--369. Google ScholarDigital Library
- K.-L. Ma. 1999. Image Graphs -- A Novel Approach to Visual Data Exploration. In Proc. IEEE Visualization. IEEE, 81--88.Google Scholar
- J. Mackinlay. 1986. Automating the Design of Graphical Presentations of Relational Information. ACM Transactions on Graphics 5, 2 (1986), 110--141. Google ScholarDigital Library
- J. Mackinlay, P. Hanrahan, and C. Stolte. 2007. ShowMe: Automatic Presentation for Visual Analysis. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1137--1144. Google ScholarDigital Library
- A. Satyanarayan, D. Moritz, K. Wongsuphasawat, and J. Heer. 2017. Vega-Lite: A Grammar of Interactive Graphics. To appear in IEEE Transactions on Visualization and Computer Graphics (2017). http://idl.cs.washington.edu/papers/vega-liteGoogle Scholar
- C. E. Scheidegger, H. T. Vo, D. Koop, J. Freire, and C. T. Silva. 2007. Querying and Creating Visualizations by Analogy. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1560--1567. Google ScholarDigital Library
- E. Segel and J. Heer. 2010. Narrative Visualization: Telling Stories with Data. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1139--1148. http://idl.cs.washington.edu/papers/narrative Google ScholarDigital Library
- C. Stolte, D. Tang, and P. Hanrahan. 2002. Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases. IEEE Transactions on Visualization and Computer Graphics 8, 1 (2002), 52--65. Google ScholarDigital Library
- M. Vartak, S. Rahman, S. Madden, A. Parameswaran, and N. Polyzotis. 2015. SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics. Proceedings of the VLDB Endowment 8, 13 (2015), 2182--2193. Google ScholarDigital Library
- H. Wickham. 2009. ggplot2: Elegant Graphics for Data Analysis. Springer.Google ScholarDigital Library
- L. Wilkinson. 1999. The Grammar of Graphics. Springer. Google ScholarCross Ref
- K. Wongsuphasawat, D. Moritz, A. Anand, J. Mackinlay, B. Howe, and J. Heer. 2016. Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 649--658. Google ScholarDigital Library
Index Terms
- GraphScape: A Model for Automated Reasoning about Visualization Similarity and Sequencing
Recommendations
Visualization of Biological Sequence Similarity Search Results
VIS '95: Proceedings of the 6th conference on Visualization '95Biological sequence similarity analysis presents visualization challenges, primarily because of the massive amounts of discrete, multi-dimensional data. Genomic data generated by molecular biologists is analyzed by algorithms that search for similarity ...
Quaternary Golay sequence pairs II: odd length
A 4-phase Golay sequence pair of length s 5 (mod 8) is constructed from a Barker sequence of the same length whose even-indexed elements are prescribed. This explains the origin of the 4-phase Golay seed pairs of length 5 and 13. The construction ...
New Design of Low-Correlation Zone Sequence Sets
In this paper, we present several construction methods for low-correlation zone (LCZ) sequence sets. First, we propose a design scheme for binary LCZ sequence sets with parameters (2n+1-2,M,L,2). In this scheme, we can freely set the LCZ length L and ...
Comments