Maximizing Library Investments in Digital Collections Through Better Data Gathering and Analysis (MaxData) Carol Tenopir and Donald W. King

Description of MaxData Funded by IMLS University of Tennessee, OhioLink and Ohio Libraries, University College London CIBER (Centre for Information Behaviour and the Evaluation of Research) Comparing and building a cost model for data collection methods (transaction logs and surveys)

Study Objectives To compare what different methods of data collection can tell you To develop a model that compares costs and effort to the library of collecting and analyzing data from various methods with the benefits of the information you obtain

Study Methods Ciber deep log analysis –OhioLink –5 Ohio Universities –Elsewhere User Surveys –5 Ohio Universities –University of Tennessee –Elsewhere Other log data from vendors (COUNTER- compliant, proxy servers, link resolvers, etc.) Costs and effort of methods

Why do libraries gather usage data? 1.To make decisions and rethink old ones 2.To demonstrate the value of the library’s collections and services 3.To improve services and collections 4.To find their place in comparative rankings 5.Because they are required to

Internally collected or added data can be used to show: Comparative amounts of use for databases Relative uses per size of user population within subject areas Cost per use Where users access the digital library

Ciber Highlights 50% of journals account for 93% of use, but 99% of titles were used at least once in a 7-month test period Health sciences titles are used more than any others OhioLink users choose to download a full article 3 times more often than view just an abstract Half of all sessions viewed an article; average was 2 articles per session Users who searched (rather than using the alpha or subject lists) tended to view more articles and viewed more older articles

Usage logs give much useful data, but… Logs don’t show why or outcomes Requests or downloads may not equal use or satisfaction Log sessions may be difficult to differentiate or compare across systems For privacy or other reasons, logs do not show behavior by demographic groups Logs show only a fraction of total use

Our surveys: Have been used since 1970s Include over 30,000 responses Provide trends since 1977 University surveys include: –2 national surveys of scientists (1977, 1984) –Astronomers and pediatricians who belong to their main professional societies (2003, 2004) –3 University of Tenn. Surveys (1993, 2001, 2003) –Drexel University (2002) –University of Pittsburgh (2003) –2 Australian universities ( )

Our Surveys are Designed to: Provide a complete picture of information seeking and reading patterns and how libraries contribute to overall information needs Distinguish: –Sources of articles read –How articles are identified/found –Time and depth of reading –Age of articles read –Format of articles read –Outcomes from reading –Value of reading from library and elsewhere

Our Surveys Establish Factors that Affect Reader Choices: Ease of use Time required to use Awareness of alternative sources Attributes of alternative sources Purposes of use

“Last Reading” is a variation of the Critical Incident Technique that: Permits observation of any combination of: –Sources of articles read –Means of identification –Time spend reading –Age of articles read –Format of articles read –Outcomes and value of reading Provides comparison: –Over time –Among disciplines –By age, sex/gender –Other types of users

Examples of Observations Over Time (1977 to 2004) Medical faculty read most articles (3 times more than humanities or engineers) Personal subscriptions and readings from them continue to go down Total amount of reading continues to go up Readings from libraries continue to go up and are more valuable to purpose and are more often for research Both print and electronic sources are used

Average Reading per Faculty member

Average Articles Read per year per University Scientist Average number of articles read per scientist Year of Studies

Source of Additional Readings

Academic Library Collections Source for Increased Readings 66 increased total readings; 64 from library collections When identified from searches, citations, etc., articles must be located and obtained Libraries the logical choice for faculty and students

Factors Leading to this Phenomenon: Number of personal subscriptions decreased (on average from nearly 6 to under 2; university scientists in U.S. from 4.2 to 3.5) Number of articles identified by searching increased (3 to about 50 articles per scientist) Breadth of journal reading increased, due in part to e-journal collections (13 to 23 journals from which at least one article read annually on average)

Critical (Last) Incident Method Can Show Usefulness and Value of Academic Library Collections Saves faculty time (15 min/reading) Library reading rated higher in importance (5.5 vs. 4.7 in 1-7 scale) Readers take more time reading library articles (39 vs. 33 minutes) Achievers read more and use library collections more than non-achievers Articles from libraries yield more favorable outcomes Articles from libraries help achieve greater productivity

1stYear 1st Year 2-5 Years Over 5Years Over 5 Years Older articles are judged more valuable & are more likely to come from libraries

What is Expected From You: Obtain any necessary Human Subjects Permission (or waivers) from your institution Review the questionnaire and make suggestions to fit your specific situation Decide whether your survey should be web or paper Send an or cover letter to your faculty and students describing the survey Post a link to the survey on your website if you wish Publicize to help response rates Help us identify your i.p. addresses (broadly) for usage logs if you can

What Is Expected From Us Obtain Human Subjects permission at UT (done) Design and test the questionnaire Receive responses at the UT secure server Analyze results Present survey results to each library Compare survey results with deep log analysis of OhioLink logs (with your name removed) in IMLS reports Show how the various user methods can be used together