The Web Annotation Working Group has published a Candidate Recommendation for three documents:
- Web Annotation Data Model: This specification describes a structured model and format, in JSON, to enable annotations to be shared and reused across different hardware and software platforms. Common use cases can be modeled in a manner that is simple and convenient, while at the same time enabling more complex requirements, including linking arbitrary content to a particular data point or to segments of timed multimedia resources.
- Web Annotation Vocabulary: specifies the set of RDF classes, predicates and named entities that are used by the Web Annotation Data Model. It also lists recommended terms from other ontologies that are used in the model, and provides the JSON-LD Context and profile definitions needed to use the Web Annotation JSON serialization in a Linked Data context.
- Web Annotation Protocol: This document describes the transport mechanisms for creating and managing annotations in a method that is consistent with the Web Architecture and REST best practices.
This is a re-publication, without substantial change, of the Candidate Recommendation published on the 5th of July for the Data Model and Vocabulary, and on the 12th of July for the Protocol. The only significant change (beyond some minor editorial clarifications and changes) is that the respective exit criteria for the Candidate Recommendation phase is now documented in the publications themselves.
Candidate Recommendation means that the Working Group considers the technical design to be complete, and is seeking implementation feedbacks on the documents. There is a separate document how to use them and report on implementation results. The group is keen to get comments and implementation experiences on these specifications, either as issues on the Group’s GitHub repository or by posting to email@example.com.
The group expects to satisfy the implementation goals (i.e., at least two, independent implementation for each of the test cases) by September 30, 2016.