Lab: OWL 1: Difference between revisions

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'''Task 1'''
'''Task 1'''


'''Write OWL triples that corresponds to the following text. '''.If you can, try to build on your example from labs 2 and 7, or extend the triples at the bottom of the page. OWL can be imported from rdflib.namespace.
'''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.
 
Cade and Emma are two different persons. <!-- All the countries mentioned above are different. --> The country USA above is
the same as the DBpedia resource http://dbpedia.org/resource/United_States (dbr:United_States) and the GeoNames
resource http://sws.geonames.org/6252001/ (gn:6252001). The person class (the RDF type the Cade and Emma resources)
in your graph is the same as FOAF's, schema.org's and AKT's person classes (they are http://xmlns.com/foaf/0.1/Person,
http://schema.org/Person, and http://www.aktors.org/ontology/portal#Person, respectively. Nothing can be any two of a person, a university, or a city at the same time. The property
you have used in your RDF/RDFS graph to represent that 94709 is the US zip code of Berkeley, California in US is
a subproperty of VCard's postal code-property (http://www.w3.org/2006/vcard/ns#postal-code). No two US cities can
have the same postal code. The property you have used for Emma living in Valencia is the same property as FOAF's
based near-property (http://xmlns.com/foaf/0.1/based_near), and it is the inverse of DBpedia's hometown property
(http://dbpedia.org/ontology/hometown, dbo:hometown). (This is not completely precise: but "hometown" is perhaps the
inverse of a subproperty of "based near".)
 
 
1. Cade and Emma are two different persons.
 
2. The resource for USA is the same as the DBpedia resource http://dbpedia.org/resource/United_States (dbr:United_States) and the GeoNames resource http://sws.geonames.org/6252001/ (gn:6252001).
 
3. The Person class is the same as schema person and akt person.
 
4. Nothing can be any two of a person, a university, or a city at the same time.
 
5. The resource for postal code is a subproperty of VCard. An No city can have the same.
 
6. The property you have used for living is the same as FOAF base_near, and is the invers of DBpedia's hometown property.  
 


* 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:Person''s as well as ''schema:Person''s (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.'' .
* Congress, FBI and the Mueller investigation are ''foaf:Organization''s.
* 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.
* ''Harder:'' Someone who supports a Republican politician is a Republican.


'''Task 2'''
'''Task 2'''
<syntaxhighlight>
<syntaxhighlight>
g.add((ex.Cade, ex.married, ex.Mary))
g.add((ex:Paul_Manafort, ex:hasBusinessPartner ex:Rick_Gates))
g.add((ex.Cade, ex.livesWith, ex.Mary))
g.add((ex:Michael_Flynn ex:adviserTo ex:Donald_Trump))
g.add((ex.Cade, ex.sibling, ex.Andrew))
g.add((ex:Rick_Gates_Lying ex:wasLyingTo ex:FBI))
g.add((ex.Cade, ex.hasFather, ex.Bob))
g.add((ex:Donald_Trump ex:presidentOf ex:USA))
g.add((ex.Bob, ex.fatherOf, ex.Cade))
g.add((ex:USA ex:hasPpresident ex:Donald_Trump))
</syntaxhighlight>
</syntaxhighlight>  


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.
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
e.g
<syntaxhighlight>
<syntaxhighlight>
g.add((ex.married, RDF.type, OWL.SymmetricProperty))
g.add((ex.wasLyingTo, RDF.type, OWL.IrreflexiveProperty))
</syntaxhighlight>
</syntaxhighlight>


'''Task 3'''
'''Task 3'''


Print/Serialize the ontology. Then use owlrl like seen below to infer additional triples. Can you spot the many inferences?
Print/Serialize the ontology. Then use owlrl as below to infer additional triples. Can you spot the many inferences?
 
<syntaxhighlight>
<syntaxhighlight>
# These three lines add inferred triples to the graph.
DeductiveClosure(OWLRL_Semantics).expand(graph)
owl = owlrl.CombinedClosure.RDFS_OWLRL_Semantics(g, False, False, False)
owl.closure()
owl.flush_stored_triples()
</syntaxhighlight>
</syntaxhighlight>


Finally write the ontology to a XML file, and try to visualise it using https://service.tib.eu/webvowl/. WebVOWL is oriented towards visualising classes and their properties, so the individuals may not show.
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==
==Useful Reading==
Line 79: Line 60:


==Triples you can extend for the tasks==
==Triples you can extend for the tasks==
'''Python'''
<syntaxhighlight>
import owlrl
from rdflib import Graph, Namespace, Literal, URIRef
from rdflib.namespace import RDF, RDFS, XSD, FOAF, OWL
g = Graph()
# Namespaces
ex = Namespace("http://example.org/")
dbp = Namespace("http://dbpedia.org/resource/")
geo = Namespace("http://sws.geonames.org/")
schema = Namespace("https://schema.org/")
akt = Namespace("http://www.aktors.org/ontology/portal#")
vcard = Namespace("http://www.w3.org/2006/vcard/ns#")
g.bind("ex", ex)
g.bind("owl", OWL)
# RDFS Tasks from last time.
g.add((ex.Cade, ex.degreeFrom, ex.University_of_California))
g.add((ex.Emma, ex.degreeFrom, ex.University_of_Valencia))
g.add((ex.Cade, ex.degreeSubject, ex.Biology))
g.add((ex.Emma, ex.degreeSubject, ex.Chemistry))
g.add((ex.University_of_California, RDF.type, ex.University))
g.add((ex.University_of_Valencia, RDF.type, ex.University))
g.add((ex.University, RDFS.subClassOf, ex.Higher_Education_Institution))
g.add((ex.expertise, RDFS.range, ex.Subject))
g.add((ex.expertise, RDFS.domain, FOAF.Person))
g.add((ex.degreeSubject, RDFS.subPropertyOf, ex.expertise))
g.add((ex.graduated, RDFS.range, ex.Higher_Education_Institution))
g.add((ex.graduated, RDFS.domain, FOAF.Person))
g.add((ex.degreeFrom, RDFS.subPropertyOf, ex.graduated))
g.add((ex.Biology, RDFS.label, Literal("Biology", lang="en")))
g.add((ex.Biology, RDFS.label, Literal("La Biologie", lang="fr")))
g.add((ex.Biology, RDFS.comment, Literal("Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, evolution, distribution, identification and taxonomy.")))
g.add((ex.Chemistry, RDFS.label, Literal("Chemistry", lang="en")))
g.add((ex.Chemistry, RDFS.label, Literal("La Chimie", lang="fr")))
g.add((ex.Chemistry, RDFS.comment, Literal("Chemistry is a branch of physical science that studies the composition, structure, properties and change of matter.", lang="en")))
# Write OWL triples here
</syntaxhighlight>
'''Turtle'''
'''Turtle'''
<syntaxhighlight>
<syntaxhighlight>
@prefix ex: <http://example.org/> .
@prefix ex: <http://example/org#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
 
ex:Cade ex:degreeFrom ex:University_of_California ;
    ex:degreeSubject ex:Biology .
 
ex:Emma ex:degreeFrom ex:University_of_Valencia ;
    ex:degreeSubject ex:Chemistry .
 
ex:degreeFrom rdfs:subPropertyOf ex:graduated .
 
ex:degreeSubject rdfs:subPropertyOf ex:expertise .
 
ex:Biology rdfs:label "Biology"@en,
        "La Biologie"@fr ;
    rdfs:comment "Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, evolution, distribution, identification and taxonomy." .
 
ex:Chemistry rdfs:label "Chemistry"@en,
        "La Chimie"@fr ;
    rdfs:comment "Chemistry is a branch of physical science that studies the composition, structure, properties and change of matter."@en .
 
ex:University_of_California a ex:University .
 
ex:University_of_Valencia a ex:University .
 
ex:expertise rdfs:domain <http://xmlns.com/foaf/0.1/Person> ;
    rdfs:range ex:Subject .


ex:graduated rdfs:domain <http://xmlns.com/foaf/0.1/Person> ;
ex:Mueller_Investigation ex:involved ex:George_Papadopoulos,
     rdfs:range ex:Higher_Education_Institution .
        ex:Michael_Cohen,
        ex:Michael_Flynn,
        ex:Paul_Manafort,
        ex:Rick_Gates,
        ex:Roger_Stone ;
     ex:leadBy ex:Robert_Mueller .


ex:University rdfs:subClassOf ex:Higher_Education_Institution .
ex:Michael_Cohen ex:attorneyFor ex:Donald_Trump ;
    ex:pleadedGuilty ex:Michael_Cohens_Lying .


ex:Cade a foaf:Person ;
ex:Michael_Cohens_Lying a ex:Lying ;
    ex:address [ a ex:Address ;
     ex:wasLyingAbout ex:Trump_RealEstateDeal ;
            ex:city ex:Berkeley ;
     ex:wasLyingTo ex:Congress .
            ex:country ex:USA ;
            ex:postalCode "94709"^^xsd:string ;
            ex:state ex:California ;
            ex:street "1516_Henry_Street"^^xsd:string ] ;
    ex:age 27 ;
    ex:characteristic ex:Kind ;
    ex:degree [ ex:degreeField ex:Biology ;
            ex:degreeLevel "Bachelor"^^xsd:string ;
            ex:degreeSource ex:University_of_California ;
            ex:year "2011-01-01"^^xsd:gYear ] ;
    ex:interest ex:Bird,
        ex:Ecology,
        ex:Environmentalism,
        ex:Photography,
        ex:Travelling ;
     ex:married ex:Mary ;
     ex:meeting ex:Meeting1 ;
    ex:visit ex:Canada,
        ex:France,
        ex:Germany ;
    foaf:knows ex:Emma ;
    ex:name "Cade_Tracey"^^xsd:string .


ex:Mary a ex:Student;
ex:Michael_Flynn ex:adviserTo ex:Donald_Trump ;
    ex:age 26 ;
     ex:negotiatedAgreement ex:PleaAgreement ;
     ex:characteristic ex:Kind ;
     ex:pleadedGuilty ex:Michael_Flynns_Lying .
     ex:interest ex:Biology,
        ex:Chocolate,
        ex:Hiking .


ex:Emma a foaf:Person ;
ex:Michael_Flynns_Lying a ex:Lying ;
    ex:address [ a ex:Address ;
     ex:wasLyingTo ex:FBI .
            ex:city ex:Valencia ;
            ex:country ex:Spain ;
            ex:postalCode "46020"^^xsd:string ;
            ex:street "Carrer_de_la Guardia_Civil_20"^^xsd:string ] ;
     ex:age 26 ;
    ex:degree [ ex:degreeField ex:Chemistry ;
            ex:degreeLevel "Master"^^xsd:string ;
            ex:degreeSource ex:University_of_Valencia ;
            ex:year "2015-01-01"^^xsd:gYear ] ;
    ex:expertise ex:Air_Pollution,
        ex:Toxic_Waste,
        ex:Waste_Management,
        ex:Bananas ;
    ex:interest ex:Bike_Riding,
        ex:Music,
        ex:Travelling ;
    ex:meeting ex:Meeting1 ;
    ex:visit ( ex:Portugal ex:Italy ex:France ex:Germany ex:Denmark ex:Sweden ) ;
    ex:name "Emma_Dominguez"^^xsd:string .


ex:Meeting1 a ex:Meeting ;
ex:Paul_Manafort ex:campaignManager ex:Donald_Trump ;
     ex:date "August, 2014"^^xsd:string ;
     ex:chargedWith ex:ForeignLobbying,
     ex:involved ex:Cade,
        ex:MoneyLaundering,
        ex:Emma ;
        ex:TaxEvasion ;
     ex:location ex:Paris .
    ex:convictedFor ex:BankAndTaxFraud ;
    ex:hasBusinessPartner ex:Rick_Gates ;
     ex:negotiatedAgreement ex:PleaAgreement ;
    ex:pleadedGuilty ex:Conspiracy ;
     ex:sentencedTo ex:Prison .


ex:Paris a ex:City ;
ex:Rick_Gates_Lying a ex:Lying ;
     ex:capitalOf ex:France ;
     ex:wasLyingTo ex:FBI .
    ex:locatedIn ex:France .


ex:France ex:capital ex:Paris .
ex:Rick_Gates ex:chargedWith ex:ForeignLobbying,
        ex:MoneyLaundering,
        ex:TaxEvasion ;
    ex:pleadedGuilty ex:Conspiracy,
        ex:Rick_Gates_Lying .
</syntaxhighlight>
</syntaxhighlight>

Revision as of 14:07, 12 March 2023

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. .
  • 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.
  • Harder: Someone who supports a Republican politician is 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:hasPpresident 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

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 .
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