IFLA Statement on Text and Data Mining

dc.audienceAudience::Advisory Committee on Copyright and other Legal Matters
dc.contributor.authorInternational Federation of Library Associations and Institutions (IFLA)
dc.date.accessioned2025-08-01T11:30:08Z
dc.date.available2025-08-01T11:30:08Z
dc.date.issued2013
dc.description.abstractThe International Federation of Library Associations and Institutions (IFLA), as the global voice of the library and information profession, affirms that legal certainty for Text and Data Mining (TDM) can only be achieved through statutory exceptions. In the digital age, characterised by unprecedented volumes of information, TDM is essential for the advancement of learning, innovation, and cultural development. It enables researchers and institutions to derive new knowledge from existing content, offering significant benefits across disciplines—from the sciences to the humanities. While copyright and database laws were not designed with such technologies in mind, they can inadvertently impede this progress by restricting the computer-based reproduction of content that users already have lawful access to. IFLA contends that these incidental copies, necessary for analysis, should not be subject to the same limitations as traditional uses of content. Licensing, due to the vast and varied nature of data sources, is not a viable solution. IFLA urges the adoption of exceptions that guarantee the right to mine lawfully accessed content and to share resulting insights, provided such outputs do not substitute the original works. Ensuring this right is vital to unlocking the full potential of TDM for education, research, health, creativity, and inclusion.
dc.identifier.urihttps://repository.ifla.org/handle/20.500.14598/4298
dc.language.isoen
dc.publisherInternational Federation of Library Associations and Institutions (IFLA)
dc.rights.holderInternational Federation of Library Associations and Institutions (IFLA)
dc.rights.licenseCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCopyright
dc.subjectAdvocacy
dc.subjectText and data mining
dc.subjectBig data
dc.titleIFLA Statement on Text and Data Mining
dc.typeStatement
ifla.UnitAdvisory Committee::Advisory Committee on Copyright and other Legal Matters
ifla.oPubId8225

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