Usage statistics for eresources: University of Notre Dame's Statistics Philosophy - Benjamin Heet
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Benjamin Heet discusses the challenges of collecting and interpreting library usage statistics at the University of Notre Dame, highlighting the inefficiencies in current data collection methods. He advocates for the development of a more streamlined database to improve accessibility and reporting while addressing the pitfalls of questionable data. The presentation also emphasizes the importance of training staff to manage statistics independently and enhance the overall understanding of usage metrics.
Usage statistics for eresources: University of Notre Dame's Statistics Philosophy - Benjamin Heet
- 1. University of Notre Dame’s Statistics Philosophy Benjamin Heet ER&L 2010 University of Notre Dame
- 2. Whatever shall we collect? • JR1 fulltext downloads (of course) • Impact factor • Eigenfactor • SFX Statistics (there’s a bunch) Can you make questionable numbers meaningful by adding even more questionable numbers? ER&L 2010
- 3. Who has the time? • I guess it’s my job » eJournal guy since 2000 » Download JR1 every month (50 platforms) • Save as a whole bunch of spreadsheets, made accessible on an ugly website • Around 20% of my time (yes that’s way too much!) » There has to be a better way to do this, right? ER&L 2010
- 4. A better way • Need a database for ease of access and reporting » Pay someone else » Build our own • What is important to us? » Less time gathering stats » Find out what the numbers mean ER&L 2010
- 5. What do these numbers mean? • Avoiding junk in, junk out » HTML vs PDF • Springer vs ScienceDirect » Outliers • Use spikes, fair or personal archiving » General bad data • Missing/incorrect issn • Duplicate data on same report ER&L 2010
- 6. What now? • CORAL Usage Statistics » Less time, all logins in single location • Train someone else to gather reports » Download every quarter • How often do folks need new numbers anyway? » Better reporting • Collection managers can gather on their own » Filtering out questionable data (outliers) ER&L 2010
- 7. Statistics Philosophy • Stats and nothing but the stats » JR1 only • Interpretation » What do the numbers mean? » Can we clean them in any way? • Functionality » Allow collection librarians greater access to reports ER&L 2010
- 8. About me! • Benjamin Heet » Senior Technical Consultant/Analyst » [email protected] » 574-631-4329 ER&L 2010