From Texts to Objects: Digitizing Rare Books
Unique artifacts are what make digital collections special but come with challenges for archivists
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Posted on January 28, 2026 in Podcasts
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LibTech Insights editor
Last fall, our friends at ACRL published Text and Data Mining Literacy for Librarians, a wide-reaching text that details how librarians are using Text and Data Mining (TDM) across disciplines and levels of expertise. In the second episode of our two-part series with ACRL, Whitney Kramer and Iliana Burgos, editors of Text and Data Mining Literacy for Librarians, move into the applications of Text and Data Mining (TDM).
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Whitney Kramer is the research and data librarian at Catherwood Library at Cornell University. In this role, she supports students and faculty in the School of Industrial and Labor Relations, and the Economics, and Statistics and Data Science departments who work with both structured and unstructured data. Her research interests include data literacy and the usage of text data in social science research. Her work has been published in The Data Literacy Cookbook, Choice, Journal of New Librarianship, and ResearchDataQ. Previously, she was the entrepreneurship and public services librarian at the Roanoke Public Libraries in Roanoke, Virginia, and the business research librarian at Lippincott Library at the University of Pennsylvania.

Iliana Burgos is the emerging data practices librarian at Digital Scholarship Services at Cornell University Library. She supports researchers in exploring digital and computational approaches to humanities scholarship principles. A Ronald E. McNair Scholar and American Library Association Spectrum Scholar, her research engages text data and algorithmic literacies, critical platform studies, and community-based data justice movements. She previously worked in community outreach roles as a Carolina Academic Library Association.
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