A Comparative Study of Non-Commercial Text Data Mining Policies in German Libraries

• Type of Material: Book Chapter
• Authors: Andrea Quinn, Emory University
• Language: English
• Date: 2025
• Publisher: Association of College and Research Libraries
• Publication Version: Final Published Version
• Copyright Statement: © 2025 Andrea M. Quinn
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): https://alastore.ala.org/text-and-data-mining-literacy-librarians
• Title of Journal or Parent Work: Text and Data Mining Literacy for Librarians
• ISBN: 979-8892555951
• Keywords: Copyright; Text data mining; Academic libraries; Germany; Law
• Research Categories: Intellectual property; Library science

Abstract

Text and data mining (TDM) is the process of using automated techniques to derive information from large sets of digital content. Librarians who liaise with a wide range of academic disciplines need TDM skills to support research at their institutions. Text and Data Mining Literacy for Librarians collects ways that academic libraries are supporting TDM literacy through services, workflows, and professional development. In five parts, it offers a variety of perspectives, insights, and experiences that can help you address the challenges of supporting TDM research, fit it into your existing reference and instruction work, and conduct your own. Essentials of Text and Data Mining (TDM) Literacy Data Literacy, Licensing, and Management Challenges with TDM TDM Research in Action: Practical Applications and Case Studies Generating Insights from Library Reference Data Proprietary TDM Software: Examples and Implementations Chapters cover a range of disciplines and subject areas from a variety of institution sizes and types. Text and Data Mining Literacy for Librarians is intended to empower library workers, inform decision-makers, and support our research communities as working with textual data becomes further embedded into the research landscape.