SlideShare uma empresa Scribd logo
1 de 41
Baixar para ler offline
OWL Full Semantics
      -- RDF-Compatible Model-Theoretic Semantics

by Peter F. Patel-Schneider, Patrick Hayes and Ian Horrocks
               W3C Recommendation, 2004

     http://www.w3.org/TR/owl-semantics/rdfs.html


                     Presented by Jie Bao
                             RPI
                        Sept 11, 2008

               Part 2 of RDF/OWL Semantics Tutorial
    http://tw.rpi.edu/wiki/index.php/RDF_and_OWL_Semantics
Disclaimer
• The semantics and inference rules about RDFS
  Plus /RDFS 3.0 are rolely Jie Bao’s own and do
  not reflect the positions of either W3C (or any
  of its working group) or any of the RDFS Plus
  /RDF 3.0 proposals (citation on the page RDFS
  Plus: a Rule Subset of OWL ).




                                                    2
A Layer Cake of Languages

         OWL2

          OWL               You
                            Are
                            Here

       (RDFS Plus)

         RDF(S)
                                   3
Not Covered in the Talk
•   Datatype
•   Annotation
•   Ontology house keeping (e.g., imports)
•   OWL comprehension conditions




                                             4
Outline
•   Review of RDF Semantics
•   OWL Overview
•   RDFS 3.0 Semantics
•   OWL Full Universe
•   OWL Full Interpretation Conditions




                                         5
RDF(S) Vocabulary
RDF                         RDFS
rdf:type                    rdfs:domain
rdf:Property                rdfs:range
                            rdfs:Resource
                            rdfs:Class
                            rdfs:subClassOf
                            rdfs:subPropertyOf

… others (rectification, annotation, literal,
collection, container)
                                                 6
RDFS Interpretation
V   vocabulary

                                     extension of classes

             IS
                                                ICEXT

    rdf:Property
                    IP                              IC
                                  IEXT                  rdfs:Class
                   IR
              rdfs:Resource

                                 IR x IR                             7
                              extension of properties
Outline
•   Review of RDF Semantics
•   OWL Overview
•   RDFS Plus Semantics
•   OWL Full Universe
•   OWL Full Interpretation Conditions




                                         8
OWL Family

       OWL Full

        OWL DL
      (SHOIN(D))

       OWL Lite
       (SHIF(D))

RDFS Plus (or RDFS 3.0)

                          9
From RDF to OWL 2 Full
             OWL 2 Full          Covered next time




              RDFS+
              RDFS
  OWL 2 RL                OWL Full
               RDF




                                                     10
OWL Extensions to RDFS
• Constructing classes:
   – e.g., ∀∃ ∧ ∨ ¬
• Constructing properties:
   – e.g., inverseOf
• Property characteristics:
   – e.g., transitive, functional, symmetric
• Mapping
   – Equality, non-equality (between classes, properties, ind.)



                                                                  11
Direct MT Sem. vs RDF MT Sem.
• Direct Model-Theoretical Semantics
  – For OWL DL (thus also OWL Lite)
  – Simpler than the RDF MT Semantics
  – Corresponds to the semantics of DL SHOIN(D)
  – Decidability guaranteed

• RDF-Compatible Model-Theoretical Semantics
  – For OWL Full (thus also OWL DL and OWL Lite)
  – Extends RDFS Semantics
                                                   12
Outline
•   Review of RDF Semantics
•   OWL Overview
•   RDFS Plus Semantics
•   OWL Full Universe
•   OWL Full Interpretation Conditions




                                         13
RDFS Plus: a Rule Subset of OWL
Design intuition: Scalable, easier to implement
 using rule inference

• RDFS Plus / OWL Prime / RDFS 3.0
  – Dean Allemang, James Hendler. Semantic Web for the Working
    Ontologist, Chapter 7
  – Oracle: OWL Prime http://www.w3.org/2007/OWL/wiki/OracleOwlPrime
• Related proposals
  – AllegroGraph RDFS++:
    http://agraph.franz.com/support/learning/Overview-of-RDFS++.lhtml
  – OWL 2 RL http://www.w3.org/2007/OWL/wiki/Profiles#OWL_2_RL
                                                                        14
RDFS Plus Vocabulary
       Equality            Property Characteristics
owl:equivalentClass,      owl:inverseOf
owl:equivalentProperty,   owl:TransitiveProperty,
owl:sameAs                owl:SymmetricProperty,
                          owl:FuncionalProperty,
                          owl:InverseFunctionalProperty
                          owl:ObjectProperty,
                          owl:DatatypeProperty


+ RDFS vocabulary

                                                          15
RDFS Plus Semantics
         If E is                         then
                       IS(E) ∈IC and IEXT (IS (E))=IOOP
owl:ObjectProperty
                       ⊆IEXT(IP)
                       IS(E) ∈IC and IEXT (IS (E))=IODP
owl:DatatypeProperty
                       ⊆IEXT(IP)
                       ⊆
         If E is                       ∈
                             then <x,y>∈IEXT (IS (E)) iff
owl:equivalentClass    x,y∈IC and ICEXT(x)=ICEXT(y)
owl:equivalentProperty x,y∈IOOP∪IODP and IEXT (x) = IEXT (y)
owl:sameAs             x=y
                                                               16
RDFS Plus Semantics
            If E is                           ∈
                                        then c∈ICEXT (IS (E)) iff
                                         ∈                       ∈
                             <x,y>, <y,z>∈IEXT (c) implies <x,z>∈IEXT (c)
owl:TransitiveProperty
                             and c ∈IOOP
                             <x,y> ∈ IEXT (c) implies <y, x>∈IEXT (c)
                                                            ∈
owl:SymmetricProperty
                             and c ∈IOOP
                             <x,y1>, <x,y2> ∈ IEXT (c) implies y1 = y2
owl:FuncionalProperty
                             and c∈IOOP ∪ IODP
                                           ∈
                             <x ,y>, <x2,y>∈IEXT (c) implies x1 = x2
owl:InverseFunctionalProperty 1
                             and c∈IOOP
            If E is                             ∈
                                      then <x,y>∈IEXT (IS(E)) iff
owl:inverseOf                 x,y∈IOOP and <u,v>∈IEXT (x) iff <v,u>∈IEXT (y)
                                                ∈                  ∈

                                                                            17
RDFS Plus Semantics

                   Extensional Semantic Conditions
                                                  c, d ∈ IC,
<c,d> ∈ IEXT(IS(rdfs:subClassOf))
                                                  ICEXT(c) ⊆ ICEXT(d)
                                                  p, q ∈ IP,
<p,q> ∈ IEXT(IS(rdfs:subPropertyOf))
                                                  IEXT(p) ⊆ IEXT(q)
                                           Iff*
                                                  p ∈ IP, c ∈ IC,
<p,c> ∈ IEXT(IS(rdfs:domain))
                                                  <x,y> ∈ IEXT(p) → x ∈ ICEXT(c)
                                                  p ∈ IP, c ∈ IC,
<p,c> ∈ IEXT(IS(rdfs:range))
                                                  <x,y> ∈ IEXT(p) → y ∈ ICEXT(c)

 * By default, RDFS uses “only if”, OWL 1 Full and OWL 2 Full uses “iff”


                                                                                   18
Inference Rules
Some examples:
                     If                                         then
 (?x, owl:sameAs, ?y)                      (?y, owl:sameAs, ?x)
 (?c1, owl:equivalentClass, ?c2)
                                           (?x, rdf:type, ?c2)
 (?x, rdf:type, ?c1)
 (?p, rdf:type, owl:FunctionalProperty)
                                           (?y1, owl:sameAs, ?y2)
 (?x, ?p, ?y1) T(?x, ?p, ?y2)
 (?p1, owl:inverseOf, ?p2) (?x, ?p1, ?y)   (?y, ?p2, ?x)
 (?p, rdfs:domain, ?c) (?x, ?p, ?y)        (?x, rdf:type, ?c)


Complete rule set is in backup slides

                                                                       19
Outline
•   Review of RDF Semantics
•   OWL Overview
•   RDFS Plus Semantics
•   OWL Full Universe
•   OWL Full Interpretation Conditions




                                         20
OWL Vocabulary
         Classes                  Class Construction
owl:Class                  owl:complementOf




                                                       Boolean
owl:Thing                  owl:intersectionOf
owl:Nothing                owl:unionOf
owl:Restriction




                                                       qualification
                                                       qualification cardinality
                           owl:allValuesFrom
owl:onProperty             owl:someValuesFrom
      Non-equality         owl:hasValue
owl:differentFrom          owl:cardinality
owl:disjointWith           owl:minCardinality
owl:AllDifferent           owl:maxCardinality
owl:distinctMembers
                           owl:oneOf
                   + RDFS Plus vocabulary
                                                                                   21
Recall: RDFS Interpretation
V   vocabulary

                                     extension of classes

             IS
                                                ICEXT

    rdf:Property
                    IP                              IC
                                  IEXT                  rdfs:Class
                   IR
              rdfs:Resource

                                 IR x IR                             22
                              extension of properties
OWL Full Interpretation
         V   vocabulary

                                                 extension of classes

                          IS
                                                            ICEXT
rdf:Property =
{owl:ObjectProperty,
owl:DatatypeProperty,           IP                              IC
owl:AnnotationProperty,
owl:OntologyProperty}
                                              IEXT                  rdfs:Class
                               IR                                   =owl:Class
                          rdfs:Resource
                          =owl:Thing
                                             IR x IR                             23
                                          extension of properties
OWL Full vs OWL DL
                OWL-DL                          OWL Full
Relation to   owl:Thing <=rdfs:Resource         owl:Thing = rdfs:Resource
RDFS universe owl:Class <= rdfs:Class           owl:Class = rdfs:Class
              P <= rdf:Property                 P = rdf:Property
Pairwise        Yes                             No
Disjointness
Decidability    Yes                             No


P is the union of owl:ObjectProperty, owl:DatatypeProperty,
owl:AnnotationProperty, and owl:OntologyProperty

Note: in OWL Full, an element can be an individual (owl:Thing element), a
class (owl:Class element) and an property (P element) at the same time.

                                                                            24
True or False?
In OWL Full
•   owl:Thing               rdfs:subClassOf             owl:Class
•   owl:Class               rdfs:subClassOf             owl:Thing
•   owl:Thing               rdf:type                    owl:Class
•   owl:Class               rdf:type                    owl:Class
•   rdf:Property            rdf:type                    owl:Class


Refer:
•   OWL RDF Schema: http://www.w3.org/2002/07/owl
•   Thing and Class: http://ontolog.cim3.net/forum/ontolog-forum/2008-
    09/threads.html#00004

                                                                         25
Outline
•   Review of RDF Semantics
•   OWL Overview
•   RDFS Plus Semantics
•   OWL Full Universe
•   OWL Full Interpretation Conditions




                                         26
OWL Classes and Properties
                                      then
    If E is
                         ∈
                   IS (E)∈        ICEXT(IS (E))=             and
owl:Class            IC                  IOC               IOC=IC

owl:Thing           IOC                  IOT        IOT=IR and IOT ≠ ∅

owl:Nothing         IOC                  {}


                             ∈
                    then if e∈ICEXT(IS
        If E is                                       Note
                        (E)) then
                                         Instances of OWL classes are OWL
owl:Class         ICEXT (e)⊆IOT
                                         individuals.
                                         Values for individual-valued
owl:ObjectProperty IEXT (e)⊆IOT×IOT
                                         properties are OWL individuals.

                                                                            27
Boolean Operations and Enumeration
              If E is                            ∈
                                       then <x,y>∈IEXT(IS (E)) iff
 owl:complementOf             x,y∈ IOC and ICEXT(x)=IOT-ICEXT(y)
                              x∈IOC and y is a sequence of y1,…yn over IOC
 owl:unionOf
                              and ICEXT(x) = ICEXT(y1) ∪…∪ ICEXT(yn)
                              x∈IOC and y is a sequence of y1,…yn over IOC
 owl:intersectionOf
                              and ICEXT(x) = ICEXT(y1) ∩…∩ ICEXT(yn)
                              x∈IC and y is a sequence of y1,…yn over IOT or
 owl:oneOf
                              over ILV and ICEXT(x) = {y1,..., yn}

    If E is                  and                           ∈
                                              then if <x,l>∈IEXT(IS (E)) then
                 l is a sequence of y1,…yn
  owl:oneOf                                  x∈IOC
                 over IOT

                                                                                28
Restriction (Anonymous Class)
                                                      then
       If E is
                             IS(E)∈               ICEXT(IS(E))=           and
owl:Restriction      IC                     IOR                    IOR⊆IOC
            If E is and
       <x,y>∈IEXT(IS(E))) ∧
            ∈                        then x∈IOR, y∈IOC, p∈IOOP, and ICEXT(x) =
                                            ∈       ∈      ∈
<x,p>∈IEXT(IS(owl:onProperty)))
      ∈
owl:allValuesFrom                {u∈IOT | <u,v>∈IEXT(p) implies v∈ICEXT(y) }
owl:someValuesFrom               {u∈IOT | ∃ <u,v>∈IEXT(p) such that v∈ICEXT(y) }
                                     then x∈IOR, y∈IOT, p∈IOOP, and ICEXT(x) =
                                            ∈       ∈      ∈
owl:hasValue                     {u∈IOT | <u, y>∈IEXT(p) }
                                  then x∈IOR, y is a non-negative integer, p∈IOOP,
                                         ∈                                   ∈
                                                     and ICEXT(x) =
owl:minCardinality               {u∈IOT | card({v ∈ IOT : <u,v>∈IEXT(p)}) ≥ y }
owl:maxCardinality, owl:cardinality defined similarly
Note: Content on this page is simplified by omitting datatype properties
                                                                                29
Non-equality
        If E is                             ∈
                                  then <x,y>∈IEXT (IS(E)) iff
owl:disjointWith     x,y∈IOC and ICEXT(x)∩ICEXT(y)={}
owl:differentFrom    x≠y


More: Comprehension conditions (which require the existence of
appropriate OWL descriptions and data ranges ) – not covered




                                                                 30
Conclusions
RDFS Plus
• A scalable rule subset of OWL Full, with MT semantics
• Equality + Property Characteristics
• Has extensional semantic conditions (while RDFS has not)

OWL Full
• Extends RDFS Plus, with MT semantics
• OWL Full universe = RDFS universe
    – rdfs:Class = owl:Class ; rdfs:Resource = owl:Thing; owl:ObjectProperty <=
      rdf:Property
• No distinction between classes, properties and individuals

Next talk: OWL 2Full
                                                                                  31
Further Reading
• Ian Horrocks, Peter F. Patel-Schneider, Frank van Harmelen - From SHIQ
  and RDF to OWL: the making of a Web Ontology Language. In J. Web
  Sem. 1(1):7-26, 2003.(URL)
• Turner, David; Carroll, Jeremy J. Comparing OWL Semantics. Technical
  Reports HPL-2007-146. HP Lab, 2007. (URL)




                                                                           32
Backup




         33
Other OWL Vocabulary
• owl:DatatypeProperty, owl:DataRange
• owl:Ontology
• owl:imports, owl:priorVersion, owl:backwardCompatibleWith,
  and owl:incompatibleWith, owl:versionInfo
• owl:OntologyProperty
• owl:DeprecatedClass, owl:DeprecatedProperty
• owl:AnnotationProperty




                                                           34
Exercise
• Prove tautology in RDFS:
  –   rdfs:subPropertyOf rdfs:subPropertyOf rdfs:subPropertyOf
  –   rdfs:domain rdfs:domain rdf:Property
  –   rdfs:doman rdfs:range rdf:Class
  –   rdf:Property rdf:type rdfs:Class
• Prove tautology in OWL Full:
  – owl:sameAs owl:sameAs owl:sameAs




                                                             35
d




                   RDFS Plus Rules (1)
                     If                                   then
                                         (?s, owl:sameAs, ?s)
    (?s, ?p, ?o)                         (?p, owl:sameAs, ?p)
                                         (?o, owl:sameAs, ?o)
    (?x, owl:sameAs, ?y)                 (?y, owl:sameAs, ?x)
    (?x, owl:sameAs, ?y)
                                         (?x, owl:sameAs, ?z)
    (?y, owl:sameAs, ?z)
    (?s, owl:sameAs, ?s‘) (?s, ?p, ?o)   (?s', ?p, ?o)
    (?p, owl:sameAs, ?p‘) (?s, ?p, ?o)   (?s, ?p', ?o)

    (?o, owl:sameAs, ?o‘) (?s, ?p, ?o)   (?s, ?p, ?o')

                                 Equality rules

                                                                 36
RDFS Plus Rules (2)
                    If                                      then
(?c1, owl:equivalentClass, ?c2)
                                           (?x, rdf:type, ?c2)
(?x, rdf:type, ?c1)
(?c1, owl:equivalentClass, ?c2)
                                           (?x, rdf:type, ?c1)
(?x, rdf:type, ?c2)
                                           (?c1, rdfs:subClassOf, ?c2)
(?c1, owl:equivalentClass, ?c2)
                                           (?c2, rdfs:subClassOf, ?c1)
                                           (?p1, rdfs:subPropertyOf, ?p2)
(?p1, owl:equivalentProperty, ?p2)
                                           (?p2, rdfs:subPropertyOf, ?p1)
(?p1, owl:equivalentProperty, ?p2)
                                           (?x, ?p2, ?y)
(?x, ?p1, ?y)
(?p1, owl:equivalentProperty, ?p2)
                                           (?x, ?p1, ?y)
(?x, ?p2, ?y)
                                  Equality rules                            37
RDFS Plus Rules (3)
                       If                                      then
(?p, rdf:type, owl:FunctionalProperty)
                                               (?y1, owl:sameAs, ?y2)
(?x, ?p, ?y1) T(?x, ?p, ?y2)
(?p, rdf:type, owl:InverseFunctionalProperty)
                                              (?x1, owl:sameAs, ?x2)
(?x1, ?p, ?y) T(?x2, ?p, ?y)
(?p, rdf:type, owl:SymmetricProperty)
                                               (?y, ?p, ?x)
(?x, ?p, ?y)
(?p, rdf:type, owl:TransitiveProperty)
                                               (?x, ?p, ?z)
(?x, ?p, ?y) (?y, ?p, ?z)
(?p1, owl:inverseOf, ?p2) (?x, ?p1, ?y)        (?y, ?p2, ?x)
(?p1, owl:inverseOf, ?p2) (?x, ?p2, ?y)        (?y, ?p1, ?x)

                            Property characteristic rules

                                                                        38
RDFS Plus Rules (4)

                       If                                        then
                                              (?c, rdfs:subClassOf, ?c)
(?c, rdf:type, owl:Class)
                                              (?c, owl:equivalentClasses, ?c)
                                              (?p, rdfs:subPropertyOf, ?p)
(?p, rdf:type, owl:ObjectProperty)
                                              (?p, owl:equivalentProperty, ?p)
                                              (?p, rdfs:subPropertyOf, ?p)
(?p, rdf:type, owl:DatatypeProperty)
                                              (?p, owl:equivalentProperty, ?p)

                            OWL Class and Property Declaration




                                                                                 39
RDFS Plus Rules (5)
                        If                                              then
                                                  (?p, rdf:type rdf:Property)
(?x, ?p, ?y)                                      (?x, rdf:type rdfs:Resource)
                                                  (?y, rdf:type rdfs:Resource)
(?p, rdf:type rdf:Property)                       (?p, rdfs:subPropertyOf ?p)
                                                  (?c, rdfs:subClassOf rdfs:Resource)
(?c, rdf:type rdfs:Class)
                                                  (?c, rdfs:subClassOf ?c)
(?p1, rdfs:subPropertyOf, ?p2) (?x, ?p1, ?y)      (?x, ?p2, ?y)
(?c1, rdfs:subClassOf, ?c2) (?x, rdf:type, ?c1)   (?x, rdf:type, ?c2)
(?c1, rdfs:subClassOf, ?c2) (?c2,
                                                  (?c1, rdfs:subClassOf, ?c3)
rdfs:subClassOf, ?c3)
(?p1, rdfs:subPropertyOf, ?p2) (?p2,
                                                  (?p1, rdfs:subPropertyOf, ?p3)
rdfs:subPropertyOf, ?p3)
                                         RDFS Rules
                                                                                        40
RDFS Plus Rules (6)
                                    If                                  then
(?p, rdfs:domain, ?c) (?x, ?p, ?y)                      (?x, rdf:type, ?c)

(?p, rdfs:range, ?c) (?x, ?p, ?y)                       (?y, rdf:type, ?c)

                    Rules due to Extensional Semantic Conditions
(?p, rdfs:domain, ?c1) (?c1, rdfs:subClassOf, ?c2)      (?p, rdfs:domain, ?c2)

(?p2, rdfs:domain, ?c) (?p1, rdfs:subPropertyOf, ?p2)   (?p1, rdfs:domain, ?c)

(?p, rdfs:range, ?c1) (?c1, rdfs:subClassOf, ?c2)       (?p, rdfs:range, ?c2)

(?p2, rdfs:range, ?c) (?p1, rdfs:subPropertyOf, ?p2)    (?p1, rdfs:range, ?c)


                                RDFS Rules (domain & range)



                                                                                 41

Mais conteúdo relacionado

Mais procurados

RDF 개념 및 구문 소개
RDF 개념 및 구문 소개RDF 개념 및 구문 소개
RDF 개념 및 구문 소개Dongbum Kim
 
RDF, SPARQL and Semantic Repositories
RDF, SPARQL and Semantic RepositoriesRDF, SPARQL and Semantic Repositories
RDF, SPARQL and Semantic RepositoriesMarin Dimitrov
 
Introduction to RDF & SPARQL
Introduction to RDF & SPARQLIntroduction to RDF & SPARQL
Introduction to RDF & SPARQLOpen Data Support
 
Getting Started with Knowledge Graphs
Getting Started with Knowledge GraphsGetting Started with Knowledge Graphs
Getting Started with Knowledge GraphsPeter Haase
 
LODAC 2017 Linked Open Data Workshop
LODAC 2017 Linked Open Data WorkshopLODAC 2017 Linked Open Data Workshop
LODAC 2017 Linked Open Data WorkshopMyungjin Lee
 
Semantic Web - Ontologies
Semantic Web - OntologiesSemantic Web - Ontologies
Semantic Web - OntologiesSerge Linckels
 
Debunking some “RDF vs. Property Graph” Alternative Facts
Debunking some “RDF vs. Property Graph” Alternative FactsDebunking some “RDF vs. Property Graph” Alternative Facts
Debunking some “RDF vs. Property Graph” Alternative FactsNeo4j
 
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
 
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -Dongbum Kim
 
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge GraphsESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge GraphsPeter Haase
 
온톨로지 개념 및 표현언어
온톨로지 개념 및 표현언어온톨로지 개념 및 표현언어
온톨로지 개념 및 표현언어Dongbum Kim
 
SHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudSHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudRichard Cyganiak
 
Jena – A Semantic Web Framework for Java
Jena – A Semantic Web Framework for JavaJena – A Semantic Web Framework for Java
Jena – A Semantic Web Framework for JavaAleksander Pohl
 
BLOGIC. (ISWC 2009 Invited Talk)
BLOGIC.  (ISWC 2009 Invited Talk)BLOGIC.  (ISWC 2009 Invited Talk)
BLOGIC. (ISWC 2009 Invited Talk)Pat Hayes
 

Mais procurados (20)

RDF 개념 및 구문 소개
RDF 개념 및 구문 소개RDF 개념 및 구문 소개
RDF 개념 및 구문 소개
 
RDF, SPARQL and Semantic Repositories
RDF, SPARQL and Semantic RepositoriesRDF, SPARQL and Semantic Repositories
RDF, SPARQL and Semantic Repositories
 
Introduction to RDF & SPARQL
Introduction to RDF & SPARQLIntroduction to RDF & SPARQL
Introduction to RDF & SPARQL
 
Getting Started with Knowledge Graphs
Getting Started with Knowledge GraphsGetting Started with Knowledge Graphs
Getting Started with Knowledge Graphs
 
LODAC 2017 Linked Open Data Workshop
LODAC 2017 Linked Open Data WorkshopLODAC 2017 Linked Open Data Workshop
LODAC 2017 Linked Open Data Workshop
 
Semantic Web - Ontologies
Semantic Web - OntologiesSemantic Web - Ontologies
Semantic Web - Ontologies
 
Wordnet
WordnetWordnet
Wordnet
 
Debunking some “RDF vs. Property Graph” Alternative Facts
Debunking some “RDF vs. Property Graph” Alternative FactsDebunking some “RDF vs. Property Graph” Alternative Facts
Debunking some “RDF vs. Property Graph” Alternative Facts
 
OWL and OBO
OWL and OBOOWL and OBO
OWL and OBO
 
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...
 
Introduction to RDF
Introduction to RDFIntroduction to RDF
Introduction to RDF
 
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -
Linked Data의 RDF 어휘 이해하고 체험하기 - FOAF, SIOC, SKOS를 중심으로 -
 
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge GraphsESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge Graphs
 
온톨로지 개념 및 표현언어
온톨로지 개념 및 표현언어온톨로지 개념 및 표현언어
온톨로지 개념 및 표현언어
 
RDF validation tutorial
RDF validation tutorialRDF validation tutorial
RDF validation tutorial
 
The basics of ontologies
The basics of ontologiesThe basics of ontologies
The basics of ontologies
 
SHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudSHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data Mud
 
Jena – A Semantic Web Framework for Java
Jena – A Semantic Web Framework for JavaJena – A Semantic Web Framework for Java
Jena – A Semantic Web Framework for Java
 
SPARQL Tutorial
SPARQL TutorialSPARQL Tutorial
SPARQL Tutorial
 
BLOGIC. (ISWC 2009 Invited Talk)
BLOGIC.  (ISWC 2009 Invited Talk)BLOGIC.  (ISWC 2009 Invited Talk)
BLOGIC. (ISWC 2009 Invited Talk)
 

Destaque

RDF Semantics
RDF SemanticsRDF Semantics
RDF SemanticsJie Bao
 
読解支援@2015 08-10-1
読解支援@2015 08-10-1読解支援@2015 08-10-1
読解支援@2015 08-10-1sekizawayuuki
 
コンセプトアイデア 1
コンセプトアイデア 1コンセプトアイデア 1
コンセプトアイデア 1Jun Saeki
 
Semantic Versioning
Semantic VersioningSemantic Versioning
Semantic VersioningKosuke Usami
 
OWLで何が言えるか
OWLで何が言えるかOWLで何が言えるか
OWLで何が言えるかKazuro Fukuhara
 
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)Ikki Ohmukai
 
パターン認識にとっかかる
パターン認識にとっかかるパターン認識にとっかかる
パターン認識にとっかかるJun Saeki
 
セマンティック・ウェブのためのRdf owl入門解説.ch5
セマンティック・ウェブのためのRdf owl入門解説.ch5セマンティック・ウェブのためのRdf owl入門解説.ch5
セマンティック・ウェブのためのRdf owl入門解説.ch5Takahiro Kubo
 
python-graph-lovestory
python-graph-lovestorypython-graph-lovestory
python-graph-lovestoryJie Bao
 
Semantic Web Technologies -metadata, ontology, logic, agent-
Semantic Web Technologies -metadata, ontology, logic, agent-Semantic Web Technologies -metadata, ontology, logic, agent-
Semantic Web Technologies -metadata, ontology, logic, agent-blanc_et_noir
 
OWLで何が書けるか
OWLで何が書けるかOWLで何が書けるか
OWLで何が書けるかKazuro Fukuhara
 
オントロジー工学に基づく 知識の体系化と利用
オントロジー工学に基づく知識の体系化と利用オントロジー工学に基づく知識の体系化と利用
オントロジー工学に基づく 知識の体系化と利用Kouji Kozaki
 
トーナメントは運か実力か
トーナメントは運か実力かトーナメントは運か実力か
トーナメントは運か実力かKazuro Fukuhara
 
RDF/OWLの概要及びOSS実装、及び活用イメージについて
RDF/OWLの概要及びOSS実装、及び活用イメージについてRDF/OWLの概要及びOSS実装、及び活用イメージについて
RDF/OWLの概要及びOSS実装、及び活用イメージについてMasayuki Isobe
 
セマンティック・ウェブのためのRdf owl入門1&2章
セマンティック・ウェブのためのRdf owl入門1&2章セマンティック・ウェブのためのRdf owl入門1&2章
セマンティック・ウェブのためのRdf owl入門1&2章Jun Saeki
 
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)Ikki Ohmukai
 
オープンソースを用いたドローンの自律制御ソフトウェア技術
オープンソースを用いたドローンの自律制御ソフトウェア技術オープンソースを用いたドローンの自律制御ソフトウェア技術
オープンソースを用いたドローンの自律制御ソフトウェア技術Masayuki Isobe
 

Destaque (20)

RDF Semantics
RDF SemanticsRDF Semantics
RDF Semantics
 
読解支援@2015 08-10-1
読解支援@2015 08-10-1読解支援@2015 08-10-1
読解支援@2015 08-10-1
 
コンセプトアイデア 1
コンセプトアイデア 1コンセプトアイデア 1
コンセプトアイデア 1
 
Semantic Versioning
Semantic VersioningSemantic Versioning
Semantic Versioning
 
セマンティックWebとオントロジー:現状と将来展望
セマンティックWebとオントロジー:現状と将来展望 セマンティックWebとオントロジー:現状と将来展望
セマンティックWebとオントロジー:現状と将来展望
 
SnapKit
SnapKitSnapKit
SnapKit
 
OWLで何が言えるか
OWLで何が言えるかOWLで何が言えるか
OWLで何が言えるか
 
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)
オープンデータとLinked Open Data@筑波大学研究談話会(2013.12.18)
 
パターン認識にとっかかる
パターン認識にとっかかるパターン認識にとっかかる
パターン認識にとっかかる
 
セマンティック・ウェブのためのRdf owl入門解説.ch5
セマンティック・ウェブのためのRdf owl入門解説.ch5セマンティック・ウェブのためのRdf owl入門解説.ch5
セマンティック・ウェブのためのRdf owl入門解説.ch5
 
python-graph-lovestory
python-graph-lovestorypython-graph-lovestory
python-graph-lovestory
 
Semantic Web Technologies -metadata, ontology, logic, agent-
Semantic Web Technologies -metadata, ontology, logic, agent-Semantic Web Technologies -metadata, ontology, logic, agent-
Semantic Web Technologies -metadata, ontology, logic, agent-
 
OWLで何が書けるか
OWLで何が書けるかOWLで何が書けるか
OWLで何が書けるか
 
オントロジー工学に基づく 知識の体系化と利用
オントロジー工学に基づく知識の体系化と利用オントロジー工学に基づく知識の体系化と利用
オントロジー工学に基づく 知識の体系化と利用
 
トーナメントは運か実力か
トーナメントは運か実力かトーナメントは運か実力か
トーナメントは運か実力か
 
RDF/OWLの概要及びOSS実装、及び活用イメージについて
RDF/OWLの概要及びOSS実装、及び活用イメージについてRDF/OWLの概要及びOSS実装、及び活用イメージについて
RDF/OWLの概要及びOSS実装、及び活用イメージについて
 
セマンティック・ウェブのためのRdf owl入門1&2章
セマンティック・ウェブのためのRdf owl入門1&2章セマンティック・ウェブのためのRdf owl入門1&2章
セマンティック・ウェブのためのRdf owl入門1&2章
 
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)
ビジネスで使えるオープンデータの技術@ビジネス活用のためのオープンデータセミナー(2016.01.22)
 
RDF Semantic Graph「RDF 超入門」
RDF Semantic Graph「RDF 超入門」RDF Semantic Graph「RDF 超入門」
RDF Semantic Graph「RDF 超入門」
 
オープンソースを用いたドローンの自律制御ソフトウェア技術
オープンソースを用いたドローンの自律制御ソフトウェア技術オープンソースを用いたドローンの自律制御ソフトウェア技術
オープンソースを用いたドローンの自律制御ソフトウェア技術
 

Semelhante a OWL Full Semantics

Semantic Modelling using Semantic Web Technology
Semantic Modelling using Semantic Web TechnologySemantic Modelling using Semantic Web Technology
Semantic Modelling using Semantic Web TechnologyRinke Hoekstra
 
Vu Semantic Web Meeting 20091123
Vu Semantic Web Meeting 20091123Vu Semantic Web Meeting 20091123
Vu Semantic Web Meeting 20091123Rinke Hoekstra
 
Ontologies and Vocabularies
Ontologies and VocabulariesOntologies and Vocabularies
Ontologies and Vocabulariesseanb
 
cade23-schneidsut-atp4owlfull-2011
cade23-schneidsut-atp4owlfull-2011cade23-schneidsut-atp4owlfull-2011
cade23-schneidsut-atp4owlfull-2011Michael Schneider
 
A Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebA Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebShamod Lacoul
 
A year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CA year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CIvan Herman
 
RSP-QL*: Querying Data-Level Annotations in RDF Streams
RSP-QL*: Querying Data-Level Annotations in RDF StreamsRSP-QL*: Querying Data-Level Annotations in RDF Streams
RSP-QL*: Querying Data-Level Annotations in RDF Streamskeski
 
POSH: The Prolog OWL Shell
POSH: The Prolog OWL ShellPOSH: The Prolog OWL Shell
POSH: The Prolog OWL ShellChris Mungall
 
Semantic web
Semantic webSemantic web
Semantic webtariq1352
 
SWRL2SPIN: Converting SWRL to SPIN
SWRL2SPIN: Converting SWRL to SPINSWRL2SPIN: Converting SWRL to SPIN
SWRL2SPIN: Converting SWRL to SPINNick Bassiliades
 
A Semantic Multimedia Web (Part 2)
A Semantic Multimedia Web (Part 2)A Semantic Multimedia Web (Part 2)
A Semantic Multimedia Web (Part 2)Raphael Troncy
 

Semelhante a OWL Full Semantics (20)

Semantic Modelling using Semantic Web Technology
Semantic Modelling using Semantic Web TechnologySemantic Modelling using Semantic Web Technology
Semantic Modelling using Semantic Web Technology
 
Vu Semantic Web Meeting 20091123
Vu Semantic Web Meeting 20091123Vu Semantic Web Meeting 20091123
Vu Semantic Web Meeting 20091123
 
BT02.pptx
BT02.pptxBT02.pptx
BT02.pptx
 
Ontologies and Vocabularies
Ontologies and VocabulariesOntologies and Vocabularies
Ontologies and Vocabularies
 
cade23-schneidsut-atp4owlfull-2011
cade23-schneidsut-atp4owlfull-2011cade23-schneidsut-atp4owlfull-2011
cade23-schneidsut-atp4owlfull-2011
 
Semantic web Technology
Semantic web TechnologySemantic web Technology
Semantic web Technology
 
eswc2011phd-schneid
eswc2011phd-schneideswc2011phd-schneid
eswc2011phd-schneid
 
A Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic WebA Hands On Overview Of The Semantic Web
A Hands On Overview Of The Semantic Web
 
RDF briefing
RDF briefingRDF briefing
RDF briefing
 
A year on the Semantic Web @ W3C
A year on the Semantic Web @ W3CA year on the Semantic Web @ W3C
A year on the Semantic Web @ W3C
 
OWL briefing
OWL briefingOWL briefing
OWL briefing
 
RSP-QL*: Querying Data-Level Annotations in RDF Streams
RSP-QL*: Querying Data-Level Annotations in RDF StreamsRSP-QL*: Querying Data-Level Annotations in RDF Streams
RSP-QL*: Querying Data-Level Annotations in RDF Streams
 
POSH: The Prolog OWL Shell
POSH: The Prolog OWL ShellPOSH: The Prolog OWL Shell
POSH: The Prolog OWL Shell
 
Sparql
SparqlSparql
Sparql
 
Semantic web
Semantic webSemantic web
Semantic web
 
Lec 3.pdf
Lec 3.pdfLec 3.pdf
Lec 3.pdf
 
SWRL2SPIN: Converting SWRL to SPIN
SWRL2SPIN: Converting SWRL to SPINSWRL2SPIN: Converting SWRL to SPIN
SWRL2SPIN: Converting SWRL to SPIN
 
eureka09
eureka09eureka09
eureka09
 
eureka09
eureka09eureka09
eureka09
 
A Semantic Multimedia Web (Part 2)
A Semantic Multimedia Web (Part 2)A Semantic Multimedia Web (Part 2)
A Semantic Multimedia Web (Part 2)
 

Mais de Jie Bao

unix toolbox 中文版
unix toolbox 中文版unix toolbox 中文版
unix toolbox 中文版Jie Bao
 
unixtoolbox.book
unixtoolbox.bookunixtoolbox.book
unixtoolbox.bookJie Bao
 
Lean startup 精益创业 新创企业的成长思维
Lean startup 精益创业 新创企业的成长思维Lean startup 精益创业 新创企业的成长思维
Lean startup 精益创业 新创企业的成长思维Jie Bao
 
Towards social webtops using semantic wiki
Towards social webtops using semantic wikiTowards social webtops using semantic wiki
Towards social webtops using semantic wikiJie Bao
 
Semantic information theory in 20 minutes
Semantic information theory in 20 minutesSemantic information theory in 20 minutes
Semantic information theory in 20 minutesJie Bao
 
Towards a theory of semantic communication
Towards a theory of semantic communicationTowards a theory of semantic communication
Towards a theory of semantic communicationJie Bao
 
Expressive Query Answering For Semantic Wikis (20min)
Expressive Query Answering For  Semantic Wikis (20min)Expressive Query Answering For  Semantic Wikis (20min)
Expressive Query Answering For Semantic Wikis (20min)Jie Bao
 
Startup best practices
Startup best practicesStartup best practices
Startup best practicesJie Bao
 
Owl 2 quick reference card a4 size
Owl 2 quick reference card a4 sizeOwl 2 quick reference card a4 size
Owl 2 quick reference card a4 sizeJie Bao
 
ISWC 2010 Metadata Work Summary
ISWC 2010 Metadata Work SummaryISWC 2010 Metadata Work Summary
ISWC 2010 Metadata Work SummaryJie Bao
 
Expressive Query Answering For Semantic Wikis
Expressive Query Answering For  Semantic WikisExpressive Query Answering For  Semantic Wikis
Expressive Query Answering For Semantic WikisJie Bao
 
24 Ways to Explore ISWC 2010 Data
24 Ways to Explore ISWC 2010 Data24 Ways to Explore ISWC 2010 Data
24 Ways to Explore ISWC 2010 DataJie Bao
 
Semantic Web: In Quest for the Next Generation Killer Apps
Semantic Web: In Quest for the Next Generation Killer AppsSemantic Web: In Quest for the Next Generation Killer Apps
Semantic Web: In Quest for the Next Generation Killer AppsJie Bao
 
Representing financial reports on the semantic web a faithful translation f...
Representing financial reports on the semantic web   a faithful translation f...Representing financial reports on the semantic web   a faithful translation f...
Representing financial reports on the semantic web a faithful translation f...Jie Bao
 
XACML 3.0 (Partial) Concept Map
XACML 3.0 (Partial) Concept MapXACML 3.0 (Partial) Concept Map
XACML 3.0 (Partial) Concept MapJie Bao
 
Development of a Controlled Natural Language Interface for Semantic MediaWiki
Development of a Controlled Natural Language Interface for Semantic MediaWikiDevelopment of a Controlled Natural Language Interface for Semantic MediaWiki
Development of a Controlled Natural Language Interface for Semantic MediaWikiJie Bao
 
Digital image self-adaptive acquisition in medical x-ray imaging
Digital image self-adaptive acquisition in medical x-ray imagingDigital image self-adaptive acquisition in medical x-ray imaging
Digital image self-adaptive acquisition in medical x-ray imagingJie Bao
 
Privacy-Preserving Reasoning on the Semantic Web (Poster)
Privacy-Preserving Reasoning on the Semantic Web (Poster)Privacy-Preserving Reasoning on the Semantic Web (Poster)
Privacy-Preserving Reasoning on the Semantic Web (Poster)Jie Bao
 
Privacy-Preserving Reasoning on the Semantic Web
Privacy-Preserving Reasoning on the Semantic WebPrivacy-Preserving Reasoning on the Semantic Web
Privacy-Preserving Reasoning on the Semantic WebJie Bao
 

Mais de Jie Bao (20)

unix toolbox 中文版
unix toolbox 中文版unix toolbox 中文版
unix toolbox 中文版
 
unixtoolbox.book
unixtoolbox.bookunixtoolbox.book
unixtoolbox.book
 
Lean startup 精益创业 新创企业的成长思维
Lean startup 精益创业 新创企业的成长思维Lean startup 精益创业 新创企业的成长思维
Lean startup 精益创业 新创企业的成长思维
 
Towards social webtops using semantic wiki
Towards social webtops using semantic wikiTowards social webtops using semantic wiki
Towards social webtops using semantic wiki
 
Semantic information theory in 20 minutes
Semantic information theory in 20 minutesSemantic information theory in 20 minutes
Semantic information theory in 20 minutes
 
Towards a theory of semantic communication
Towards a theory of semantic communicationTowards a theory of semantic communication
Towards a theory of semantic communication
 
Expressive Query Answering For Semantic Wikis (20min)
Expressive Query Answering For  Semantic Wikis (20min)Expressive Query Answering For  Semantic Wikis (20min)
Expressive Query Answering For Semantic Wikis (20min)
 
Startup best practices
Startup best practicesStartup best practices
Startup best practices
 
Owl 2 quick reference card a4 size
Owl 2 quick reference card a4 sizeOwl 2 quick reference card a4 size
Owl 2 quick reference card a4 size
 
ISWC 2010 Metadata Work Summary
ISWC 2010 Metadata Work SummaryISWC 2010 Metadata Work Summary
ISWC 2010 Metadata Work Summary
 
Expressive Query Answering For Semantic Wikis
Expressive Query Answering For  Semantic WikisExpressive Query Answering For  Semantic Wikis
Expressive Query Answering For Semantic Wikis
 
CV
CVCV
CV
 
24 Ways to Explore ISWC 2010 Data
24 Ways to Explore ISWC 2010 Data24 Ways to Explore ISWC 2010 Data
24 Ways to Explore ISWC 2010 Data
 
Semantic Web: In Quest for the Next Generation Killer Apps
Semantic Web: In Quest for the Next Generation Killer AppsSemantic Web: In Quest for the Next Generation Killer Apps
Semantic Web: In Quest for the Next Generation Killer Apps
 
Representing financial reports on the semantic web a faithful translation f...
Representing financial reports on the semantic web   a faithful translation f...Representing financial reports on the semantic web   a faithful translation f...
Representing financial reports on the semantic web a faithful translation f...
 
XACML 3.0 (Partial) Concept Map
XACML 3.0 (Partial) Concept MapXACML 3.0 (Partial) Concept Map
XACML 3.0 (Partial) Concept Map
 
Development of a Controlled Natural Language Interface for Semantic MediaWiki
Development of a Controlled Natural Language Interface for Semantic MediaWikiDevelopment of a Controlled Natural Language Interface for Semantic MediaWiki
Development of a Controlled Natural Language Interface for Semantic MediaWiki
 
Digital image self-adaptive acquisition in medical x-ray imaging
Digital image self-adaptive acquisition in medical x-ray imagingDigital image self-adaptive acquisition in medical x-ray imaging
Digital image self-adaptive acquisition in medical x-ray imaging
 
Privacy-Preserving Reasoning on the Semantic Web (Poster)
Privacy-Preserving Reasoning on the Semantic Web (Poster)Privacy-Preserving Reasoning on the Semantic Web (Poster)
Privacy-Preserving Reasoning on the Semantic Web (Poster)
 
Privacy-Preserving Reasoning on the Semantic Web
Privacy-Preserving Reasoning on the Semantic WebPrivacy-Preserving Reasoning on the Semantic Web
Privacy-Preserving Reasoning on the Semantic Web
 

Último

What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality AssuranceInflectra
 
Manual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditManual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditSkynet Technologies
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesAssure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesThousandEyes
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesThousandEyes
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPathCommunity
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfpanagenda
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsNathaniel Shimoni
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rick Flair
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesKari Kakkonen
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Hiroshi SHIBATA
 

Último (20)

What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance[Webinar] SpiraTest - Setting New Standards in Quality Assurance
[Webinar] SpiraTest - Setting New Standards in Quality Assurance
 
Manual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditManual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance Audit
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyesAssure Ecommerce and Retail Operations Uptime with ThousandEyes
Assure Ecommerce and Retail Operations Uptime with ThousandEyes
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to Hero
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
Time Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directionsTime Series Foundation Models - current state and future directions
Time Series Foundation Models - current state and future directions
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...Rise of the Machines: Known As Drones...
Rise of the Machines: Known As Drones...
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examples
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024
 

OWL Full Semantics

  • 1. OWL Full Semantics -- RDF-Compatible Model-Theoretic Semantics by Peter F. Patel-Schneider, Patrick Hayes and Ian Horrocks W3C Recommendation, 2004 http://www.w3.org/TR/owl-semantics/rdfs.html Presented by Jie Bao RPI Sept 11, 2008 Part 2 of RDF/OWL Semantics Tutorial http://tw.rpi.edu/wiki/index.php/RDF_and_OWL_Semantics
  • 2. Disclaimer • The semantics and inference rules about RDFS Plus /RDFS 3.0 are rolely Jie Bao’s own and do not reflect the positions of either W3C (or any of its working group) or any of the RDFS Plus /RDF 3.0 proposals (citation on the page RDFS Plus: a Rule Subset of OWL ). 2
  • 3. A Layer Cake of Languages OWL2 OWL You Are Here (RDFS Plus) RDF(S) 3
  • 4. Not Covered in the Talk • Datatype • Annotation • Ontology house keeping (e.g., imports) • OWL comprehension conditions 4
  • 5. Outline • Review of RDF Semantics • OWL Overview • RDFS 3.0 Semantics • OWL Full Universe • OWL Full Interpretation Conditions 5
  • 6. RDF(S) Vocabulary RDF RDFS rdf:type rdfs:domain rdf:Property rdfs:range rdfs:Resource rdfs:Class rdfs:subClassOf rdfs:subPropertyOf … others (rectification, annotation, literal, collection, container) 6
  • 7. RDFS Interpretation V vocabulary extension of classes IS ICEXT rdf:Property IP IC IEXT rdfs:Class IR rdfs:Resource IR x IR 7 extension of properties
  • 8. Outline • Review of RDF Semantics • OWL Overview • RDFS Plus Semantics • OWL Full Universe • OWL Full Interpretation Conditions 8
  • 9. OWL Family OWL Full OWL DL (SHOIN(D)) OWL Lite (SHIF(D)) RDFS Plus (or RDFS 3.0) 9
  • 10. From RDF to OWL 2 Full OWL 2 Full Covered next time RDFS+ RDFS OWL 2 RL OWL Full RDF 10
  • 11. OWL Extensions to RDFS • Constructing classes: – e.g., ∀∃ ∧ ∨ ¬ • Constructing properties: – e.g., inverseOf • Property characteristics: – e.g., transitive, functional, symmetric • Mapping – Equality, non-equality (between classes, properties, ind.) 11
  • 12. Direct MT Sem. vs RDF MT Sem. • Direct Model-Theoretical Semantics – For OWL DL (thus also OWL Lite) – Simpler than the RDF MT Semantics – Corresponds to the semantics of DL SHOIN(D) – Decidability guaranteed • RDF-Compatible Model-Theoretical Semantics – For OWL Full (thus also OWL DL and OWL Lite) – Extends RDFS Semantics 12
  • 13. Outline • Review of RDF Semantics • OWL Overview • RDFS Plus Semantics • OWL Full Universe • OWL Full Interpretation Conditions 13
  • 14. RDFS Plus: a Rule Subset of OWL Design intuition: Scalable, easier to implement using rule inference • RDFS Plus / OWL Prime / RDFS 3.0 – Dean Allemang, James Hendler. Semantic Web for the Working Ontologist, Chapter 7 – Oracle: OWL Prime http://www.w3.org/2007/OWL/wiki/OracleOwlPrime • Related proposals – AllegroGraph RDFS++: http://agraph.franz.com/support/learning/Overview-of-RDFS++.lhtml – OWL 2 RL http://www.w3.org/2007/OWL/wiki/Profiles#OWL_2_RL 14
  • 15. RDFS Plus Vocabulary Equality Property Characteristics owl:equivalentClass, owl:inverseOf owl:equivalentProperty, owl:TransitiveProperty, owl:sameAs owl:SymmetricProperty, owl:FuncionalProperty, owl:InverseFunctionalProperty owl:ObjectProperty, owl:DatatypeProperty + RDFS vocabulary 15
  • 16. RDFS Plus Semantics If E is then IS(E) ∈IC and IEXT (IS (E))=IOOP owl:ObjectProperty ⊆IEXT(IP) IS(E) ∈IC and IEXT (IS (E))=IODP owl:DatatypeProperty ⊆IEXT(IP) ⊆ If E is ∈ then <x,y>∈IEXT (IS (E)) iff owl:equivalentClass x,y∈IC and ICEXT(x)=ICEXT(y) owl:equivalentProperty x,y∈IOOP∪IODP and IEXT (x) = IEXT (y) owl:sameAs x=y 16
  • 17. RDFS Plus Semantics If E is ∈ then c∈ICEXT (IS (E)) iff ∈ ∈ <x,y>, <y,z>∈IEXT (c) implies <x,z>∈IEXT (c) owl:TransitiveProperty and c ∈IOOP <x,y> ∈ IEXT (c) implies <y, x>∈IEXT (c) ∈ owl:SymmetricProperty and c ∈IOOP <x,y1>, <x,y2> ∈ IEXT (c) implies y1 = y2 owl:FuncionalProperty and c∈IOOP ∪ IODP ∈ <x ,y>, <x2,y>∈IEXT (c) implies x1 = x2 owl:InverseFunctionalProperty 1 and c∈IOOP If E is ∈ then <x,y>∈IEXT (IS(E)) iff owl:inverseOf x,y∈IOOP and <u,v>∈IEXT (x) iff <v,u>∈IEXT (y) ∈ ∈ 17
  • 18. RDFS Plus Semantics Extensional Semantic Conditions c, d ∈ IC, <c,d> ∈ IEXT(IS(rdfs:subClassOf)) ICEXT(c) ⊆ ICEXT(d) p, q ∈ IP, <p,q> ∈ IEXT(IS(rdfs:subPropertyOf)) IEXT(p) ⊆ IEXT(q) Iff* p ∈ IP, c ∈ IC, <p,c> ∈ IEXT(IS(rdfs:domain)) <x,y> ∈ IEXT(p) → x ∈ ICEXT(c) p ∈ IP, c ∈ IC, <p,c> ∈ IEXT(IS(rdfs:range)) <x,y> ∈ IEXT(p) → y ∈ ICEXT(c) * By default, RDFS uses “only if”, OWL 1 Full and OWL 2 Full uses “iff” 18
  • 19. Inference Rules Some examples: If then (?x, owl:sameAs, ?y) (?y, owl:sameAs, ?x) (?c1, owl:equivalentClass, ?c2) (?x, rdf:type, ?c2) (?x, rdf:type, ?c1) (?p, rdf:type, owl:FunctionalProperty) (?y1, owl:sameAs, ?y2) (?x, ?p, ?y1) T(?x, ?p, ?y2) (?p1, owl:inverseOf, ?p2) (?x, ?p1, ?y) (?y, ?p2, ?x) (?p, rdfs:domain, ?c) (?x, ?p, ?y) (?x, rdf:type, ?c) Complete rule set is in backup slides 19
  • 20. Outline • Review of RDF Semantics • OWL Overview • RDFS Plus Semantics • OWL Full Universe • OWL Full Interpretation Conditions 20
  • 21. OWL Vocabulary Classes Class Construction owl:Class owl:complementOf Boolean owl:Thing owl:intersectionOf owl:Nothing owl:unionOf owl:Restriction qualification qualification cardinality owl:allValuesFrom owl:onProperty owl:someValuesFrom Non-equality owl:hasValue owl:differentFrom owl:cardinality owl:disjointWith owl:minCardinality owl:AllDifferent owl:maxCardinality owl:distinctMembers owl:oneOf + RDFS Plus vocabulary 21
  • 22. Recall: RDFS Interpretation V vocabulary extension of classes IS ICEXT rdf:Property IP IC IEXT rdfs:Class IR rdfs:Resource IR x IR 22 extension of properties
  • 23. OWL Full Interpretation V vocabulary extension of classes IS ICEXT rdf:Property = {owl:ObjectProperty, owl:DatatypeProperty, IP IC owl:AnnotationProperty, owl:OntologyProperty} IEXT rdfs:Class IR =owl:Class rdfs:Resource =owl:Thing IR x IR 23 extension of properties
  • 24. OWL Full vs OWL DL OWL-DL OWL Full Relation to owl:Thing <=rdfs:Resource owl:Thing = rdfs:Resource RDFS universe owl:Class <= rdfs:Class owl:Class = rdfs:Class P <= rdf:Property P = rdf:Property Pairwise Yes No Disjointness Decidability Yes No P is the union of owl:ObjectProperty, owl:DatatypeProperty, owl:AnnotationProperty, and owl:OntologyProperty Note: in OWL Full, an element can be an individual (owl:Thing element), a class (owl:Class element) and an property (P element) at the same time. 24
  • 25. True or False? In OWL Full • owl:Thing rdfs:subClassOf owl:Class • owl:Class rdfs:subClassOf owl:Thing • owl:Thing rdf:type owl:Class • owl:Class rdf:type owl:Class • rdf:Property rdf:type owl:Class Refer: • OWL RDF Schema: http://www.w3.org/2002/07/owl • Thing and Class: http://ontolog.cim3.net/forum/ontolog-forum/2008- 09/threads.html#00004 25
  • 26. Outline • Review of RDF Semantics • OWL Overview • RDFS Plus Semantics • OWL Full Universe • OWL Full Interpretation Conditions 26
  • 27. OWL Classes and Properties then If E is ∈ IS (E)∈ ICEXT(IS (E))= and owl:Class IC IOC IOC=IC owl:Thing IOC IOT IOT=IR and IOT ≠ ∅ owl:Nothing IOC {} ∈ then if e∈ICEXT(IS If E is Note (E)) then Instances of OWL classes are OWL owl:Class ICEXT (e)⊆IOT individuals. Values for individual-valued owl:ObjectProperty IEXT (e)⊆IOT×IOT properties are OWL individuals. 27
  • 28. Boolean Operations and Enumeration If E is ∈ then <x,y>∈IEXT(IS (E)) iff owl:complementOf x,y∈ IOC and ICEXT(x)=IOT-ICEXT(y) x∈IOC and y is a sequence of y1,…yn over IOC owl:unionOf and ICEXT(x) = ICEXT(y1) ∪…∪ ICEXT(yn) x∈IOC and y is a sequence of y1,…yn over IOC owl:intersectionOf and ICEXT(x) = ICEXT(y1) ∩…∩ ICEXT(yn) x∈IC and y is a sequence of y1,…yn over IOT or owl:oneOf over ILV and ICEXT(x) = {y1,..., yn} If E is and ∈ then if <x,l>∈IEXT(IS (E)) then l is a sequence of y1,…yn owl:oneOf x∈IOC over IOT 28
  • 29. Restriction (Anonymous Class) then If E is IS(E)∈ ICEXT(IS(E))= and owl:Restriction IC IOR IOR⊆IOC If E is and <x,y>∈IEXT(IS(E))) ∧ ∈ then x∈IOR, y∈IOC, p∈IOOP, and ICEXT(x) = ∈ ∈ ∈ <x,p>∈IEXT(IS(owl:onProperty))) ∈ owl:allValuesFrom {u∈IOT | <u,v>∈IEXT(p) implies v∈ICEXT(y) } owl:someValuesFrom {u∈IOT | ∃ <u,v>∈IEXT(p) such that v∈ICEXT(y) } then x∈IOR, y∈IOT, p∈IOOP, and ICEXT(x) = ∈ ∈ ∈ owl:hasValue {u∈IOT | <u, y>∈IEXT(p) } then x∈IOR, y is a non-negative integer, p∈IOOP, ∈ ∈ and ICEXT(x) = owl:minCardinality {u∈IOT | card({v ∈ IOT : <u,v>∈IEXT(p)}) ≥ y } owl:maxCardinality, owl:cardinality defined similarly Note: Content on this page is simplified by omitting datatype properties 29
  • 30. Non-equality If E is ∈ then <x,y>∈IEXT (IS(E)) iff owl:disjointWith x,y∈IOC and ICEXT(x)∩ICEXT(y)={} owl:differentFrom x≠y More: Comprehension conditions (which require the existence of appropriate OWL descriptions and data ranges ) – not covered 30
  • 31. Conclusions RDFS Plus • A scalable rule subset of OWL Full, with MT semantics • Equality + Property Characteristics • Has extensional semantic conditions (while RDFS has not) OWL Full • Extends RDFS Plus, with MT semantics • OWL Full universe = RDFS universe – rdfs:Class = owl:Class ; rdfs:Resource = owl:Thing; owl:ObjectProperty <= rdf:Property • No distinction between classes, properties and individuals Next talk: OWL 2Full 31
  • 32. Further Reading • Ian Horrocks, Peter F. Patel-Schneider, Frank van Harmelen - From SHIQ and RDF to OWL: the making of a Web Ontology Language. In J. Web Sem. 1(1):7-26, 2003.(URL) • Turner, David; Carroll, Jeremy J. Comparing OWL Semantics. Technical Reports HPL-2007-146. HP Lab, 2007. (URL) 32
  • 33. Backup 33
  • 34. Other OWL Vocabulary • owl:DatatypeProperty, owl:DataRange • owl:Ontology • owl:imports, owl:priorVersion, owl:backwardCompatibleWith, and owl:incompatibleWith, owl:versionInfo • owl:OntologyProperty • owl:DeprecatedClass, owl:DeprecatedProperty • owl:AnnotationProperty 34
  • 35. Exercise • Prove tautology in RDFS: – rdfs:subPropertyOf rdfs:subPropertyOf rdfs:subPropertyOf – rdfs:domain rdfs:domain rdf:Property – rdfs:doman rdfs:range rdf:Class – rdf:Property rdf:type rdfs:Class • Prove tautology in OWL Full: – owl:sameAs owl:sameAs owl:sameAs 35
  • 36. d RDFS Plus Rules (1) If then (?s, owl:sameAs, ?s) (?s, ?p, ?o) (?p, owl:sameAs, ?p) (?o, owl:sameAs, ?o) (?x, owl:sameAs, ?y) (?y, owl:sameAs, ?x) (?x, owl:sameAs, ?y) (?x, owl:sameAs, ?z) (?y, owl:sameAs, ?z) (?s, owl:sameAs, ?s‘) (?s, ?p, ?o) (?s', ?p, ?o) (?p, owl:sameAs, ?p‘) (?s, ?p, ?o) (?s, ?p', ?o) (?o, owl:sameAs, ?o‘) (?s, ?p, ?o) (?s, ?p, ?o') Equality rules 36
  • 37. RDFS Plus Rules (2) If then (?c1, owl:equivalentClass, ?c2) (?x, rdf:type, ?c2) (?x, rdf:type, ?c1) (?c1, owl:equivalentClass, ?c2) (?x, rdf:type, ?c1) (?x, rdf:type, ?c2) (?c1, rdfs:subClassOf, ?c2) (?c1, owl:equivalentClass, ?c2) (?c2, rdfs:subClassOf, ?c1) (?p1, rdfs:subPropertyOf, ?p2) (?p1, owl:equivalentProperty, ?p2) (?p2, rdfs:subPropertyOf, ?p1) (?p1, owl:equivalentProperty, ?p2) (?x, ?p2, ?y) (?x, ?p1, ?y) (?p1, owl:equivalentProperty, ?p2) (?x, ?p1, ?y) (?x, ?p2, ?y) Equality rules 37
  • 38. RDFS Plus Rules (3) If then (?p, rdf:type, owl:FunctionalProperty) (?y1, owl:sameAs, ?y2) (?x, ?p, ?y1) T(?x, ?p, ?y2) (?p, rdf:type, owl:InverseFunctionalProperty) (?x1, owl:sameAs, ?x2) (?x1, ?p, ?y) T(?x2, ?p, ?y) (?p, rdf:type, owl:SymmetricProperty) (?y, ?p, ?x) (?x, ?p, ?y) (?p, rdf:type, owl:TransitiveProperty) (?x, ?p, ?z) (?x, ?p, ?y) (?y, ?p, ?z) (?p1, owl:inverseOf, ?p2) (?x, ?p1, ?y) (?y, ?p2, ?x) (?p1, owl:inverseOf, ?p2) (?x, ?p2, ?y) (?y, ?p1, ?x) Property characteristic rules 38
  • 39. RDFS Plus Rules (4) If then (?c, rdfs:subClassOf, ?c) (?c, rdf:type, owl:Class) (?c, owl:equivalentClasses, ?c) (?p, rdfs:subPropertyOf, ?p) (?p, rdf:type, owl:ObjectProperty) (?p, owl:equivalentProperty, ?p) (?p, rdfs:subPropertyOf, ?p) (?p, rdf:type, owl:DatatypeProperty) (?p, owl:equivalentProperty, ?p) OWL Class and Property Declaration 39
  • 40. RDFS Plus Rules (5) If then (?p, rdf:type rdf:Property) (?x, ?p, ?y) (?x, rdf:type rdfs:Resource) (?y, rdf:type rdfs:Resource) (?p, rdf:type rdf:Property) (?p, rdfs:subPropertyOf ?p) (?c, rdfs:subClassOf rdfs:Resource) (?c, rdf:type rdfs:Class) (?c, rdfs:subClassOf ?c) (?p1, rdfs:subPropertyOf, ?p2) (?x, ?p1, ?y) (?x, ?p2, ?y) (?c1, rdfs:subClassOf, ?c2) (?x, rdf:type, ?c1) (?x, rdf:type, ?c2) (?c1, rdfs:subClassOf, ?c2) (?c2, (?c1, rdfs:subClassOf, ?c3) rdfs:subClassOf, ?c3) (?p1, rdfs:subPropertyOf, ?p2) (?p2, (?p1, rdfs:subPropertyOf, ?p3) rdfs:subPropertyOf, ?p3) RDFS Rules 40
  • 41. RDFS Plus Rules (6) If then (?p, rdfs:domain, ?c) (?x, ?p, ?y) (?x, rdf:type, ?c) (?p, rdfs:range, ?c) (?x, ?p, ?y) (?y, rdf:type, ?c) Rules due to Extensional Semantic Conditions (?p, rdfs:domain, ?c1) (?c1, rdfs:subClassOf, ?c2) (?p, rdfs:domain, ?c2) (?p2, rdfs:domain, ?c) (?p1, rdfs:subPropertyOf, ?p2) (?p1, rdfs:domain, ?c) (?p, rdfs:range, ?c1) (?c1, rdfs:subClassOf, ?c2) (?p, rdfs:range, ?c2) (?p2, rdfs:range, ?c) (?p1, rdfs:subPropertyOf, ?p2) (?p1, rdfs:range, ?c) RDFS Rules (domain & range) 41