These recommendations are extracted from the Collection Analysis Task Force: CATF Final Report.

From the Executive Summary: Responsible collection stewardship includes regular assessment of collection resources. This assessment should include, at a minimum, data from the following: academics & enrollment, acquisitions, circulation, interlibrary loan, and usage statistics. Collections-related data are currently collected in the UMass Amherst Libraries through various avenues and made available through Tableau software and other sources. However, there are no guidelines on how these data are used in decision making. This report will provide details of available data sources and make recommendations on how data can be used to inform collections decisions.


A through J will be reviewed for implementation by the Assessment Librarian in conjunction with IRM.

A. Expand the use of Tableau for data informed collections assessment activities to enable ease of use by selectors and other Library staff. Develop content focused dashboards for selectors that include: purchasing, overlap, circulation, ILL, reserves, MINES, COUNTER, and LibQUAL data. Work with selectors to ensure that Tableau views meet their assessment and analysis needs.

B. Hire a Data Collections Analysis Librarian for the Discovery & Resource Management Systems (DRMS) unit to be responsible for extracting raw data from resource management systems, importing data into Tableau (or other visualization software), evaluating the integrity of the data, conducting data clean-up projects, and supporting data-informed collection assessment activities. This position would be the main point of contact for automating the gathering of vendor-supplied resource usage data. The focus of this position will be on collections data.

C. Hire a Data Analyst in the Assessment Unit to support data capture and use across the library. The Data Analyst would be responsible for capturing data from multiple sources across the Library and supporting use of data through various tools including Tableau. The focus of this position is library-wide, supporting assessment occurring in all library departments and reporting to the Assessment Librarian.

D. Provide regular training and information sessions about what data is available and how to use and access the data.

E. Use circulation data in combination with e-reserves, interlibrary loan and open-education resource data to determine which subject areas (call number ranges) are most frequently used. These could potentially inform the relevant selector(s) about the areas of more active student and faculty inquiry.

F. Use acquisitions purchasing data in combination with cataloging data and 5 Colleges overlap analysis to see which subject areas are being added to the collections both in our library and in other 5 Colleges libraries to assess how often newly acquired materials are being used. This data can be used to adjust spending to target areas that need more focus than others as well as areas that show changes in usage, allowing collections funds to be spent in a more mindful way.

G. Use LibQUAL, MINES, collection use, and demographic data to develop a deeper understanding of the users and non-users of library collections. This includes relevant analysis of user status, affiliation, purpose of use and format/type of resource.

H. Scholarly Communications, Reserves Staff and the Data Collections Analysis Librarian: Look at subject areas for content being added to ScholarWorks and tie Open Access initiatives and e-reserves data into collection assessment activities.

I. E-resource usage data is available from varied sources: vendor usage statistics, proxy server data, and MINES data. Use this information for subscription review and to identify areas of overlap and areas that are underrepresented in the collection. Establish regular e-resource reviews (every 3-5 years as able/needed) and engage key stakeholders across campus on a regular basis in e-resource reviews. See Appendix D.

J. Use all of the above data points to inform selector allocation fund spending.

K-O will be reviewed by Acquisitions staff for implementation.

K. Library Acquisitions should build systematic alerts for journal package renewals to make sure they provide notice far enough in advance to start the review process.

L. Develop a subscription review checklist, similar to that in Appendix C.

M. Test the CATF-developed model for assessment of large-scale subscription review projects on two bundled packages that expire Dec. 31, 2017: ScienceDirect and Springer.

N. Retire formula method of budget allocation for subject specialist monograph allocations and instead implement a data-driven firm-order monograph fund to more equitably make funds available for discretionary spending.

O. Implement a tri-annual database review process in order to free up funding for new subscription resources.

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