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Search and Rescue

Eighth Annual Reference Research Forum, American Library Association Annual Conference, Atlanta, June 16, 2002. Search and Rescue. Repair Strategies of Remote Users Searching the Online Catalog. Nancy B. Turner, Electronic Resources Librarian, Syracuse University

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Search and Rescue

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  1. Eighth Annual Reference Research Forum, American Library Association Annual Conference, Atlanta, June 16, 2002 Search and Rescue Repair Strategies of Remote Users Searching the Online Catalog Nancy B. Turner, Electronic Resources Librarian, Syracuse University Susan E. Beck, Head of Reference & Research Services, New Mexico State University

  2. Research Questions • Do users in remote locations repair searches? • What types of repair strategies do they employ? • How can this information inform our work as reference librarians?

  3. Transaction Logs • Traditional OPAC Logs • Web Server Logs • Appropriate Uses • Drawbacks

  4. User Population • Carnegie I—Research Extensive/ Hispanic Serving • 15,000 enrollment • Doctoral degrees in 5 colleges: Agriculture, Arts & Sciences, Business, Education, Engineering

  5. Physical Environment • Two library buildings: Branson & Zuhl • Two periodicals areas • Two reference desk areas • Two stack areas

  6. Endeavor catalog

  7. Search Screen

  8. Methodology: Data collection • Apache server log extraction • 7 two hour intervals over 3 month period • Various times: am, pm, weekends • Created Library IP address map • Charted search locations by IP address: • Campus (NMSU domain) • Off campus (non-NMSU domain) • Staff • Zuhl & Branson public service areas

  9. Methodology: Data treatment I • Text files imported to spreadsheet • Imported three columns only • IP address, Date/Time, Search Query • Mapped IP’s to library locations • Selected only unmediated, remote locations to review • Divided spreadsheet into 3 worksheets • All, Unmediated, Staff

  10. Methodology: Data Treatment II Search_Code = TALL replaced with Search=Title Search_Code = JALL replaced with Search=Journal Title Search_Code = FT*& replaced with Search=Keyword Search_Code=NAME replaced with Search=Author Search_Code=SUBJECT replaced with Search=Subject Search_Code=CALL replaced with Search=Call Number %2B = replaced with + %3F = replaced with ? %3A = replaced with : %2C= replaced with , %27 = replaced with ‘ %22 = replaced with “

  11. Cgi search syntax translation 1. GETSearch_Arg=tankers+full+of+trouble&Search_ Code=TALL&PID=19913&SEQ=20020314130448&CNT=25&HIST=1&SEARCH_FROM_TITLES_PAGE 2. GETSearch_Arg=tankers full of trouble &Search=TITLE &PID=19913&SEQ= 20020314130448&CNT=25&HIST=1&SEARCH_FROM_ TITLES_PAGE User searching for the title, “Tankers full of trouble” from the Titles display listing page

  12. Search query translation

  13. Methodololgy: Data Treatment III • Selected “searches” based on syntax GETSearch_Arg= • Coded searches by search type JT, T, S, A, CN, B, K, C • Tallied searches by type & area

  14. March 14 Tallies

  15. Excerpt from search log GETSearch_Arg=new mexico litter controll&Search=Keyword GETv1=1&ti=1,1&Search_Arg=new mexico litter controll&Search=Keyword GETti=21,0&Search_Arg=new mexico litter controll&Search=Keyword GETPAGE=sbSearch GETSearch_Arg=new mexico litter&Search=Keyword GETti=11,0&Search_Arg=new mexico litter&Search=Keyword GETti=21,0&Search_Arg=new mexico litter&Search=Keyword GETti=31,0&Search_Arg=new mexico litter&Search=Keyword GETSearch_Arg=texas litter&Search=Keyword GETSearch_Arg=texas litter laws&Search=Keyword GETSearch_Arg= litter laws&Search=Keyword

  16. Data Analysis • After coding all discrete searches, we then re-coded those searches based on repair types.

  17. Search Repair Levels • Word Repairs occur at word level • ConceptRepairs involve the concept(s) searched. A concept is typically multi-word or a phrase. It can be multi-concept • Search Repairs show knowledge of search types or knowledge of formatting within search types

  18. Word Level Repairs

  19. Word Level Example • GETSearch_Arg=bertrand russel& Search=Keyword • GETSearch_Arg=bertrand russell& Search=Keyword • GET Search_Arg=raceism in unimployment &Search=Keyword & • GET Search_Arg=racism in imployment &Search=Keyword

  20. Concept Level Repairs

  21. Concept Level Example • GETSearch_Arg=Patton&Search=Keyword • GETSearch_Arg=General Georgo Patton &Search =Keyword (CN) • GETSearch_Arg=Leadership&Search=Subject (CC) • GETSearch_Arg=Military Leadership& Search =Subject (CN, ST • GETSearch_Arg=General Patton leadership& Search=Subject (CN) • GETSearch_Arg=George Patton leadership& Search=Subject (CR) • GETSearch_Arg=Leadership style of George Patton& Search=Subject (CR, CN)

  22. Search Level Repairs

  23. Search Level Example I • GET Search_Arg=child abuse laws&Search=Keyword • GET Search_Arg=child abuse laws& Search=Subject • GET Search_Arg=Troy Boone&Search=Author • GET Search_Arg=Boone, Troy&Search=Author • GET Search_Arg=A Doll House&Search=Title • GET Search_Arg=Doll House&Search=Title

  24. Search Level Example II • GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Keyword • GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Subject • GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Title …2 minutes pass… • GET Search_Arg=History of Babylonian Mathematics&Search=Title • GET Search_Arg=History of Babylonian Mathematics&Search=Journal Title • GET Search_Arg=History of Babylonian Mathematics&Search=Subject • GET Search_Arg=History of Babylonian Mathematics& Search= Keyword

  25. Preliminary findings: Search types • Although no specific search type emerges as an obvious favorite Keyword 28% Jrnl Title 15% Subject 19% Author 10% Title 16% Boolean 9% Call # 3% • 44% of all searches are for known items(title, journal title, author & call number)

  26. Preliminary findings: Word level repairs

  27. Preliminary findings: Concept level repairs

  28. Preliminary findings: Search level repairs

  29. Preliminary findings: Overall repairs

  30. Preliminary findings • Over 50% catalog uses are non-staff • Unassisted user searches.…………….56% • Staff/Mediated user searches………..44% • Higher incidence of concept level repairs than word and search level • Preferred repair strategy is to switch search types • High incidence of retyping exact search

  31. Further study • Extend data collection time periods • Increase # of data collection sessions • Include different user population • Extend analysis to include • Length of time spent repairing search • Search types leading to more repairs • Number of repairs made per search

  32. Questions? For more information, contact: Nancy B. Turner at nbturner@library.syr.edu Susan E. Beck at susabeck@lib.nmsu.edu

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