1. METRIDOC: A Framework for Library Business Intelligence With the support of University of Pennsylvania Libraries

2. METRIDOC University of Pennsylvania Libraries Business intelligence starts with a basic abstraction: The Event

3. METRIDOC University of Pennsylvania Libraries xxx.xx.xxx.xxx|-|zucca|[26/Jul/2007:15:41:01 -0500]| GET https://proxy.library.upenn.edu:443/login?proxySessionID=10335905&url=ht tp://www.csa.com/htbin/dbrng.cgi?username=upenn3&access=upenn34&ca t=psycinfo&adv=1 HTTP/1.1| 302|0|http://www.library.upenn.edu/cgibin/res/sr.cgi?community=59| Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/418.9.1 (KHTML, like Gecko) Safari/419.3| NGpmb6dT6JXswQH|__utmc=94565761;ezproxy=NGpmb6dT6JXswQH; hp=/; proxySessionID=10335514; __utmc=247612227; __utmz=247612227.1184251774.1.1.utmccn=(direct)|utmcsr=(direct)|utmc md=(none);UPennLibrary=AAAAAUaWP5oAACa4AwOOAg==; sfx_session_id=s6A37A3E0-3B8E-11DC-80E985076F88F67F Viewing an Ejournal article. The Event as raw data

4. METRIDOC University of Pennsylvania Libraries User & Program Parameters College | Dept Rank Course Host College Host Dept Instructor Grant Spnsr Library Parameters Srvice Genre Cognzt Staff Orgn’l Unit Budget cntr Environmental Parameters Bibliographic Parameters Title URI Format Cost| Supplr Date | Time Location IP Domain URL EVENT An Event Abstracted

5. METRIDOC University of Pennsylvania Libraries Link resolver Proxy server COUNTER ILS (Voyager, I3, Kuali-OLE) Resource sharing system Web server Social networking Srvs. Spreadsheets, databases Other targets… The “Event” is represented in machine-readable data, stored in a plethora of business systems. E-Resource Use by service, demographic, package Expenditures & Inventory planning / reader interest data Supply chain data Discovery systems & content use Research & instructional data learning management Other events… Event TypesSource Target

6. Is a framework for : Extracting event data from systems Transforming those data into readable, normalized formats Loading transformed/normalized payload into a repository Supporting analysis through local and collaborative dissemination channels. MetriDoc METRIDOC University of Pennsylvania Libraries

7. Increased scope of sources Synthesis of vectors, e.g.  Expenditure per use  Resources use by communities Contextualized data with greater statistical dimension and descriptive power. Collaborative assessment. Improved Data Resolution Through Integration METRIDOC University of Pennsylvania Libraries

8. Our legacy system: Datafarm Perl cron Perl cron Perl cron Voyager Farmer Quaker App Logs

9. METRIDOC University of Pennsylvania Libraries Datafarm Shortcomings

10. METRIDOC University of Pennsylvania Libraries What we need

11. METRIDOC University of Pennsylvania Libraries Current System: Metridoc Perl cron Perl cron Perl cron Voyager Farmer Quaker App Logs

12. METRIDOC University of Pennsylvania Libraries Metridoc Philosophy

13. METRIDOC University of Pennsylvania Libraries Scripting Framework

14. METRIDOC University of Pennsylvania Libraries Scripting Example

15. METRIDOC University of Pennsylvania Libraries Scripting Example

16. METRIDOC University of Pennsylvania Libraries Exposing data

17. METRIDOC University of Pennsylvania Libraries Metrics on the cheap (google charts)

18. METRIDOC University of Pennsylvania Libraries Thoughts on complex statistics

19. METRIDOC University of Pennsylvania Libraries The future

20. METRIDOC University of Pennsylvania Libraries Abstracts 4 key functions, exposes interfaces for interoperability Target Source, e.g. Relais, Illiad, ILS Ingest Log Parse Format Refined output 1. Extract Resolution Sources e.g. IdM, WorldCat Refined output Resolve Codes & IDs Normalize 2. Transform Query Srvc Data Repo 3. Load User Interface Local Data Stores Results Document Query Document 4. Query

21. METRIDOC University of Pennsylvania Libraries Partners are welcome Sponsor More at http://code.google.com/p/metridoc/