Quality Control Automation for Student Driven Digitization Workflows

At Union College Schaffer Library, the digitization lab is mostly staffed by undergraduates who only work a handful of hours a week. While they do a great job, the infrequency of their work hours and lack of experience results in errors in digitization and metadata. Many of these errors are difficult to catch during quality control checks because they are so minute, such as a missed counted page number here, or a transposed character in a filename there. So, a Computer Science student and a librarian collaborated to create a quality control automation application for the digitization workflow. The application is written in Python and relies heavily on using Openpyxl libraries to check the metadata spreadsheet and compare metadata with the digitized files. This article discusses the purpose and theory behind the Quality Control application, how hands-on experience with the digitization workflow informs automation, the methodology, and the user interface decisions. The goal of this application is to make it usable by other students and staff and to build it into the workflow in the future. This collaboration resulted in an experiential learning opportunity that has benefited the student's ability to apply what they have learned in class to a real-world problem.