1. OCLC Online Computer Library Center What Can Be Learned From Usage Data Lynn Silipigni Connaway Research Scientist Mark Bendig Systems Analyst ASIST 2003 Annual Conference October 22, 2003

2. What Can Be Learned What is being accessed –Subject areas –Types of content –Publishers of content Depth of access –Perusing –In-depth reading –Number of items accessed –Number of screens/pages accessed Patterns of access –When accessed –Length of use/activity –Movements within the site and the text System and interface design

3. Limitations of Usage Data Do not know –Who the users are Usually cannot associate user demographics with usage patterns –Where they get access to the resources –How they use resources –Why they use resources Massive amounts of data to manipulate

4. netLibrary Subject Areas

5. Accesses by ARL Libraries

6. Accesses by Academic Libraries

7. Accesses by Public Libraries

8. Accesses by Special Libraries

9. Accesses by Federal Libraries

10. Accesses by School Libraries

11. netLibrary Site Activity Unique Users –Tues., 2/26/02 = 3796 –Wed., 2/26/03 = 8789 Total Sessions –Tues., 2/26/02 = 3989 –Wed., 2/26/03 = 9458

12. netLibrary Session Durations

13. netLibrary Login Times

14. Books Viewed Per Session

15. MinimumMaximumAverage 2/26/021311.27 2/26/0316501.42

16. Pages Viewed Per Book

17. MinimumMaximumAverage 2/26/02159413.41 2/26/03372213.61

18. Pages Viewed Per Session

19. MinimumMaximumAverage 2/26/02759417.15 2/26/031150819.34

20. Data Interpretation Increase in number of users Increase in duration of sessions Little difference in –Books viewed per session –Pages viewed per session –Pages viewed per book Peak usage times correlate with time most libraries are open and available –Need to distinguish differences in time zones

21. Future Research Identify the whys and hows of user satisficing of information needs –Online survey –Focus group interviews –Structured field observations –Structured interviews Continue to collect, analyze, and compare transaction log data –Users geographical location –Identify books per unique user –Correlate data sets

22. OCLC Online Computer Library Center Questions and Discussion connawal@oclc.org