Ebook Call Number Project: Automating Library of Congress Classification Numbers to Ebooks for Reporting

Abstract

The Ebook Call Number Project at the University of South Florida Libraries automated the process of
adding Library of Congress (LC) Classification numbers into call number fields, thereby enhancing
ebook metadata while minimizing manual work. This initiative aimed to improve the accuracy of
analytics reporting for discipline-specific collection assessment and reporting. The project involved
analyzing existing metadata, developing a Python-based automation tool using OCLC’s Connexion
API, and implementing a systematic workflow within the Ex Libris Alma Library Management
System for cataloging and quality control. The effort increased the number of ebook records with
LC call numbers from 91 percent to 99 percent, significantly enhancing reporting accuracy and
efficiency. This article details the project’s rationale, methodology, and outcomes, demonstrating how
automation and artificial intelligence can streamline metadata enrichment in academic libraries.
Finally, the article presents an alternative method for smaller institutions that lack access to
programmers or programming solutions and discusses future applications