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Identifying the best web accessibility workflows for legacy archival description data
Journal of Digital Media Management,
13
(3),
259-266
(2025)
Abstract
This paper examines the challenges and solutions associated with making archival PDF finding aids accessible to blind and low-vision users, particularly those who rely on screen readers. The project, conducted at the University of Toronto, highlights the barriers posed by unstructured PDFs, which fail to meet the various accessibility standards specified in the WWW Consortium’s Web Content Accessibility Guidelines. Three methods were tested to improve accessibility: manual remediation, PDF-to-HTML conversion, and data migration into the Access to Memory (AtoM) platform. The results indicated that both the manual and automated remediation methods were either too costly or ineffective, while the most promising approach involved migrating the description data into AtoM via CSV import, enhancing both accessibility and search functionality. The paper underscores the need for ongoing funding and professional expertise to address web accessibility issues in archival settings and outlines future steps to improve PDF generation within AtoM for broader application.
Keywords: accessibility; AtoM; finding aid; screen reader; PDF
The full article is available to subscribers to the journal.
Author's Biography
Isobel R. S. Carnegie Isobel Carnegie graduated from the Faculty of Information at the University of Toronto in 2024 with a master’s of information, earning a double concentration in archives and records management and libraries and information science. While completing her master’s degree, she worked as the Digital Collections Support GSLA in Information Technology Services. She also holds a master’s in literature from Toronto Metropolitan University. Her research interests include the intersections of queerness with archives and information science, reparative description, and the use of critical fabulation to write minor histories. She is currently writing her first novel with support from the Toronto Arts Council.
Christina Cutler graduated from the Faculty of Information at the University of Toronto in 2023 with a master’s of information. While completing her master’s degree, she worked as the Scholarly Publishing Graduate Student Library Assistant in Information Technology Services, supporting the University of Toronto’s institutional repository and the journals platform. Since graduating, she has worked as a data librarian in the University of Toronto’s Map and Data Library, providing support for researchers interested in text and data mining. Her primary research interest is in providing accessible and equitable services in galleries, libraries and museums.
