1. Empowering Data: Persuasion Through Presentation
E-Resource Usage Data for
Decision Making and More
Maribeth Manoff
University of Tennessee Libraries
ACRL EBSS Program
June 23, 2007

2. Outline MaxData Project UT Libraries and E-Resource Usage Data
What data do we have available?
What questions do we want to answer?
Which data do we use to answer our questions?
Next Steps
Survey of librarians
Gathering a variety of data sets and views

3. MaxData Project
“Maximizing Library Investments in Digital Collections Through Better Data Gathering and Analysis”
Funded by Institute of Museum and Library Services (IMLS)
Carol Tenopir, PI

4. MaxData Project Purpose
Evaluate and compare methods of usage data collection and analysis
Develop cost/benefit model to help librarians select appropriate method(s) for electronic resource usage assessments

5. MaxData Project Teams
Carol Tenopir and Donald King: readership surveys at UT and four Ohio Universities
David Nicholas et al. (Ciber): deep log analysis on OhioLINK journal usage data
UT Libraries: COUNTER data from vendors, data from several local systems
Gayle Baker, Electronic Services Coordinator
Eleanor Read, Data Services Librarian
Maribeth Manoff, Systems Librarian

6. UT Libraries – What Data Do We Have Available?
Database or Package Level
“Hits” recorded from database menu pages
COUNTER reports from vendors (e.g. Database Report 1: Total Searches and Sessions by Month and Database)
Federated search system (MetaLib) statistics
Totals from journal-level data

7. UT Libraries – What Data Do We Have Available?
Journal Level
COUNTER reports from vendors (e.g. Journal Report 1: Number of Successful Full-Text Article Requests by Month and Journal)
Link resolver (SFX) statistics (e.g. Report 10: Requests and Clickthroughs by Journal and Target)
Some libraries using proxy server logs

8. UT Libraries – What Questions Do We Want to Answer?
We want insights into user behavior
Which databases and e-journals are they using?
Which are they not using?
How are they navigating to full-text?

9. UT Libraries – What Questions Do We Want to Answer?
We want to make collection management decisions and improve access
Does e-resource usage justify money spent?
Which of our e-subscriptions do we need to keep?
Are there new e-titles we need to obtain?
Are there low use titles that would benefit from PR efforts?
Are there access points that could be added or improved?

10. UT Libraries – Which Data Do We Use?
The good news and the bad news - all the data we’ve looked at thus far has potential.
Next steps in determining costs and benefits for the model:
Survey of librarians who collect and work with usage data from vendors
Gathering a variety of data sets and views for analysis and presentation

11. Next Steps – Survey Purpose
How much effort is involved in working with vendor-supplied use data?
How are the data used?
What data are most useful in managing electronic resources?

12. Next Steps – Survey Subjects
Sent to Library Directors at 284 Carnegie/ARL research institutions
Forwarded to the librarian who collects and works with usage data from vendors
April 2006
92 respondents

13. Next Steps – Survey Results
Purpose for reviewing and/or analyzing vendor data
Subscription decisions (94%)
Justify expenditures (86%)
Reporting (61%)
Other (28%)

14. Next Steps – Survey Results
“Other” purposes for reviewing and/or analyzing vendor data
Collection management
Cost/use
Cancellation decisions
Change to electronic-only
Promotion / marketing / training for lower use e-resources
Administrative
Strategic planning / budget
Curiosity

15. Next Steps – Survey Results
Most Useful Statistics
Number of full-text downloads (67)
Number of searches (41)
Number of sessions (27)
COUNTER statistics (26)
Number of turnaways (17)
Other (17)

16. Next Steps – Survey Results
Combining data for added value
Combine vendor stats (36)
Combine / compare with other use data gathered electronically (SFX, web logs, consortia reports) (17)
Cost per use (12)
Fund code/subject (5)
Other (12)

17. Next Steps – Data Gathering and Analysis
Since 1999, homegrown system to record “hits” to web page database links
Subscription management
Number of simultaneous users
Pattern of use of a database over time
Continuation decisions
Cost per request
Services management
Use patterns by day, week or semester
Location of users (campus, off-campus, wireless)

18. Next Steps – Data Gathering and Analysis
Totals from COUNTER vendor reports for reporting to ARL (Supplementary Statistics)
Number of sessions (logins) to databases or services
Number of searches (queries) in databases or services
Number of successful full-text article requests

19. Next Steps – Data Gathering and Analysis
Journal level analysis for MaxData project
Spreadsheet combining JR1 Reports for 30+ vendors
Using Sep-Nov 2005 time period to correspond with MaxData readership surveys
Interest in high use titles, also low or zero use
Calculate % of titles accounting for 80% of full-text downloads

20. Next Steps – Data Gathering and Analysis
In order for journal level data to be useful to collection managers, we need a way to present data by subject area
Subject categories from link resolver (SFX), mapped to local subjects and added to combined JR1 spreadsheet

21. Next Steps – Data Gathering and Analysis
Data from SFX statistical module to complement and supplement vendor data
Elements from SFX report correspond to COUNTER JR1 report:
ISSN, Title, SFX Target – JR1 Platform
SFX Clickthrough – JR1 Full Text Download
Look at these two numbers alongside each other to see a fuller picture of use
Compare trends and patterns
See data not in JR1 reports, e.g., non-COUNTER packages, open access journals, backfiles

22. Empowering Data An Iterative Process
Ask questions
Envision the data possibilities
Gather data sets and views
Have we answered our questions?
Ask more questions, envision more possibilities, gather more data…