All the metadata collected in the VEST map of data standards are also available in an RDF store.
An RDF store is a way of storing data using a machine-readable "grammar" (the Resource Description Framework) and machine-readable semantics (RDF vocabularies).
The whole RDF store is accessible through a SPARQL engine, which means that any system can run remote queries and get the resulting triples.
The endpoint of the SPARQL engine is: http://vest.agrisemantics.org/sparql
The vocabularies used in the RDF store are (with prefixes used in the examples below):
For example, the URI of the Agrovoc vocabulary in this RDF store is:
On each vocabulary page, there is a link to its RDF representation: following Linked Data best practices, the URI of the resource can serve both an HTML version of the resource and the RDF version, depending on the request. This means that if the URI is requested by a browser (which normally calls a URL with the specific text or HTML content type) the server will serve the HTML page, while if the request comes from an RDF tool the server will serve the RDF version.
To access the RDF version directly, you can add .rdf to the URI address, e.g. for Agrovoc: http://vest.agrisemantics.org/node/18630.rdf.
It was decided not to provide full resources (and therefore fully resolvable URIs) for secondary entities like authors, contributors or responsible bodies: therefore, these entities are treated in the RDF as “blank nodes” for which only the label (the name) is provided. Blank nodes are also used for some properties that in the VEST model are direct properties of the vocabulary while in other vocabularies are properties of related resources
The metadata model adopted in the map contains many elements for which there are no properties in any existing vocabulary: for these, we will create a new small VEST vocabulary containing only the properties for which there is no existing vocabulary. We also plan on creating a VEST application profile including all the classes and properties that we reuse from existing vocabularies plus the properties in the new VEST vocabulary.
Besides the description vocabularies used as schemas for the description, whenever possible the map also links internal classifications (like Type of vocabulary, Domain, Format...) to existing authority lists, possibly RDF as well.
For instance, the classification of vocabulary types is largely mapped to the W3C KOS Type vocabulary (http://w3id.org/nkos/nkostype), so that value vocabularies in the VEST registry have an owl:sameAs link to the URI of the corresponding vocabulary type defined in the more authoritative W3C list.
These mappings with existing value vocabularies were already described in D1.1.1, (table 5) and added to the database, but now they are also embedded in the RDF store so that queries can be run using the external better known URIs