ILI2009: Exploiting Usage Data

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My short (~10min) presentation at ILI2009.

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  • 2009 value is predicted
  • 2009 value is predicted
  • ILI2009: Exploiting Usage Data

    1. 1. I Know What You Borrowed Last Summer Exploiting Usage Data in an Academic Library Dave Pattern Library Systems Manager University of Huddersfield, UK [email_address] www.daveyp.com
    2. 2. Preamble <ul><li>More information about this presentation… </li></ul><ul><ul><li>daveyp.com/ili2009/ </li></ul></ul><ul><li>Please remix and reuse these slides! </li></ul><ul><ul><li>creativecommons.org/licenses/by-nc-sa/3.0 </li></ul></ul><ul><li>Have you remembered to switch your phone on? </li></ul><ul><ul><li>please feel free take photos, record audio, live blog, tweet (@daveyp, #ili2009), etc </li></ul></ul>
    3. 3. University of Huddersfield Library <ul><li>Medium sized UK University </li></ul><ul><ul><li>20,000 students and 2,000 staff </li></ul></ul><ul><ul><li>Library holds over 240,000 books </li></ul></ul><ul><li>Current LMS/ILS Horizon installed in 1996 </li></ul><ul><ul><li>over 3 million borrowing (“circ”) transactions stored in the DB </li></ul></ul>
    4. 4. Suggestions based on circ data “people who borrowed this…”
    5. 5. Borrowing profile average loans per month average number of book loans per month
    6. 6. Feature usage “people who borrowed this…” average number of clicks per month on “people who borrowed this” suggestions
    7. 7. Getting personal! suggestions for what to borrow next
    8. 8. Building better new book lists course specific RSS feeds
    9. 9. The impact on borrowing range of stock borrowed per year number of unique titles (bib#) borrowed per calendar year (2009 figure is predicted) ? borrowing suggestions added to catalogue at start of 2006
    10. 10. The impact on borrowing average number of books borrowed average number of books borrowed per active borrower per calendar year (2009 predicted)
    11. 11. Catalogue keyword searches keyword cloud eye candy…
    12. 12. Catalogue keyword searches guided searches
    13. 13. <ul><li>http://library.hud.ac.uk/usagedata/ </li></ul><ul><ul><li>prompted by the JISC Tile Project </li></ul></ul><ul><ul><li>aggregated usage data for 2 million circulation transactions, covering around 80,000 book titles </li></ul></ul><ul><ul><li>recommendation data for over 37,000 titles </li></ul></ul><ul><ul><li>simple XML format </li></ul></ul><ul><ul><li>Open Data Commons / CC0 licence </li></ul></ul>Library usage data release “if you love something, set it free…”
    14. 14. <ul><li>Data released on 12th Dec 2008… </li></ul><ul><li>… 2 days later, Patrick Murray-John at University of Mary Washington converts the data to RDF!  </li></ul><ul><ul><li>Patrick’s blog post at http://bit.ly/noJD </li></ul></ul><ul><ul><li>Talis podcast at http://bit.ly/z6yjF </li></ul></ul>Library usage data release “if you love something, set it free…”
    15. 15. Library usage data release “if you love something, set it free…”
    16. 18. JISC MOSAIC Project http://bit.ly/jiscmosaic
    17. 19. JISC MOSAIC Project developer competition
    18. 20. JISC MOSAIC Project developer competition
    19. 21. JISC MOSAIC Project developer competition
    20. 22. In summary… <ul><li>At Huddersfield, exploited usage data is helping to change borrowing habits </li></ul><ul><li>Are libraries prepared to let go of their data? </li></ul><ul><li>“Raw data now!” – Sir Tim Berners-Lee </li></ul><ul><ul><li>TED speech, March 2009 (http://bit.ly/q9sR) </li></ul></ul>
    21. 23. Final recommendations… <ul><li>Capture as much usage data as you can …even if you don’t have a use for it now! </li></ul><ul><li>Whenever possible, release aggregated or anonymised versions of the data </li></ul><ul><ul><li>try to use a Creative Commons Zero or Open Data Commons licence to encourage re-use </li></ul></ul><ul><ul><li>don’t be a “data hugger”!  </li></ul></ul>

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