Circular Visualization Enhancement through Complementary Interaction

In today’s scenario, most of the applications like web repository generate bulk of heterogeneous data. Visualization helps in the interpretation of meaningful information from huge data generated by these applications. There are many visualization techniques available in literature. Parallel Coordinates, Glyph and Projection techniques are some of the famous data visualization techniques. Projection techniques are unable to illustrate the details of data like intertuple variations. Parallel Coordinates have good capacity to express the details, but require more space as well as it is affected from clutter. Trend figure is also affected from clutter up to some extent. Considering the heterogeneous nature of data and limitation of visualization techniques, single visualization technique does not fulfill the analytical requirements of different application domains. But combination of these visualization techniques may fulfill the analytical requirements of applications from different domain. In this work, we have developed a tool, in which Parallel coordinates and trend figure used as interactive techniques with projection technique. The proposed combination reduces the limitation like intertuple variations of projection technique. Analysis of data with proposed tool has the potential to uncover other relationships and non-trivial structures.

[1]  Alfred Inselberg,et al.  Parallel coordinates: a tool for visualizing multi-dimensional geometry , 1990, Proceedings of the First IEEE Conference on Visualization: Visualization `90.

[2]  Robert Kosara,et al.  Privacy-preserving data visualization using parallel coordinates , 2011, Electronic Imaging.

[3]  Kwan-Liu Ma,et al.  StarClass: Interactive Visual Classification using Star Coordinates , 2003, SDM.

[4]  Allison Woodruff,et al.  Guidelines for using multiple views in information visualization , 2000, AVI '00.

[5]  Ivan Bratko,et al.  VizRank: Data Visualization Guided by Machine Learning , 2006, Data Mining and Knowledge Discovery.

[6]  Georges G. Grinstein,et al.  Dimensional anchors: a graphic primitive for multidimensional multivariate information visualizations , 1999, NPIVM '99.

[7]  Jimmy Johansson,et al.  Interactive Exploration of Ingredient Mixtures Using Multiple Coordinated Views , 2009, 2009 13th International Conference Information Visualisation.

[8]  N. Andrienko,et al.  Parallel coordinates for exploring properties of subsets , 2004, Proceedings. Second International Conference on Coordinated and Multiple Views in Exploratory Visualization, 2004..

[9]  Holger Theisel,et al.  An Enhanced Spring Model for Information Visualization , 1998, Comput. Graph. Forum.

[10]  Eser Kandogan,et al.  Visualizing multi-dimensional clusters, trends, and outliers using star coordinates , 2001, KDD '01.

[11]  Jonathan C. Roberts,et al.  On encouraging multiple views for visualization , 1998, Proceedings. 1998 IEEE Conference on Information Visualization. An International Conference on Computer Visualization and Graphics (Cat. No.98TB100246).

[12]  Robert Kosara,et al.  Pargnostics: Screen-Space Metrics for Parallel Coordinates , 2010, IEEE Transactions on Visualization and Computer Graphics.

[13]  Harri Siirtola,et al.  Combining parallel coordinates with the reorderable matrix , 2003, Proceedings International Conference on Coordinated and Multiple Views in Exploratory Visualization - CMV 2003 -.

[14]  Robert Kosara Indirect multi-touch interaction for brushing in parallel coordinates , 2011, Electronic Imaging.

[15]  G. Santucci,et al.  SpringView: cooperation of radviz and parallel coordinates for view optimization and clutter reduction , 2005, Coordinated and Multiple Views in Exploratory Visualization (CMV'05).

[16]  Yuanzhen Li,et al.  Feature congestion: a measure of display clutter , 2005, CHI.

[17]  Richard F. Riesenfeld,et al.  A Survey of Radial Methods for Information Visualization , 2009, IEEE Transactions on Visualization and Computer Graphics.

[18]  Xiaoru Yuan,et al.  Interactive local clustering operations for high dimensional data in parallel coordinates , 2010, 2010 IEEE Pacific Visualization Symposium (PacificVis).

[19]  H. Hauser,et al.  Interactive focus+context visualization with linked 2D/3D scatterplots , 2004, Proceedings. Second International Conference on Coordinated and Multiple Views in Exploratory Visualization, 2004..

[20]  Urska Cvek,et al.  Multidimensional Visualization Tools for Analysis of Expression Data , 2009 .