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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? logs.library.cornell.edu 2 logs.library.cornell.edu 3 logs.library.cornell.edu 4 Live demo 1 logs.library.cornell.edu 5 That’s it? Why bother? Just use Google Analytics logs.library.cornell.edu 6 logs.library.cornell.edu 7 Why not Google Analytics? logs.library.cornell.edu: 1. 2. 3. 4. 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 logs.library.cornell.edu 8 'bibliomining' Nicholson, S. (2003) The Bibliomining Process: Data Warehousing and Data Mining for Library Decision-Making. Information Technology and Libraries 22 (4) logs.library.cornell.edu 9 “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.” logs.library.cornell.edu 10 logs.library.cornell.edu 11 logs.library.cornell.edu 12 “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.” logs.library.cornell.edu 13 “The bibliomining process consists of · determining areas of focus; · identifying internal and external data sources; · collecting, cleaning, and anonymizing the data into a data warehouse; · selecting appropriate analysis tools; · discovery of patterns through data mining and creation of reports with traditional analytical tools; and · analyzing and implementing the results.” logs.library.cornell.edu 14 Nicholson, S. (2003) The Bibliomining Process: Data Warehousing and Data Mining for Library Decision-Making. Information Technology and Libraries 22 (4) logs.library.cornell.edu 15 “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.” logs.library.cornell.edu 16 Apache Log logs.library.cornell.edu 17 Apache Log logs.library.cornell.edu 18 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 logs.library.cornell.edu 19 logs.library.cornell.edu 20 Live demo 2 logs.library.cornell.edu 21 Who uses it and for what? logs.library.cornell.edu 22 How do I get help? logs.library.cornell.edu 23 How do I get help? logs.library.cornell.edu 24 https://confluence.cornell.edu/display/culweblogstool/ logs.library.cornell.edu 25 Credits logs.library.cornell.edu 26 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 logs.library.cornell.edu 27 logs.library.cornell.edu