BIBFRAME to Linked Data

Most commercial search engines like Google and Microsoft Bing, accept another linked-data vocabulary for indexing called for structuring descriptions that are typically embedded into a web page.

For this example we will use the BIBFRAME RDF that was generated from the MODS to BIBFRAME example and convert it to linked data that could be embedded in an HTML page.

Creating another SPARQLProcessor instance, this time we will use the bf-to-schema.ttl RML rules file and original BIBFRAME Lean graph we generated with the first rml_processor.

>>> bf2schema_processor = processor.SPARQLProcessor(

Using the same instance_iri and item_iri as before, we will now run the processor.


Displaying the as Turtle

@prefix rdf: <> .
@prefix rdfs: <> .
@prefix schema: <>

<> a schema:CreativeWork ;
    schema:contributor "Austen, Jane, 1775-1817.",
        "C. Scribner's sons",
        "Howells, William Dean, 1837-1920." ;
    schema:datePublished "1918"^^<>,
        "c1918" ;
    schema:name "Pride and prejudice /" ;
    schema:publisher "New York, Chicago [etc.] : C. Scribner's sons, [c1918]" 

The final exercise in this section will be creating a new RML TriplesMap and including that rule when running an existing mapping workflow.

Original contented Copyrighted © 2017 by Jeremy Nelson and KnowledgeLinks under Creative Commons License, Source code repository licensed under the Apache 2 and available on Github.