what can be learned from usage data
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What Can Be Learned From Usage Data. Lynn Silipigni Connaway Research Scientist Mark Bendig Systems Analyst ASIST 2003 Annual Conference October 22, 2003. What Can Be Learned. What is being accessed Subject areas Types of content Publishers of content Depth of access Perusing - PowerPoint PPT PresentationTRANSCRIPT
OCLC Online Computer Library Center
What Can Be Learned From
Usage DataLynn Silipigni ConnawayResearch Scientist
Mark BendigSystems Analyst
ASIST 2003 Annual ConferenceOctober 22, 2003
What Can Be LearnedWhat Can Be LearnedWhat 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
Limitations of Usage DataLimitations 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
netLibrary Site ActivitynetLibrary 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
Books Viewed Per SessionBooks Viewed Per Session
Minimum Maximum Average
2/26/02 1 31 1.27
2/26/03 1 650 1.42
Pages Viewed Per BookPages Viewed Per Book
Minimum Maximum Average
2/26/02 1 594 13.41
2/26/03 3 722 13.61
Pages Viewed Per SessionPages Viewed Per Session
Minimum Maximum Average
2/26/02 7 594 17.15
2/26/03 1 1508 19.34
Data InterpretationData 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
Future ResearchFuture ResearchIdentify 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