This paper is about how libraries can legally lend digital copies of books. It explains the legal and policy rationales for the process— “controlled digital lending”— as well as a variety of risk factors and practical considerations that can guide libraries seeking to implement such lending. We write this paper in support of the Position Statement on Controlled Digital Lending, a document endorsed by many libraries, librarians, and legal experts. Our goal is to help libraries and their lawyers become more comfortable with the concept by more fully explaining the legal rationale for controlled digital lending, as well as situations in which this rationale is the strongest.
A wealth of digital texts and the proliferation of automated research methodologies enable researchers to analyze large sets of data at a speed that would be impossible to achieve through manual review. When researchers use these automated techniques and methods for identifying, extracting, and analyzing patterns, trends, and relationships across large volumes of un- or thinly structured digital content, they are applying a methodology called text data mining or TDM. TDM is also referred to, with slightly different emphases, as “computational text analysis” or “content mining.”
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