Collection Understanding Michelle Chang, John J. Leggett, Richard Furuta, Andruid Kerne Texas A&M University Michelle Chang, John J. Leggett, Richard Furuta, Andruid Kerne Texas A&M University J. Patrick Williams, Samuel A. Burns, Randolph G. Bias University of Texas at Austin

Introduction Large collection of digital artifacts Actual contents difficult to perceive Image retrieval methods are insufficient Large collection of digital artifacts Actual contents difficult to perceive Image retrieval methods are insufficient

Collection Understanding Understand the essence of the collection by focusing on the artifacts Comprehensive view Not locating specific artifacts Understand the essence of the collection by focusing on the artifacts Comprehensive view Not locating specific artifacts

Collection Understanding (CU) vs. Information Retrieval (IR) Find specific artifacts Prior knowledge of metadata Define queries Find specific artifacts Prior knowledge of metadata Define queries

Related Work Collages Photo Browsers Image Browsers Ambient Displays Collages Photo Browsers Image Browsers Ambient Displays

Collage combinFormation Collaborage Notification Collage Aesthetic Information Collages Video Collage combinFormation Collaborage Notification Collage Aesthetic Information Collages Video Collage

Photo Browsers Calendar Browser Hierarchical Browser FotoFile PhotoFinder PhotoMesa Calendar Browser Hierarchical Browser FotoFile PhotoFinder PhotoMesa

Image Browsers Zoomable Image Browser Strip-Browser Flamenco Image Browser Zoomable Image Browser Strip-Browser Flamenco Image Browser

Ambient Displays Dangling String Tangible Bits Informative Art Dangling String Tangible Bits Informative Art

Problems with Querying by Metadata Currently the most used method Two levels: collection, artifact Creator/maintainer/collector defines metadata Time-consuming Vague Currently the most used method Two levels: collection, artifact Creator/maintainer/collector defines metadata Time-consuming Vague

Problems with Browsing Pre-defined and fixed structure Requires large amount of navigation (pointing and clicking) Narrows a collection Pre-defined and fixed structure Requires large amount of navigation (pointing and clicking) Narrows a collection

Problems with Scrolling Limited screen space Entire result set not visible Requires large amount of pointing and clicking Limited screen space Entire result set not visible Requires large amount of pointing and clicking

Visualization Streaming Collage Ambient Slideshow Variably Gridded Thumbnails Streaming Collage Ambient Slideshow Variably Gridded Thumbnails

Streaming Collage Collage is “an assembly of diverse fragments” Streaming – constructed dynamically in time Collage is “an assembly of diverse fragments” Streaming – constructed dynamically in time

Metadata Filtering Modifying metadata fields and values Expand result set Constrain result set Modifying metadata fields and values Expand result set Constrain result set

Connecting Streaming Collage with Metadata Filtering Continuous Process of: Interactively filtering metadata Generating dynamic collage Temporal and Spatial Continuous Process of: Interactively filtering metadata Generating dynamic collage Temporal and Spatial

Demonstration: Metadata Filtering

Demonstration: Streaming Collage

Demonstration: Subcollections

Ambient Slideshow Peripheral Display Chance encounters Slowly reveals artifacts in the collection Peripheral Display Chance encounters Slowly reveals artifacts in the collection

Demonstration: Ambient Picasso

Demonstration: Variably Gridded Thumbnails

Variably Gridded Thumbnails Relevance measure Full-text search Grid of thumbnails Grid element’s background color varies Relevance measure Full-text search Grid of thumbnails Grid element’s background color varies

Evaluation Independent evaluation Usability study gauged intuitiveness of interface 15 graduate students: UT at Austin Independent evaluation Usability study gauged intuitiveness of interface 15 graduate students: UT at Austin

No Directed Tasks Users “queried the database” Didn’t right-click on any images Didn’t use metadata filtering Users “queried the database” Didn’t right-click on any images Didn’t use metadata filtering

Directed Tasks Successfully created collages Right-clicked on images Used metadata filtering Successfully created collages Right-clicked on images Used metadata filtering

Conclusions from study Improvements for intuitive interface –Initial engagement –Metadata Filtering form & controls –Help menu –Hint for no results Improvements for intuitive interface –Initial engagement –Metadata Filtering form & controls –Help menu –Hint for no results

Summary Collection understanding shifts the traditional focus of image retrieval Inspire users to derive their own relationships by focusing on artifacts Collection insight increases Collection understanding shifts the traditional focus of image retrieval Inspire users to derive their own relationships by focusing on artifacts Collection insight increases

Acknowledgments Dr. Enrique Mallen, The On-Line Picasso Project The Humanities Informatics Initiative, Telecommunications and Informatics Task Force, Texas A&M University. Dr. Enrique Mallen, The On-Line Picasso Project The Humanities Informatics Initiative, Telecommunications and Informatics Task Force, Texas A&M University.