This 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. This month, we’re joined by two of the book’s editors, Whitney Kramer and Iliana Burgos, for a two-part series to discuss why this book is needed right now. In the series, our guests highlight the growing demand for TDM literacy among researchers and outline what makes TDM partnerships work across campus. Further, they chat about licensing agreements and copyright in relation to TDM, practical case studies in the book, and how TDM literacy might evolve from here.

In this first episode, Whitney and Iliana reveal that they started this project with their coeditor Evan Muzzall in response to a gap in the literature—there was a clear lack of guidance for librarians on how to support researchers using TDM. Next, they share their working definition for Text and Data Mining and why their call for chapter proposals specifically sought out early-career writers. Last, Whitney and Iliana underscore that librarians don’t need to become TDM experts overnight, instead recommending to approach any new technology from a “learning perspective.”

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