Theory Article

Licensing Challenges Associated With Text and Data Mining: How Do We Get Our Patrons What They Need?

Authors
  • Peter McCracken (Cornell University)
  • Emma Raub orcid logo (Cornell University)

Abstract

Today’s researchers expect to be able to complete text and data mining (TDM) work on many types of textual data. But they are often blocked more by contractual limitations on what data they can use, and how they can use it, than they are by what data may be available to them. This article lays out the different types of TDM processes currently in use, the issues that may block researchers from being able to do the work they would like, and some possible solutions.

Keywords: text and data mining, tdm, contracts, dmca exemptions

How to Cite:

McCracken, P. & Raub, E., (2023) “Licensing Challenges Associated With Text and Data Mining: How Do We Get Our Patrons What They Need?”, Journal of Librarianship and Scholarly Communication 11(1). doi: https://doi.org/10.31274/jlsc.15530

Rights: © 2023 The Author(s). License: CC BY 4.0

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Published on
03 Feb 2023
Peer Reviewed