Research Libraries: How You Can Support Text and Data Mining
Europe’s incoming Directive on Copyright in the Digital Single Market contains two new exceptions allowing text and data mining (TDM). The Directive is currently being implemented by all member states and must come into force no later than June 2021.
Download our guide to supporting TDM.
Article 3 grants universities, educational establishments and libraries the right to mine in-copyright works to which they have lawful access.
Article 4 introduces an exception mainly aimed at commercial data analytics and AI. This exception could be helpful in the context of Knowledge Transfer between private companies and universities.
For European research libraries which want to make the most of this exciting new opportunity to support researchers undertaking TDM, LIBER’s Copyright & Legal Matters Working Group has drafted a document with several recommendations.
Libraries Supporting TDM: Guidance from LIBER
The guide outlines the key role of libraries as TDM partners. As organisations, research libraries are — among other things — often the locus of copyright law expertise at a university, have the relationship with the publisher and play an important part in supporting Open Science through overseeing the institutional repository.
They also support FAIR data, open access and open data, and operate as a natural place where skills from across the university can come together to in support of TDM.
Getting Started With TDM
To help libraries make the most of this unique positioning, we offer several ideas for getting started in six categories: (1) Understand the Current Situation; (2) Share Knowledge & Resources; (3) Get Leadership Buy-In; (4) Library Policies & Structures; (5) Network Building and (6) Staff Training.
We also outline in detail recommendations for interacting with publishers and respecting researcher privacy.
Please download the guide and, if you want to stay updated on LIBER’s copyright work, subscribe for copyright updates. We also recently ran a webinar offering tips for libraries looking to support Text and Data Mining.
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