Lab: RDFS: Difference between revisions
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=Lab | =Lab 7: RDFS Programming with rdflib and owlrl= | ||
==Topics== | ==Topics== | ||
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Entailments and axioms with owlrl. | Entailments and axioms with owlrl. | ||
==Classes/ | ==Classes/Methods/Vocabularies== | ||
owlrl.RDFSClosure (RDFS_Semantics, closure, flush_stored_triples | owlrl.RDFSClosure (RDFS_Semantics, closure, flush_stored_triples) | ||
'''Vocabularies: ''' | |||
RDFS | RDF.type | ||
RDFS.subClassOf, RDFS.subPropertyOf, RDFS.domain, RDFS.range, RDFS.label, RDFS.comment, | |||
==Tasks== | ==Tasks== | ||
Consider the following | First, pip install owlrl. | ||
"University of California | The RDFS Vocabulary can be imported from rdflib.namespace, just like FOAF or RDF. | ||
All universities are higher education | |||
'''Consider the following Scenario:''' | |||
that the person has expertise in that subject. Only persons can have expertise, and what they have expertise | "University of California and University of Valencia are both Universities. | ||
in is always a subject." | All universities are higher education institutions (HEIs). That a person has a degree in a subject means | ||
that the person has expertise in that subject. Only persons can have an expertise, and what they have expertise | |||
in is always a subject. Having a degree from a HEI means that you have also graduated from that HEI. Only persons can graduate from a HEI." | |||
'''Create RDFS triples corresponding to the text above with RDFlib''' - if you can, try to build on | |||
your example from lab 2! | |||
Using these three lines we can add automatically the inferred triples (like ex:University rdf:type ex:Higher_Education_Institute) : | |||
<syntaxhighlight> | |||
rdfs = owlrl.RDFSClosure.RDFS_Semantics(g, False, False, False) | |||
rdfs.closure() | |||
rdfs.flush_stored_triples() | |||
</syntaxhighlight> | |||
Check that simple inference works - make sure that your graph contains triples like these, even if | Check that simple inference works - make sure that your graph contains triples like these, even if | ||
you have not asserted them explicitly: | you have not asserted them explicitly: | ||
* that | * that University of California and Valencia are HEIs | ||
* that Cade and | * that Cade and Emma both have expertises | ||
* that Cade and Emma are both persons | |||
* that Cade and | |||
* that biology and chemistry are both subjects | * that biology and chemistry are both subjects | ||
* that Cade and Emma have both graduated from some HEI | |||
One way to check if the triples are there: | |||
<syntaxhighlight> | |||
universities = g.query(""" | |||
PREFIX ex: <http://example.org/> | |||
ASK { | |||
ex:University_of_California rdf:type ex:Higher_Education_Institution. | |||
} | |||
""") | |||
print(bool(universities)) | |||
</syntaxhighlight> | |||
Rewrite some of your existing code to use rdfs:label in a triple and add an rdfs:comment to the same resource. | Rewrite some of your existing code to use rdfs:label in a triple and add an rdfs:comment to the same resource. | ||
==If you have more time...== | ==If you have more time...== | ||
Create a new RDFS graph | Create a new RDFS graph that wraps an empty graph. This graph contains only RDFS axioms. Write it out in Turtle and check that you understand the meaning and purpose of each axiom. | ||
Create an RDF (not RDFS) graph that contains all the triples in your first graph (the one with all the people and universities). Subtract all the triples in the axiom graph from the people/university graph. Write it out to see that you are left with only the asserted and entailed triples and that none of the axioms remain. | Create an RDF (not RDFS) graph that contains all the triples in your first graph (the one with all the people and universities). Subtract all the triples in the axiom graph from the people/university graph. Write it out to see that you are left with only the asserted and entailed triples and that none of the axioms remain. | ||
Download the SKOS vocabulary from https://www.w3.org/2009/08/skos-reference/skos.rdf and save it to a file called, e.g., SKOS.rdf . | <!-- Download the SKOS vocabulary from https://www.w3.org/2009/08/skos-reference/skos.rdf and save it to a file called, e.g., SKOS.rdf . | ||
Use the schemagen tool (it is inside your Jena folders, for example under apache-jena-3.1.1/bin) to generate a Java class for the SKOS vocabulary. | Use the schemagen tool (it is inside your Jena folders, for example under apache-jena-3.1.1/bin) to generate a Java class for the SKOS vocabulary. | ||
You need to do this from a console window, using a command like "<path>/schemagen -i <infile.rdf> -o <outfile.java>". | You need to do this from a console window, using a command like "<path>/schemagen -i <infile.rdf> -o <outfile.java>". | ||
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Copy the SKOS.java file into your project in the same package as your other Java files, and try to use SKOS properties | Copy the SKOS.java file into your project in the same package as your other Java files, and try to use SKOS properties | ||
where they fit, for example to organise the keywords for interests and expertise. | where they fit, for example to organise the keywords for interests and expertise. | ||
--> | |||
==Useful Readings== | |||
*[https://wiki.uib.no/info216/index.php/File:S05-RDFS-11.pdf Lecture Notes] | |||
*[https://wiki.uib.no/info216/index.php/Python_Examples Example page] |
Revision as of 16:30, 4 March 2020
Lab 7: RDFS Programming with rdflib and owlrl
Topics
Basic RDFS graph programming in RDFlib. Entailments and axioms with owlrl.
Classes/Methods/Vocabularies
owlrl.RDFSClosure (RDFS_Semantics, closure, flush_stored_triples)
Vocabularies:
RDF.type
RDFS.subClassOf, RDFS.subPropertyOf, RDFS.domain, RDFS.range, RDFS.label, RDFS.comment,
Tasks
First, pip install owlrl. The RDFS Vocabulary can be imported from rdflib.namespace, just like FOAF or RDF.
Consider the following Scenario: "University of California and University of Valencia are both Universities. All universities are higher education institutions (HEIs). That a person has a degree in a subject means that the person has expertise in that subject. Only persons can have an expertise, and what they have expertise in is always a subject. Having a degree from a HEI means that you have also graduated from that HEI. Only persons can graduate from a HEI."
Create RDFS triples corresponding to the text above with RDFlib - if you can, try to build on your example from lab 2!
Using these three lines we can add automatically the inferred triples (like ex:University rdf:type ex:Higher_Education_Institute) :
rdfs = owlrl.RDFSClosure.RDFS_Semantics(g, False, False, False)
rdfs.closure()
rdfs.flush_stored_triples()
Check that simple inference works - make sure that your graph contains triples like these, even if you have not asserted them explicitly:
- that University of California and Valencia are HEIs
- that Cade and Emma both have expertises
- that Cade and Emma are both persons
- that biology and chemistry are both subjects
- that Cade and Emma have both graduated from some HEI
One way to check if the triples are there:
universities = g.query("""
PREFIX ex: <http://example.org/>
ASK {
ex:University_of_California rdf:type ex:Higher_Education_Institution.
}
""")
print(bool(universities))
Rewrite some of your existing code to use rdfs:label in a triple and add an rdfs:comment to the same resource.
If you have more time...
Create a new RDFS graph that wraps an empty graph. This graph contains only RDFS axioms. Write it out in Turtle and check that you understand the meaning and purpose of each axiom.
Create an RDF (not RDFS) graph that contains all the triples in your first graph (the one with all the people and universities). Subtract all the triples in the axiom graph from the people/university graph. Write it out to see that you are left with only the asserted and entailed triples and that none of the axioms remain.