The Association of College and Research Libraries (ACRL) has released Text and Data Mining Literacy for Librarians, a new volume edited by Whitney Kramer, Iliana Burgos, and Evan Muzzall. The book highlights how academic libraries are advancing literacy in text and data mining (TDM) through services, workflows, and professional development initiatives.
TDM, broadly defined as the use of automated techniques to extract information from structured and unstructured digital content, has become an important methodology across disciplines, from the social sciences and humanities to natural and physical sciences. Librarians increasingly support researchers working with these methods, often requiring them to develop new skills and adapt existing practices.
The publication builds on earlier research and training efforts, serving as a standalone resource for library workers regardless of specific tools or platforms. It addresses issues such as dataset access, licensing, and ethical considerations, while also connecting TDM to broader areas including data literacy, algorithmic literacy, and open scholarship.
Organized into five parts, the volume covers essential skills, legal and managerial challenges, case studies of TDM projects, applications of library data, and examples of Proprietary TDM Software. Contributions reflect a wide range of disciplines and institutions, with several chapters authored by first-time contributors.
The collection underscores librarians’ expanding role in supporting TDM research and demonstrates how these efforts are contributing to advances in artificial intelligence and scholarly communication.
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