ER&L 2010: We’ve Got Data – Now What Do We Do With It? Applying Standards to Assess Information Resources

Speakers: Mary Feeney, Ping Situ, and Jim Martin

They had a budget cut (surprise surprise), so they had to asses what to cut using the data they had. Complicating this was a change in organizational structure. In addition, they adopted the BYU project management model. Also, they had to sort out a common approach to assessment across all of the disciplines/resources.

They used their ILLs to gather stats about print resource use. They hired Scholarly Stats to gather their online resource stats, and for publishers/vendors not in Scholarly Stats, they gathered data directly from the vendors/publishers. Their process involved creating spreadsheets of resources by type, and then divided up the work of filling in the info. Potential cancellations were then provided to interested parties for feedback.

Quality standards:

  • 60% of monographs need to show at least one use in the last four years – this was used to apply cuts to the firm orders book budget, which impacts the flexibility for making one-time purchases with remaining funds and the book money was shifted to serial/subscription lines
  • 95% of individual journal titles need to show use in the last three years (both in-house and full-text downloads) – LJUR data was used to add to the data collected about print titles
  • dual format subscriptions required a hybrid approach, and they compared the costs with the online-only model – one might think that switching to online only would be a no-brainer, but licensing issues complicate the matter
  • cost per use of ejournal packages will not exceed twice the cost of ILL articles

One problem with their approach was with the existing procedures that resulted in not capturing data about all print journals. They also need to include local document delivery requests in future analysis. They need to better integrate the assessment of the use of materials in aggregator databases, particularly since users are inherently lazy and will go the easiest route to the content.

Aggregator databases are difficult to compare, and often the ISSN lists are incomplete. And, it’s difficult to compare based on title by title holdings coverage. It’s useful for long-term use comparison, but not this immediate project. Other problems with aggregator databases include duplication, embargos, and completeness of coverage of a title. They used SerSol’s overlap analysis tool to get an idea of duplication. It’s a time-consuming project, so they don’t plan to continue with it for all of their resources.

What if you don’t have any data or the data you have doesn’t have a quality standard? They relied on subject specialists and other members of the campus to assess the value of those resources.