Download logs.library.cornell.edu

Example of a bibliomining system:
logs.library.cornell.edu
Adam Chandler
Data Discussion on Library Data
Cornell University Library
June 1, 2012
What is it?
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Live demo 1
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That’s it? Why bother?
Just use Google Analytics
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Why not Google Analytics?
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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
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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. In order to make it more conducive for those
concerned with data mining in a library setting to locate other
works and other researchers, the term 'bibliomining' was
created. The term pays homage to bibliometrics, which is the
science of pattern discovery in scientific communication.”
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“Bibliomining is the application of statistical and patternrecognition tools to large amounts of data associated with
library systems in order to aid decision-making or justify
services.”
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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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“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.”
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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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Live demo 2
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Who uses it and for what?
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How do I get help?
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How do I get help?
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https://confluence.cornell.edu/display/culweblogstool/
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Credits
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Credits
System design
Software
User interface
Adam Chandler and Pete Hoyt
Pete Hoyt
Adam Chandler and Nancy Solla
Documentation
Adam Chandler, Glen Wiley,
Nancy Solla
Linda Miller and Assessment, Pete
Magnus and Desktop Services
In-library IP address
lookup tables
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logs.library.cornell.edu