OARS: Toward Automating the Ongoing Subscription Review

What is it about?

A few years ago I had the joyous privilege of coordinating a library subscription review. Particularly in times of tight budgets, academic librarians are regularly evaluating their serial subscriptions. Budgeting for these annual expenses, most of which inflate each year, is a challenge. Another challenge is how to gather the cost and usage data, as well as perhaps the impact factors; to present it to the faculty for their recommendations; and to make the final decisions for renewals, cancellations, and new subscriptions. How do we look at thousands of subscriptions and identify those with high costs per use, and maybe also use the impact factor of each journal as part of the formula-- especially when not every journal has an impact factor associated with it? How can we also incorporate the recommendations of our faculty and weigh those alongside the rest of the data? For example, when I surveyed the faculty at one library, none of them saw a reason to renew The Journal of College Student Development. But when we looked at the data, we saw that it had the highest usage of all of the journals-- presumably because it was getting heavy use by other university employees, not by the faculty. A librarian colleague came up with the idea of streamlining the process by creating a system to manage the data and recommend titles to consider for cancellation, based on all these factors. Another librarian colleague, Geoffrey Timms of Mercer University, went to work on creating this system. Geoff and I talked a lot about the specifications, how we wanted it to work, and the importance of making it user-friendly and available for free to libraries. We came to call it OARS: the Ongoing/Online Automated Review System. I've tested it with the collections of two very different libraries where I've worked-- one much larger than the other. My colleagues and I have found it invaluable for taking a large set of data and getting a big-picture view, resulting in an easy way to generate a list of titles to review for possible cancellation (the "low-hanging fruit" we're always trying to identify). Upload the data in an Excel template. Need to cut a certain dollar amount, or a certain percentage? Just pop that in, adjust the weights as you like, and there's your list of low-hanging fruit for librarians and faculty to evaluate. Check it out for yourself at http://www.rollins.edu/library/services/oars.html See the "About OARS" link or our Charleston Conference paper at http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1114&context=charleston for a full explanation of how it works. You're more than welcome to use (and modify) it for free. You're even more welcome to think about, and improve on, the concept of how we took data items and melded them with a flexible weighting mechanism. Geoff believes that the infrastructure he created is already dated, and that interested librarians might work with their Systems Departments to devise a system which works for them in their contexts. There's nothing really complicated about it. It involves entering and storing data and then running the OARS report. The OARS report is where our concept is utilized. For example, a similar system could be built by creating the structure in the Python-based Django (with a PGSQL database) which offers an out of the box administrative backend and convenient form generation. You could also do something similar by just using Access. If it looks like an idea that works, use it. Play with it. Spread the word. And salute Geoff for his hard work!

Featured Image

Why is it important?

Librarians facing budget cuts and having to cancel journals need a free tool to manage the process without reinventing the wheel. Journal cancellation projects can consume months of time, and we need a way to analyze the subscriptions in order to make the decisions with minimal impact on the information needs of the patrons. OARS is a free, open-source system that identifies low-hanging fruit based on a weighted formula.

Perspectives