We currently offer the following licenses to be used with the Data items you supply:
PDDL Public Domain Dedication and License:
Place the data/database in the public domain (waiving all rights)
CC0 "No Rights Reserved":
Enables scientists, educators, artists and other creators and owners of copyright-protected content to waive copyright interests in their works and thereby place them as completely as possible in the public domain, so that others may freely build upon, enhance and reuse the works for any purposes without restriction under copyright.
ODbL Open Database License:
You are free
- To Share: To copy, distribute and use the database
- To Create: To produce works from the database
- To Adapt: To modify, transform and build upon the database
- Attribute: You must attribute any public use of the database, or works produced from the database, in the manner specified in the ODbL. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database
- Share-Alike: If you publicly use any adapted version of this database, or works produced from an adapted database, you must also offer that adapted database under the ODbL
- Keep open: If you redistribute the database, or an adapted version of it, then you may use technological measures that restrict the work (such as DRM) as long as you also redistribute a version without such measures.
Task + Method Licenses
These item types are fixed to CC-BY-SA 3.0.
- to Share — to copy, distribute and transmit the work
- to Remix — to adapt the work
- Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).
- Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same, similar or a compatible license.
This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)