SchemaLine: Timeline Visualization for Sensemaking

Timeline visualization is an important tool for sense making. It allows analysts to examine information in chronological order and to identify temporal patterns and relationships. However, many existing timeline visualization methods are not designed for the dynamic and iterative nature of the sense making process and the various analysis activities it involves. In this paper, we introduce a novel timeline visualization, Schema Line, to address these deficiencies. Schema Line is designed to group notes into analyst-determined schema, using a layout algorithm to produce compact but aesthetically pleasing timeline visualization, and includes fluid user interactions to support sense making activities. It enables interactive temporal schemata construction with seamless integration with visual data exploration and note taking. Our preliminary evaluation results show that the participants found the new method easy to learn and use, and its features effective for the sense making activities for which it was designed.

[1]  Vijay Kumar,et al.  Metadata visualization for digital libraries: interactive timeline editing and review , 1998, DL '98.

[2]  Neesha Kodagoda,et al.  INVISQUE: intuitive information exploration through interactive visualization , 2011, CHI EA '11.

[3]  Niklas Elmqvist,et al.  Fluid interaction for information visualization , 2011, Inf. Vis..

[4]  Ben Shneiderman,et al.  LifeLines: visualizing personal histories , 1996, CHI.

[5]  Jennifer K. Phillips,et al.  A Data–Frame Theory of Sensemaking , 2007 .

[6]  Monica M. C. Schraefel,et al.  Continuum: designing timelines for hierarchies, relationships and scale , 2007, UIST.

[7]  Kawa Nazemi,et al.  SemaTime - Timeline Visualization of Time-Dependent Relations and Semantics , 2010, ISVC.

[8]  Cynthia A. Brewer,et al.  ColorBrewer.org: An Online Tool for Selecting Colour Schemes for Maps , 2003 .

[9]  Mengchen Liu,et al.  StoryFlow: Tracking the Evolution of Stories , 2013, IEEE Transactions on Visualization and Computer Graphics.

[10]  John T. Stasko,et al.  Reflections on the evolution of the Jigsaw visual analytics system , 2014, Inf. Vis..

[11]  Alexander W. Skaburskis,et al.  The Sandbox for analysis: concepts and methods , 2006, CHI.

[12]  M. Sheelagh T. Carpendale,et al.  Empirical Studies in Information Visualization: Seven Scenarios , 2012, IEEE Transactions on Visualization and Computer Graphics.

[13]  P. Pirolli,et al.  The Sensemaking Process and Leverage Points for Analyst Technology as Identified Through Cognitive Task Analysis , 2007 .

[14]  Lucy T. Nowell,et al.  ThemeRiver: Visualizing Thematic Changes in Large Document Collections , 2002, IEEE Trans. Vis. Comput. Graph..

[15]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[16]  Nicholas J. Pioch,et al.  POLESTAR: collaborative knowledge management and sensemaking tools for intelligence analysts , 2006, CIKM '06.

[17]  Michelle X. Zhou,et al.  Interactive Visual Synthesis of Analytic Knowledge , 2006, 2006 IEEE Symposium On Visual Analytics Science And Technology.

[18]  John T. Stasko,et al.  Jigsaw: Supporting Investigative Analysis through Interactive Visualization , 2007, 2007 IEEE Symposium on Visual Analytics Science and Technology.

[19]  Kwan-Liu Ma,et al.  Design Considerations for Optimizing Storyline Visualizations , 2012, IEEE Transactions on Visualization and Computer Graphics.