Notes from NISO Forum

Below are some selected notes from the NISO Forum I attended 11/1/2007 – 11/2/2007. Overall, I enjoyed many of the presentations at the Forum. The ones talking about analyzing usage data peaked my interest the most as I’ve done some work of my own in this area while at Cortland but haven’t played with those things in a while. This is really something I want to get back into and with some changes at UH will likely have a chance to delve into some of this stuff soon. I was really interested in the work being done at Los Alamos National Labs by Johan Bollen and the work of John McDonald who recently moved to the Claremont Colleges. Johan showed some people R, a statistics program that is free and which he used on many of his large data sets. Definitely worth checking out.

Aggregation and Analysis of Usage Data: A Structural and Qualitative Perspective – Johan Bollen

What is important for raw item level usage data?

• Preserve event info
• Preserve sequence info
• Preserve document metadata

Important field for capturing individual accesses

• Event ID
• Referent ID
• User/session ID
• Date and time ID
• Request types

Implications

• Sequence
• Privacy
• Request Types

See the relationships between documents and resources – helpful for Web 2.0 social network analysis and social modeling

Barabasi (2003) Linked.

OpenURL ContextObject to represent usage data

OAI-PMH – Aggregation framework

Usage Data: An aggregator Perspective – John Law

When is a search a search?

• RSS
• Email Alerts
• “Searches” that include multiple databases
• Topic browse?
• Thesaurus lookup?

Variations in exposure

• E-resources page design and navigation
• A-Z list of databases vs. placement on the main page
• Database-specific links vs. platform links
  • meaningful labels for discipline specific databases
• Subject or course-specific library pages
• Learning management system integration

Federated search effect

• databases included vs. those excluded
• Changes in placement of/prominence of federated search box
• Z39.50 interface vs. XML gateway (SRU/SRW)

SUSHI

• Amplifies need for refining metrics in usage standards to increased consistency
• Makes it easier to aggregate data (in potentially bad ways)

Take heart…

• “The measures that have typically been employed to gauge library use are in question and no widely recognized substitute has appeared.”
  • Danny Wallace – Journal of Academic Librarianship Sept 2007
• “While counting of electronic uses has reached a stage of youthful maturity, an understanding of what these rounts mean in the language of resource allocation is arguably in its infancy”
  • Charles Martell – Sept 2007 College and Research Libraries Sept 2007

Usage Statistics & Information Behaviors: Understanding User Behavior with Quantitative Indicators – John McDonald

What we should do:
Understand usage behaviors
Understand our impact on our users
Guide our decision-making processes

David Ellis – Information Usage Behaviors

• Starting
• Browsing
• Accessing
• Chaining
• Differentiating
• Extracting
• Verifying
• Networking
• Monitoring
• Managing
• Manipulating *
• Teaching *
• Ending

* added by McDonald

OpenURL resolvers have methods that match these behavior

• Accessing
• Chaining and Differentiating
• Managing and Editing
• Browsing, Chaining, Accessing

How do we observe and measure?

• Pose a Question
• Develop a Theory
• Test a Theory

Interesting data on the how the implementation of federated search and/or OpenURL resolver changed usage statistics

Investigating virtual vertical files and vertial syllabus really interesting problem – McDonald did this by looking at use of content created by local authors (ie articles by professors at the university). This has increased.

• personally I’d do this with referrers

Service Related Behaviors

• Order Articles via Document Delivery
• See References for this Article
• Search the Library catalog
• Read Abstract
• Search Article Title on the Web
• Send Feedback to the Library
• See Articles citing this Article

What else could we be studying

• Monitoring – e-alerts, saved searches
• Networking – email citation to a colleague or another student
• Extracting – passing bibliographic information to another database search
• Analyzing -

Non-use is use
the idea that you discover that you don’t want to use an given article or journal

How do we get at non-use?

• article is accessed but not cited?
• see an information trail dying?