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

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

MaxData Project “Maximizing Library Investments in Digital Collections Through Better Data Gathering and Analysis” Funded by Institute of Museum and Library Services (IMLS) 2005-2007 Carol Tenopir, PI

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

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

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

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

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?

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?

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

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?

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

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

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

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)

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)

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)

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

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

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

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

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…