Download logs.library.cornell.edu

There are interesting reports in the
CUL bibliomining system
(logs.library.cornell.edu)
Adam Chandler
Electronic Resources User Experience Librarian
Library Technical Services
CUL Reference & Outreach Forum
Cornell University Library
October 9, 2012
http://logs.library.cornell.edu
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What is it?
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Why bother?
Just use Google Analytics
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Why not Google Analytics?
Because logs.library.cornell.edu …
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Uses Cornell single sign for security and convenience
gives us the freedom to export and use the data anyway we want for
our special reporting needs
requires no changes to our websites. Google Analytics requires a section
of Javascript code that sends information about each request to Google
where it is recorded. Repeated privacy violations from commercial sites
such as Facebook are driving some users towards widgets such as
ghostery (http://news.ghostery.com/) that block javascript based web
tracking.
our flexible design allows us to store logs which cannot easily be tracked
with javascript: examples: PURL, checkip, flickr
Patron Privacy
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'bibliomining'
Nicholson, S. (2003) The Bibliomining Process: Data
Warehousing and Data Mining for Library Decision-Making.
Information Technology and Libraries 22 (4)
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“The term 'bibliomining' was first used by Nicholson and
Stanton (2003) in discussing data mining for libraries. In the
research literature, most works that contain the terms 'library'
and 'data mining' are not talking about traditional library data,
but rather using library in the context of software libraries, as
data mining is the application of techniques from a large library
of tools… The term pays homage to bibliometrics, which is the
science of pattern discovery in scientific communication.”
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“The bibliomining process consists of
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determining areas of focus;
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identifying internal and external data sources;
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collecting, cleaning, and anonymizing the data
into a data warehouse;
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selecting appropriate analysis tools;
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discovery of patterns through data mining and
creation of reports with traditional analytical tools;
and
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analyzing and implementing the results.”
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Nicholson, S. (2003) The Bibliomining Process: Data Warehousing and Data Mining for
Library Decision-Making. Information Technology and Libraries 22 (4)
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Apache Log
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Apache Log
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CUL Logs IP Address Groups
CU (Weill)
CU (Qatar)
Ithaca not CU
CU Lib
(Public)
CU (Campus)
CU Lib
(Staff)
NY not Ithaca
USA not NY
Overseas
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E-usage Analysis Task Force
This group is called together for a 4 month project to survey
all existing data sources and questions they could answer by
themselves or in some combination about the use of CUL’s
digital services and electronic and print collections. The
nature of the work is a broad survey, rather than detailed
analysis of any one specific area. The priority of the group is
creating an inventory of electronic resource usage streams
(80% of effort), but print usage data should also be
summarized (20% of effort) so as to provide a comprehensive
picture across CUL.
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E-usage Analysis Task Force
The goal is to better equip CUL to assess our investment in eresources and e-services, such as :
• What does our data tell about disciplinary use, strengths
and weaknesses? (The ability to add demographic
understanding of the use of our resources)
• How do we tell we are making the right types of
investments in collections? (The ability to have cost per use
data on the title level for, e.g., collection development or
cancellation projects)
• How do we tell we are making the right types of investment
in digital services in support of electronic and other
resources?
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E-usage Analysis Task Force
The goal is to better equip CUL to assess our investment in eresources and e-services, such as :
• What does our data tell about disciplinary use, strengths
and weaknesses? (The ability to add demographic
understanding of the use of our resources)
• How do we tell we are making the right types of
investments in collections? (The ability to have cost per
use data on the title level for, e.g., collection
development or cancellation projects)
• How do we tell we are making the right types of investment
in digital services in support of electronic and other
resources?
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E-usage Analysis Task Force
The goal is to better equip CUL to assess our investment in eresources and e-services, such as :
• What does our data tell about disciplinary use, strengths
and weaknesses? (The ability to add demographic
understanding of the use of our resources)
• How do we tell we are making the right types of
investments in collections? (The ability to have cost per use
data on the title level for, e.g., collection development or
cancellation projects)
• How do we tell we are making the right types of
investment in digital services in support of electronic and
other resources?
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E-usage Analysis Task Force
Xin Li, Dean Krafft, and John Saylor will serve as sponsors and
resource to the team to support their work.
Membership:
• Adam Chandler (E-Resources User Experience Librarian –
Chair)
• Rich Entlich (Collection Development)
• Zsuzsa Koltay (Assessment & Communication)
• Mary Beth Martini-Lyons (IT and Usability)
• Liisa Mobley (LTS).
Report due January 31, 2013
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Some interesting reports from
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CUL’s DLXS digital collections
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Library website search boxes
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OpenURL Sources
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Licensed E-Resources via Checkip
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Huh?
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Huh?
“The process is cyclical in nature: as patterns are discovered,
more questions will be raised which will start the process again.
As additional areas of the library are explored, the data
warehouse will become more complete, which will make the
exploration of other issues
much easier.” – Scott Nicholson
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