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OARS: Toward Automating the Ongoing Subscription Review

Jul 05, 2015

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Technology

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).

  • 1. OARS: Toward Automating the Ongoing Subs ription Re ieOngoing Subscription Review Geoffrey P. Timms Mercer University i d Jonathan H. Harwell Georgia Southern University jh ll i h d [email protected]@georgiasouthern.edu

2. Context Georgia Southern University Doctoral-Research University FY09: $300 000 collection budget cutFY09: $300,000 collection budget cut FY10: $470,000 collection budget cut, g FY11: $1.2 million total budget C&RS: 4 librarians & 12 support staff 3. Needs Balance the budgetg Rapid assessment Maximum input from stakeholders St li th f l tStreamline the process for long-term use Control the data vs. data controlling usControl 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 decisionsrenewal decisions Phase 1 & Phase 2 Two development guidelines: SimpleSimple Open source 5. Variables/Data Tracked Title U i C t l # Entanglement N tUnique Control # ISSN Notes Current Cost EISSN LC Call Number Usage Data Faculty Rating Year Publisher y g Eigenfactor Percentile u i e 6. Discarded Variables lAlternative coverage Frequency/cost per issue/useq y p Faculty format preference Peer reviewPeer review Print cost Online only cost Print plus online costp Usage Year 2 Librarian ratingLibrarian rating ILL borrowing (will be in Phase 2) 7. Structure L.A.M.P environment MySQL database on backend PEAR MDB2 Abstraction LayerPEAR MDB2 Abstraction Layer Coded in PHP & JavaScriptJ p Input via .csv upload or forms Data export in .csv format 8. OARS Recommendation Metric Faculty Rating Essential = 100 %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 Relative Cost Cost as % of average cost 80 100 120 ore Calculation of Cost Score Cost as % of average cost (-0.5 x Cost as % of av. cost) + 100 Score range limited to 0-100 0 20 40 60 80 CostSc g Covers Cost at 0-200% of av. cost 0 0 50 100 150 200 250 300 Cost as % of average cost Relative Usage U % f 80 100 120 ore Calculation of Usage Score Use as % of average use (0.5 x Use as % of av. use) Score range limited to 0-100 0 20 40 60 80 UsageScg Covers 0-200% of av. use 0 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% weighting applied to each of the four variables Total weighting = 100% Even weighting Cost Score Usage Score Rating Eigenfactor TOTAL 44 65 50 85.944 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 85 944 65 50 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 pointsamong the other data points Library of Congress Call Numbersy g MySQL Boolean Searching spaces and periods Sorting Required normalizationRequired normalization Complex Regex (Cheers to Bill Dueber) Reverse normalization MySQL Natural Language Search Minimum is four-character stringMinimum is four character string ACM, ACS, etc. cannot be searched MySQL can be locally re-configured 13. Discussion OARS Recommendation MetricOARS Recommendation Metric Data/variables tracked OARS Report OtherOther 14. h kTh k !Thank you!Thank you!yy Jonathan H. Harwell [email protected] Geoffrey P. Timms timms [email protected] image from http://www.blogcdn.com/www.gadling.com/media/2008/05/oars.jpg [email protected]