New Resource From the Data Curation Network (DCN): A Primer for Applying and Interpreting Licenses for Research Data and Code

A new resource from the Data Curation Network.

A Primer for Applying and Interpreting Licenses for Research Data and Code (2024)

Authors
Lisa Chinn, Matthew Murray, and Isaac Wink

Affiliate Contributors (Peer Reviewers)
Talya Cooper
Laura Hjerpe
Katherine Klosek
Sophia Lafferty-Hess
Allison Langham-Puttrow
Jiebei Luo.

DCN Mentors
Jennifer Huck, University of Virginia

From the Introduction to the Primer:

This primer gives data curators an overview of the licenses that are commonly applied to datasets and code, familiarizes them with common requirements in institutional data policies, and makes recommendations for working with researchers who need to apply a license to their research outputs or understand a license applied to data or code they would like to reuse. While copyright issues are highly case-dependent, the introduction to the data copyright landscape and the general principles provided here can help data curators empower researchers to understand the copyright context of their own data.

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