Visualization Directions

Visualization Directions

Document Visualization at UMBC Penny Rheingans October 2002 Goals Provide powerful and flexible visual

representations of document data in order to facilitate exploration and explanation Develop novel information visualization and interaction techniques applicable to a wide range of document types Document Metadata

Date Relevance multiple measures Topic multiple keywords

Provenance Whatever Information Visualization Toolkit Glyph-based visualization of document by metadata Glyph per document

Metadata values mapped interactively to 3D position Color Size Opacity Interactive 3D viewing

Built on vtk with tcl/tk interface Recent Advances Implemented on both irix and linux platforms Automatic and flexible scaling Basic clustering

Ongoing Efforts

Additional platforms Performance enhancements Picking and probing Dynamic update Closer integration with IR engines Application to intrusion detection

New Directions for ivtk Additional visualization techniques, possibly Additional dimension reduction methods Parallel coordinates Improved user interface with expanded interaction modes

(carried out as part of LUCITE task) Address issues of scale

Provide both context and detail on demand Filtering of data items Generalization and summary representations Glyphs for composite objects Hierarchical viewing modes (LUCITE)

Filtering of Data Items Select which individual items to show Drastically reduce number of items displayed Subsetting mechanisms Interactive value-based selection Stochastic sampling

Select how to show individual items Direct attention to match interest Modulate appearance of items Emphasis Filter Approach Treat match to target as variable Map to perceptually-based parameter or alter base

mapping Interaction capabilities dynamic control of view dynamic control of some visualization parameters Previous SFA-based prototype

Personal Profiles Individual weightings for documents flexible audience-specific interactive Supplement to precomputed relevance

simple measures computed dynamically Matching Mechanisms Value Requirement Composite multiple factors

fuzzy matches Threshold significance levels Window focus area

Future Directions in Filtering Revive prototype Extend to include profile mechanism profile construction and manipulation matching metric specification

Integrate with ivtk Summary Representations Convey overview of corpus structure without showing each individual document Possibilities Visualization processes to create and render aggregates

Splatting or other implicit representations Isosurfaces or volume rendering Explicit analysis to characterize structure Glyphs for Composite Objects Extend glyph representation to apply to composite objects

Collections Clusters Information of interest about composites Mean variable value Variable range/variability Number of component objects

Composite Metaphors Display mean and variability information in consistent manner Position Color

Some visual attributes dedicated to supporting other display parameters Opacity Shape

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