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.edu2 3 4 Live demo 1 logs.library.cornell.edu5 Thats it? Why bother? Just use Google Analytics logs.library.cornell.edu6 7 Why not Google Analytics? logs.library.cornell.edu: 1.Uses Cornell single sign for security and convenience 2.gives us the freedom to export and use the data anyway we want for our special reporting needs 3.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.http://news.ghostery.com/ 4.our flexible design allows us to store logs which cannot easily be tracked with javascript: examples: PURL, checkip, flickr logs.library.cornell.edu8 'bibliomining' logs.library.cornell.edu9 Nicholson, S. (2003) The Bibliomining Process: Data Warehousing and Data Mining for Library Decision-Making. Information Technology and Libraries 22 (4) logs.library.cornell.edu10 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.edu11 logs.library.cornell.edu12 logs.library.cornell.edu13 Bibliomining is the application of statistical and pattern- recognition tools to large amounts of data associated with library systems in order to aid decision-making or justify services. logs.library.cornell.edu14 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.edu15 Nicholson, S. (2003) The Bibliomining Process: Data Warehousing and Data Mining for Library Decision-Making. Information Technology and Libraries 22 (4) logs.library.cornell.edu16 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. Apache Log logs.library.cornell.edu17 Apache Log logs.library.cornell.edu18 CU (Campus) logs.library.cornell.edu19 CU Lib (Staff) CU Lib (Public) CU (Weill) CU (Qatar) Ithaca not CU NY not Ithaca USA not NY Overseas CUL Logs IP Address Groups logs.library.cornell.edu20 Live demo 2 logs.library.cornell.edu21 WhoWho uses it and for what?what logs.library.cornell.edu22 How do I get help? logs.library.cornell.edu23 How do I get help? logs.library.cornell.edu24 https://confluence.cornell.edu/display/culweblogstool/ logs.library.cornell.edu25 Credits logs.library.cornell.edu26 Credits logs.library.cornell.edu27 System designAdam Chandler and Pete Hoyt SoftwarePete Hoyt User interfaceAdam Chandler and Nancy Solla DocumentationAdam Chandler, Glen Wiley, Nancy Solla In-library IP address lookup tables Linda Miller and Assessment, Pete Magnus and Desktop Services logs.library.cornell.edu