Big Brother in the library

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Big Brotherin the library

• Dave Pattern, Library Systems ManagerUniversity
  of Huddersfield
• d.c.pattern_at_hud.ac.uk

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Preamble

• Presentation available at
• www.slideshare.net/daveyp/
• Please remix and reuse this presentation
• creativecommons.org/licenses/by-nc-sa/3.0

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Contents

• Supermarkets
• Virtual footprints
• Data collected at Huddersfield
• Using data analysis to improve services
• Sharing data

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A long, longtime ago
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www.flickr.com/photos/hippie/2476662922/
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tinyurl.com/c8qm8h
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www.guardian.co.uk/money/2005/sep/27/ethicalmoney.
lifeandhealth
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www.timesonline.co.uk/tol/news/uk/article1572626.e
ce
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www.flickr.com/photos/jay-chilli/2178457837/
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in a digital world, we leave virtual footprints
wherever we go
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University ofHuddersfield
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Facts and figures

• Student population
• about 20,000 (full-time and part-time)
• University Library
• just under 400,000 physical items
• over 700,000 loans per year

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User data collected by the library

• Turnstile System
• when you entered the library
• Books
• which items you borrowed and when
• Computers
• which PCs/Macs you used and for how long
• which web sites you looked at

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Anonymous data collected

• Library Catalogue web site
• keywords used for searches and the number of
  results found
• which books were looked at
• which features and tools were used

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What the data is used for

• Library Catalogue web site
• improving the search facility
• analysing search trends
• Turnstile System
• find out how well the library is being used (e.g.
  weekends and holidays)
• has the refurbishment of the library made any
  difference to the number of people using the
  library?

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What the data is used for

• Books
• which books do we need extra copies of?
• which books can we get rid of?
• which books are being borrowed by specific groups
  of students?
• create borrowing suggestions for students in the
  Library Catalogue web site

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library non-usageanalysis
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Library Catalogueweb site
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Keyword cloud
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Keyword suggestions
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Borrowing suggestions
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Personalised suggestions
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how is it done?
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1) find out whos borrowed the book
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2) find all the other books they borrowed
Alice
Cathy
Brian
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3) find the common titles
Alice
Cathy
Brian
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• people who borrowed
• also borrowed

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so, was it worth it?
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Range of stock being borrowed
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Books per active borrower
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sharing usage data
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Usage data

• Nov 2008 Released of aggregated and anonymised
  book usage data and book recommendation data
  (link)
• 2 million book loans and 80,000 book titles
• Apr 2009 Aggregated keyword search data and
  linked keywords (link)
• 3 million searches on the library catalogue
• Open Data Commons Licence
• no restrictions on how the data can be used

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what next?
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What if

• every library shared its usage data?
• could we use that data to improve the student
  experience?
• can we encourage people to play with that data
  and create cool stuff?

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Thank you!
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