Negotiating a Text Mining License for Faculty Researchers

Author:

Williams Leslie A.,Fox Lynne M,Roeder Christophe,Hunter Lawrence

Abstract

<p>This case study examines strategies used to leverage the library’s existing journal licenses to obtain a large collection of full-text journal articles in extensible markup language (XML) format; the right to text mine the collection; and the right to use the collection and the data mined from it for grant-funded research to develop biomedical natural language processing (BNLP) tools. Researchers attempted to obtain content directly from PubMed Central (PMC). This attempt failed due to limits on use of content in PMC. Next researchers and their library liaison attempted to obtain content from contacts in the technical divisions of the publishing industry. This resulted in an incomplete research data set. Then researchers, the library liaison, and the acquisitions librarian collaborated with the sales and technical staff of a major science, technology, engineering, and medical (STEM) publisher to successfully create a method for obtaining XML content as an extension of the library’s typical acquisition process for electronic resources. Our experience led us to realize that text mining rights of full-text articles in XML format should routinely be included in the negotiation of the library’s licenses.</p>

Publisher

Boston College University Libraries

Subject

Library and Information Sciences,Information Systems

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Copyright and Text and Data Mining: Is the Current Legislation Sufficient and Adequate?;portal: Libraries and the Academy;2024-07

2. Trends in content development and licensing of electronic resources;Journal of Electronic Resources Librarianship;2021-01-02

3. Collaborative Digital Research: Case Study of Text Mining a Corpus of Academic Journals;New Review of Academic Librarianship;2020-09-21

4. Whose text, whose mining, and to whose benefit?;Quantitative Science Studies;2020-09

5. Text mining in business libraries;Journal of Business & Finance Librarianship;2017-02-28

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