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OARS: Toward Automating the Ongoing Subscription Review

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Thorough assessments of subscriptions are unwieldy and time- consuming to perform every year. A metric has been developed for standardizing the process, with a Web-based platform being constructed to …

Thorough assessments of subscriptions are unwieldy and time- consuming to perform every year. A metric has been developed for standardizing the process, with a Web-based platform being constructed to recommend renewals and
cancellations. This session will describe the metric and demonstrate the functionality of the platform, engaging the audience in making refinements. Coded in PHP and utilizing a MySQL database on the backend, the completed product will be an open-source Ongoing Automated Review System (OARS) for subscription reviews.
OARS will automate the selection of titles and data for review, which will result in a semi-automated process for annual renewal decisions. OARS will utilize multiple, customized variables, as well as an adjustable cumulative weighted scale of all variables which the system will use to recommend a renewal decision. OARS will use automated processes as much as possible, and will also provide data entry forms and uploads from files for easy input. There will also be an interface for stakeholders to view the data and respond to the review.
All of the variables and the draft requirements for OARS will be shared during the session. The variables include faculty ratings, cost, usage, Eigenfactor, and entanglements (such as consortial agreements, bundled packages, or cooperative collection development commitments).

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  • 1. OARS: Toward Automating the Ongoing Subs ription Review Subscription Re ie Jonathan H. Harwell Geoffrey P. Timms Georgia Southern University Mercer University jharwell@georgiasouthern.edu jh ll i h d timms_gp@mercer.edu i d
  • 2. Context Georgia Southern University Doctoral-Research University FY09: $300,000 collection budget cut $300 000 FY10: $470,000 collection budget cut , g FY11: $1.2 million total budget C&RS: 4 librarians & 12 ½ support staff
  • 3. Needs g Balance the budget Rapid assessment Maximum input from stakeholders St li th f l t Streamline the process for long-term use Control the data vs. data controlling us
  • 4. What is OARS? Ongoing Automated Review System Automate the selection of titles and , data for review, which will result in a semi-automated process for annual renewal decisions Phase 1 & Phase 2 Two development guidelines: Simple Open source
  • 5. Variables/Data Tracked Title Entanglement Unique Control # U i C t l Notes N t ISSN Current Cost EISSN Usage Data LC Call Number Faculty Rating y g Year Eigenfactor Percentile Publisher u i e
  • 6. “Discarded” Variables Alternative coverage l Frequency/cost per issue/use q y p Faculty format preference Peer review Print cost Online only cost Print plus online cost p Usage Year 2 Librarian rating ILL borrowing (will be in Phase 2)
  • 7. Structure L.A.M.P environment MySQL database on backend PEAR MDB2 Abstraction Layer Coded in PHP & JavaScript J p Input via .csv upload or forms Data export in .csv format
  • 8. OARS Recommendation Metric Faculty Rating Essential = 100 % Desirable = 50 % Not Needed = 0 % Eigenfactor™ Article Influence Percentile Percentile = % score E g 44.80 = 44.8% E.g. 44 80 44 8%
  • 9. OARS Recommendation Metric Calculation of Cost Score 120 Relative Cost 100 Score Cost as % of average cost 80 60 (-0.5 x Cost as % of av. cost) + 100 Co st 40 g Score range limited to 0-100 20 0 Covers Cost at 0-200% of av. 0 50 100 150 200 250 300 Cost as % of average cost cost Calculation of Usage Score 120 Relative Usage 100 Usage Score U as % of average use Use f 80 60 (0.5 x Use as % of av. use) 40 g Score range limited to 0-100 20 0 Covers 0-200% of av. use 0 50 100 150 200 250 300 Use as % of average use
  • 10. OARS Recommendation Metric Weighted Metric % weighting applied to each of the four variables Total weighting = 100% Even weighting Cost Score Usage Score Rating Eigenfactor TOTAL 44 65 50 85.9 Weight 25% 25% 25% 25% 100% Net Score 11 16.25 12.5 21.48 61.23 Usage/Eigenfactor preferred Cost Score Usage Score Rating Eigenfactor TOTAL 44 65 50 85.9 85 9 Weight 10% 35% 10% 45% 100% Net Score 4.4 22.75 5 38.66 70.81
  • 11. The OARS Interface to-date
  • 12. Challenges How to treat titles where usage data unavailable Divide the usage data proportion of weighting among the other data points y g Library of Congress Call Numbers MySQL Boolean Searching – spaces and periods Sorting Required normalization Complex Regex (Cheers to Bill Dueber) Reverse normalization MySQL Natural Language Search Minimum is four-character string four character ACM, ACS, etc. cannot be searched MySQL can be locally re-configured
  • 13. Discussion OARS Recommendation Metric Data/variables tracked OARS Report Other
  • 14. Th k you! Thank y ! h Jonathan H. Harwell jharwell@georgiasouthern.edu Geoffrey P. Timms timms_gp@mercer.edu timms gp@mercer.edu image from http://www.blogcdn.com/www.gadling.com/media/2008/05/oars.jpg