Maximizing Equitable Reach and Accessibility of ETDs

Abstract

This poster addresses accessibility issues of electronic theses and dissertations (ETDs) in digital libraries (DLs). ETDs are available primarily as PDF files, which present barriers to equitable access, especially for users with visual impairments, cognitive or learning disabilities, or for anyone needing more efficient and effective ways of finding relevant information within these long documents. We propose using AI techniques, including natural language processing (NLP), computer vision, and text analysis, to convert PDFs into machine-readable HTML documents with semantic tags and structure, extracting figures and tables, and generating summaries and keywords. Our goal is to increase the accessibility of ETDs and to make this important scholarship available to a wider audience.

Citation

BibTeX

@inproceedings{ingram2023maximizing,
  author = {Ingram, William and Wu, Jian and Fox, Edward},
  title = {Maximizing Equitable Reach and Accessibility of ETDs},
  booktitle = {Proceedings of the 23rd {ACM}/{IEEE}-CS Joint Conference on Digital Libraries},
  location = {Santa Fe, New Mexico, USA},
  publisher = {{IEEE} Press},
  series = {JCDL '23},
  year = {2023},
  month = jun,
  pages = {256--257},
  doi = {10.1109/JCDL57899.2023.00049},
  note = {Poster Presentation},
  month_numeric = {6}
}