1. PDA Profile Optimization at Liberty University Erin Crane, Ebooks Librarian ecrane@liberty.edu Lori Snyder, E-Resource Cataloging Librarian lbsnyder@liberty.edu

2. Liberty University Quick Facts Undergraduate and graduate programs offered through Liberty University, Liberty University School of Law, and Liberty Baptist Theological Seminary Founded 1971 Residential enrollment – 12,600; online enrollment – 80,000+ Library holdings ▫225,000 electronic books and media items ▫75,000 unique electronic full-text and print journals ▫341,000 physical items

3. Liberty University PDA Pilot program began in February 2010 with ebrary ▫Pilot ended in September 2010; transition to PDA product Initial load of 40,000+ PDA eligible MARC records. ▫Ongoing loads of various sizes have followed. PDA program evolution: ▫Collection Management PDA profile management ▫Acquisitions and Cataloging workflows

5. The Goals Meet the needs of the growing online population by expanding the ebrary PDA profile Expand ebrary PDA profile strategically by utilizing previous years of use data Create a reusable method for selecting new titles based on use data

6. The Formula Worked with Greg Smith, Director of Finance and Assessment Used 4 years of ebrary use data: Title Report and COUNTER Report Combined usage data into one spreadsheet in Access Focused on LC Class rounded to the nearest hundred as the data point for assessing and predicting use

7. The Formula continued Average COUNTER use for each year, average Page Views for each year, then average each title’s use for all years (weighting most recent year) Create percentile ranks for COUNTER average use and Page Views average use by title Average percentile ranks into one percentile rank by title Create pivot table which averages percentile ranks for titles in a given LC Class range The pivot table becomes the look up table for the formula which predicts use based on LC Class range

8. Here we averaged usage and created percentile ranks for each title.

9. Lookup table which was created through a pivot table

10. Results for Religion titles. Selection was mainly based on LC Class Broad Demand (rounded to the nearest 100)

11. The Load Further filtered by publication date and publisher 8970 records loaded into the catalog in September 2012 (print and ebook duplicates rejected by catalog) 11768 added to ebrary (including print and ebook duplicates) About half covered Social Science; the other half covered Religion, History, and Communication Studies

13. Cost

14. Titles

15. Prediction Accuracy

17. Continued Use

19. Conclusions The formula is not perfect (as shown by the trend in percentage of total triggered) However, the top percentile ranks do get triggered the most AND Formula driven titles receive more continued use than non-formula driven titles

20. Prediction Accuracy

21. Possible Future Steps Limit percentile rank lookup table to LC Classes with 5+ titles (would hopefully increase formula accuracy) Assess whether LC Class rounded to the hundreds was the most accurate predictor of use

22. Lookup table which was created through a pivot table

24. Cataloging Loading added titles ▫Normally search OCLC for best record  Easiest way to identify duplicate titles ▫Loads for this project were over 1,000 – downloaded records from ebrary partner portal and loaded using Voyager’s Webadmin  Saved time in terms of adding to the catalog but additional work to be completed in evaluating and managing rejected records

25. Cataloging (continued) Identification of owned/not owned titles ▫Upon load, statistical category of “PDA not yet owned” is added to the item record ▫When title is triggered, statistical category is changed to “PDA owned” ▫Allows for better reporting Maintenance of available titles ▫Delete records for titles on ebrary deleted titles list

26. Acquisitions Identification of fund codes (for profiles) in the ILS ledger ▫Allows for tracking of activity within each profile and by each subject area included in the program ▫Ease of reporting Non-itemized purchase orders in ILS ▫Time-saver – hundreds of triggered titles each week makes itemized purchase orders more time consuming ▫Prevents the creation of duplicate item records with In Process locations