Lab: OWL 1

Topics

Basic OWL ontology programming with RDFlib and owlrl.

WebVOWL visualisation.

RDF and RDFS might be relevant too.

Classes/Vocabularies

Vocabulary:

OWL (sameAs, equivalentClass, equivalentProperty, differentFrom, disjointWith, inverseOf)
OWL (SymmetricProperty, AsymmetricProperty, ReflexiveProperty, IrreflexiveProperty, TransitiveProperty, FunctionalProperty, InverseFunctionalProperty, AllDifferent)

Tasks

Task 1

Write OWL triples that corresponds to the following text. .If you can, try to build on your example from labs 1 and 2, or extend the triples at the bottom of the page. OWL terms can be imported from rdflib in the same way as RDF and RDFS terms.

Donald Trump and Robert Mueller are two different persons.
Actually, all the names mentioned in connection with the Muelle investigation refer to different people.
All these people are foaf:Persons as well as schema:Persons (they are http://xmlns.com/foaf/0.1/Person and http://schema.org/Person).
Tax evation is a kind of bank and tax fraud.
The Donald Trump involved in the Mueller investigation is dbpedia:Donald_Trump and not dbpedia:Donald_Trump_Jr. .
- Tip: rdflib's Turtle parser does not like URLs with punctuation marks written "prefix style" (dbpedia:Donald_Trump_Jr.), but it will accept the full URL written in angle brackets (<http://dbpedia.org/resource/Donald_Trump_Jr.>)
Congress, FBI and the Mueller investigation are foaf:Organizations.
Nothing can be both a person and an organization.
Leading an organization is a way of being involved in an organization.
Being a campaign manager or an advisor for is a way of supporting someone.
Donald Trump is a politician and a Republican.
A Republican politician is both a politician and a Republican.

Task 2

g.add((ex:Paul_Manafort, ex:hasBusinessPartner, ex:Rick_Gates))
g.add((ex:Michael_Flynn, ex:adviserTo, ex:Donald_Trump))
g.add((ex:Rick_Gates_Lying, ex:wasLyingTo, ex:FBI))
g.add((ex:Donald_Trump, ex:presidentOf, ex:USA))
g.add((ex:USA, ex:hasPresident, ex:Donald_Trump))

Look through the predicates (properties) above and add new triples for each one that describes them as any of the following: a reflexive, irreflexive, symmetric, asymmetric, transitive, functional, or an inverse functional property. e.g

g.add((ex.wasLyingTo, RDF.type, OWL.IrreflexiveProperty))

Task 3

Print/Serialize the ontology. Then use owlrl as below to infer additional triples. Can you spot the many inferences?

DeductiveClosure(OWLRL_Semantics).expand(graph)

Finally write the ontology to a XML file, and visualise it using https://service.tib.eu/webvowl/. The purpose of WebVOWL is to visualise classes and their properties, so the individuals may not show.

Useful Reading

Lecture Notes

Example page

Triples you can extend for the tasks

Turtle

@prefix ex: <http://example/org#> .

ex:Mueller_Investigation ex:involved ex:George_Papadopoulos,
        ex:Michael_Cohen,
        ex:Michael_Flynn,
        ex:Paul_Manafort,
        ex:Rick_Gates,
        ex:Roger_Stone ;
    ex:leadBy ex:Robert_Mueller .

ex:Michael_Cohen ex:attorneyFor ex:Donald_Trump ;
    ex:pleadedGuilty ex:Michael_Cohens_Lying .

ex:Michael_Cohens_Lying a ex:Lying ;
    ex:wasLyingAbout ex:Trump_RealEstateDeal ;
    ex:wasLyingTo ex:Congress .

ex:Michael_Flynn ex:adviserTo ex:Donald_Trump ;
    ex:negotiatedAgreement ex:PleaAgreement ;
    ex:pleadedGuilty ex:Michael_Flynns_Lying .

ex:Michael_Flynns_Lying a ex:Lying ;
    ex:wasLyingTo ex:FBI .

ex:Paul_Manafort ex:campaignManager ex:Donald_Trump ;
    ex:chargedWith ex:ForeignLobbying,
        ex:MoneyLaundering,
        ex:TaxEvasion ;
    ex:convictedFor ex:BankAndTaxFraud ;
    ex:hasBusinessPartner ex:Rick_Gates ;
    ex:negotiatedAgreement ex:PleaAgreement ;
    ex:pleadedGuilty ex:Conspiracy ;
    ex:sentencedTo ex:Prison .

ex:Rick_Gates_Lying a ex:Lying ;
    ex:wasLyingTo ex:FBI .

ex:Rick_Gates ex:chargedWith ex:ForeignLobbying,
        ex:MoneyLaundering,
        ex:TaxEvasion ;
    ex:pleadedGuilty ex:Conspiracy,
        ex:Rick_Gates_Lying .