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Summa/Search and Facets


 Digital Libraries à la Carte 2009
      Tilburg University, 2009-07-31




     Mads Villadsen <mv@statsbiblioteket.dk>
A Short History of
 Summa/Search
Why?


   Improve response times
   Greater flexibility to create a system that had end user
     concerns as a priority
   Expose all our resources through a single point of entry
   Combine IT knowledge with knowledge of library
     science
How

Integrated search
   Speed and meaningful ranking of material from

     different sources
Exploratory search
   Help users find what they are looking for – even if

     they don't quite know it themselves
Motivational design
   Show users the information they need when they

     need it
“Facets” – Limit Your
       Search




   Limit your search to certain material types
Facets – No Counts




  Proper facets. The facet counts came later.
Facets Today




Proper facet counts. Only the most useful facets are shown.
Facet Information


Current system at the State and University Library
   9.1 million records
   8.7 million unique tags in 15 facets
   Average number of tags/document is 10
   Large facets
     Subject: 3.5 million unique tags

     Author: 4.8 million unique tags
How Did It All Work Out?
Recent Usability Test:
              The Good

   The Google-like initiatives
     One simple search field

     Search suggestions

     Did-You-Mean

   The integration of extra information in the full records –
     especially covers and abstracts
   The Todo list
Recent Usability Test:
           What To Improve



   Users had trouble finding journal articles
   Many users failed to discover the facets
   Further tweaking of the relevancy ranking
   Simplification of the request procedure
What Now?
Simple Changes



   Rename “order list” to “basket”
   Make it possible to add any item to the Todo list
   Move facets to the left side
   ...
Search Tomorrow
More Data


User expectations: If they can't find it in Search, then we
                       don't have it.

      Particularly a problem with article level data.

Will make the experience as a whole better for the end
                        user.
Rethink Facet Presentation
Clustering


  Add clustering framework to facilitate automatic tag
                      extraction.

May link together articles, books, and data-sets that the
                user hadn't thought of.

      Should prove very useful with full text data.
Other


   Rights integration
   Duplicate reduction
   User specific ranking
   Further develop system and statistics tools
   Index look-ups
   And more...
Resources


   The hybrid library: from the users perspective
    http://www.statsbiblioteket.dk/om-statsbiblioteket/brugbarhed/feltstudier
   Summa Site
    http://statsbiblioteket.dk/summa/
   Search Usability Test
    http://www.statsbiblioteket.dk/summa/search%20-%20usability-test-English.pdf
   Code4lib 2009 presentation on Complete Faceting
    http://www.code4lib.org/conference/2009/eskildsen
Questions?

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Ticer - Search And Facets

  • 1. Summa/Search and Facets Digital Libraries à la Carte 2009 Tilburg University, 2009-07-31 Mads Villadsen <mv@statsbiblioteket.dk>
  • 2. A Short History of Summa/Search
  • 3. Why?  Improve response times  Greater flexibility to create a system that had end user concerns as a priority  Expose all our resources through a single point of entry  Combine IT knowledge with knowledge of library science
  • 4. How Integrated search  Speed and meaningful ranking of material from different sources Exploratory search  Help users find what they are looking for – even if they don't quite know it themselves Motivational design  Show users the information they need when they need it
  • 5. “Facets” – Limit Your Search Limit your search to certain material types
  • 6. Facets – No Counts Proper facets. The facet counts came later.
  • 7. Facets Today Proper facet counts. Only the most useful facets are shown.
  • 8. Facet Information Current system at the State and University Library  9.1 million records  8.7 million unique tags in 15 facets  Average number of tags/document is 10  Large facets  Subject: 3.5 million unique tags  Author: 4.8 million unique tags
  • 9. How Did It All Work Out?
  • 10. Recent Usability Test: The Good  The Google-like initiatives  One simple search field  Search suggestions  Did-You-Mean  The integration of extra information in the full records – especially covers and abstracts  The Todo list
  • 11. Recent Usability Test: What To Improve  Users had trouble finding journal articles  Many users failed to discover the facets  Further tweaking of the relevancy ranking  Simplification of the request procedure
  • 13. Simple Changes  Rename “order list” to “basket”  Make it possible to add any item to the Todo list  Move facets to the left side  ...
  • 15. More Data User expectations: If they can't find it in Search, then we don't have it. Particularly a problem with article level data. Will make the experience as a whole better for the end user.
  • 17. Clustering Add clustering framework to facilitate automatic tag extraction. May link together articles, books, and data-sets that the user hadn't thought of. Should prove very useful with full text data.
  • 18. Other  Rights integration  Duplicate reduction  User specific ranking  Further develop system and statistics tools  Index look-ups  And more...
  • 19. Resources  The hybrid library: from the users perspective http://www.statsbiblioteket.dk/om-statsbiblioteket/brugbarhed/feltstudier  Summa Site http://statsbiblioteket.dk/summa/  Search Usability Test http://www.statsbiblioteket.dk/summa/search%20-%20usability-test-English.pdf  Code4lib 2009 presentation on Complete Faceting http://www.code4lib.org/conference/2009/eskildsen