RightsML
For the latest on the development of RightsML please consult our Work in Progress page.
RightsML is IPTC's Rights Expression Language for the media industry
Rights Expression Languages are machine-readable languages used to convey the rights and restrictions associated with a particular asset. They codify the permissible actions (under certain duties and constraints) for an asset when it's made available by one party to another.
A typical scenario in the world of photo agencies: the agency's customer is a major publishing house with magazines, newspapers and broadcast properties (each of which has websites and iPad apps, too). The publishing house has consolidated internal systems and storage and uses one single Enterprise Digital Asset Management System across all of its properties. The pictures the agency sends to the publishing house are usable under certain conditions for one or more of the publishing house's properties -- but seldom under the same identical conditions by all of them at the same time. Traditionally, the agency would need to supply the publishing house with multiple sets of images (one for each of the publisher's properties), resulting in duplicate images and additional overhead. Even then, editors would still need to examine any natural language notes, to find out if there are relevant restrictions for a particular use of an image.
How to streamline this complicated, error-prone and manually-intensive setup? And how to ensure that both rights holders and clients can be confident that the use of digital assets complies with the appropriate rights and restrictions? Enter RightsML.
With RightsML, every single piece of content distributed by a publisher can be annotated with machine-readable instructions that spell out the particular permissions and restrictions for a piece of content. For example "this photo can be used in print but not in broadcast" or "this photo can be used online for 30 days after it was created but print use requires additional licenses."
RightsML: The IPTC Standard for Machine Readable Rights
RightsML builds on ODRL, the framework for digital rights hosted by the W3C, by extending and refining it, to meet the specific needs of the media industry. RightsML 1.0 and 1.1 are in sync with ODRL 2.0 and 2.1. RightsML 2.0 is in sync with the W3C ODRL 2.2 Recommendation.
- RightsML 2.0 specification document
- Use Cases
- Implementation Guide
- Introduction to ODRL
- Libraries for generating RightsML 1.1 and ODRL 2.1 licenses in Python and Javascript
Machine Readable Rights and the News Industry: Opportunities, Standards and Challenges
In March 2013, the IPTC held a one day conference: "Machine Readable Rights and the News Industry". The aim was to bring together the major players interested in machine readable rights, to explore the possibilities of working with the members of the IPTC to take advantage of the opportunities and overcome the challenges. The event was a great success - read a summary and view the presentations.
How to give us feedback on RightsML
The IPTC invites publishers and their partners to try RightsML and to give us feedback, so that we can fine tune RightsML. One way to help us assess the new standard is to examine the vocabularies we have put forward for permissions, restrictions and duties, to ensure that they allow you to express the rights you need to apply in your business. If you identify terms that are missing or that aren't sufficiently clearly documented, let us know. If you would like to actually try encoding your rights expressions using RightsML, we would be happy to support you by providing suggested implementations and providing feedback on any sample XML implementations you generate. We would also be happy to advise on the best ways to process RightsML documents, to ensure that partners are complying with the expressed rights and restrictions.
We welcome feedback on and questions about RightsML. You may post to the public RightsML mailing list. If you are an IPTC member, then you are also entitled to join the IPTC members-only RightsML email discussion list.