Apples to Oranges: Using Python and the pymarc library to match bookstore ISBNs to locally held eBook ISBNs

Abstract

To alleviate financial burdens faced by students and to provide additional avenues for the benefits shown to be present when no-cost materials are available to students (equity and access and an increase in student success metrics), more and more libraries are leveraging their collections and acquisition processes to provide no-cost eBook alternatives to students. It is common practice now for academic libraries to have a partnership with their campus bookstore and to receive a list of print and eBook materials required for an upcoming semester. Libraries take these lists and use various processes and workflows, some extremely labor intensive and others semi-labor intensive, to identify which of these titles they already own as unlimited access eBooks, and which titles could be purchased as unlimited access eBooks. The most common way to match bookstore titles to already licensed eBooks is by searching the bookstore provided ISBN or title in either the Library Management System (LMS), the Analytics and Reporting layer of the LMS, the Library Discovery Layer, or via another homegrown process. While some searching could potentially be automated, depending on the available functionality of the LMS or the Analytics component of the LMS, the difficulty lies in matching the bookstore ISBN, often the print ISBN, to the library eBook ISBN. This article will discuss the use of Python, the Pymarc library in Python, and Library eBook MARC records to create an automated identification process to accurately match bookstore lists to library eBook holdings.