logic importance logic importance (2) logic importance (3) specializations of logic Horn logic specializations of logic RDF and OWL

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Franklin Logan
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logic importance - high-level language for expressing knowledge - high expressive power - well-understood formal semantics - precise notion of logical consequence - systems that can automatically

coincides with syntactic derivation within the proof system soundness & completeness - predicate logic is unique in the sense that sound and complete proof systems do exist not the case for more

1 logic importance - high-level language for expressing knowledge - high expressive power - well-understood formal semantics - precise notion of logical consequence - systems that can automatically derive statements syntactically from a set of premises lecture 17: semantic web rules of#35# ece#627,#winter# 13# 2# of#35# logic importance (2) - proof systems for which semantic logical consequence coincides with syntactic derivation within the proof system soundness & completeness - predicate logic is unique in the sense that sound and complete proof systems do exist not the case for more expressive logics (higher-order logics) logic importance (3) - trace the proof that leads to a logical consequence - logic can provide explanations for answers by tracing a proof ece#627,#winter# 13# 3# of#35# ece#627,#winter# 13# 4# of#35# specializations of logic RDF and OWL - RDF/S and OWL (Lite and DL) are specializations of predicate logic they correspond (roughly) to a description logic - they define reasonable subsets of logic - trade-off between the expressive power and the computational complexity (the more expressive the language, the less efficient the corresponding proof systems) specializations of logic Horn logic a rule has the form: A1,..., An B - Ai and B are atomic formulas ece#627,#winter# 13# 5# of#35# ece#627,#winter# 13# 6# of#35#

2 specializations of logic Horn logic there are two ways of reading such a rule - deductive if A1,..., An are known to be true, then B is also true - reactive if the conditions A1,..., An are true, then carry out the action B logic: description vs Horn OWL vs rules it is impossible to assert that a person X who is brother of Y is uncle of Z (where Z is child of Y) in OWL this can be done easily using rules: brother(x,y), childof(z,y) uncle(x,z) ece#627,#winter# 13# 7# of#35# ece#627,#winter# 13# 8# of#35# logic: description vs Horn OWL vs rules (2) rules cannot assert the information that a person is either a man or a woman this information is easily expressed in OWL using disjoint union OWL needs rules!!! rule languages rule languages define how to synthesize new facts form those stored in the knowledge base - RuleML - semantic web rule language - ece#627,#winter# 13# 9# of#35# ece#627,#winter# 13# 10# of#35# RuleML - effort to standardize inference rules - RuleML is a markup language for publishing and sharing rule bases on the World Wide Web - focus is on rule interoperation between industry standards - provides an XML syntax for Datalog clauses Datalog its alphabet is a set of predicate symbols, constants, and variables atom is an expression of the form P(t1, t2,, tn), where P is an n-ary predicate symbol and t1,, tn are terms term is a variable or constant ece#627,#winter# 13# 11# of#35# ece#627,#winter# 13# 12# of#35#

3 Datalog examples (1): book( Semantic Web, U.K., 2007 ) (2): book(title, counry, 2005 ) Datalog clause clause is either a fact or a rule fact is an expression of the form B where B is a variable-free atom rule is an expression of the form A1,, Am C where A1,, Am atoms are called antecedents, C atom is called the consequent or head ece#627,#winter# 13# 13# of#35# ece#627,#winter# 13# 14# of#35# Datalog example (3): book(x, U.K., y) UKbook(x) RuleML example (1) book( Semantic Web, U.K., 2007 ) <Rel>book</Rel> <Ind>Semantic Web</Ind> <Ind>U.K.</Ind> <Ind>2007</Ind> ece#627,#winter# 13# 15# of#35# ece#627,#winter# 13# 16# of#35# RuleML example (2) book(tilte, country, 2005 ) <Rel>book</Rel> <Var>title</Var> <Var>country</Var> <Ind>2007</Ind> RuleML example (3) book(x, U.K., y) UKbook(x) <Implies> <head> <Rel>UKbook</Rel> <Var>x</Var> </head> ece#627,#winter# 13# 17# of#35# ece#627,#winter# 13# 18# of#35#

4 RuleML example (3) continuation <body> <Rel>book</Rel> <Var>x</Var> <Ind>U.K.</Ind> <Var>y</Var> </body> </Implies> - is an acronym for Semantic Web Rule Language - is intended to be the rule language of the Semantic Web - is based on OWL: all rules are expressed in terms of OWL concepts (classes, properties, individuals, literals...). ece#627,#winter# 13# 19# of#35# ece#627,#winter# 13# 20# of#35# atoms (predicates) C(x) C is an OWL class P(x,y) P is an OWL predicate sameas(x,y) sameas belongs to the OWL differentfrom(x,y) differentfrom belongs to the OWL vocabulary builtin(r,x, ) r is a built-in relation example (1) from Datalog book( Semantic Web, U.K., 2007 ) 1. Book(B) 2. title(b, Semantic Web ) 3. countryofpub(b, U.K ) 4. yearofpub(b, 2007 ) x,y are either variables, individuals, or data values ece#627,#winter# 13# 21# of#35# ece#627,#winter# 13# 22# of#35# atoms (predicates) differences to Datalog - atoms are only unary or binary predicates (no restrictions in RuleML) - OWL class descriptions can be viewed as unary predicates (nothing like that in RuleML) atoms (predicates) 1 C(x) C is an OWL class holds iff x is an individual of the class description or data range C Person(John) Person(?x) ece#627,#winter# 13# 23# of#35# ece#627,#winter# 13# 24# of#35#

5 atoms (predicates) 2 P(x,y) P is an OWL predicate holds iff x is related to y by property P hasbrother(john, Bill) hasbrother(john,?y) hasbrother(?x,?y) atoms (predicates) 3 sameas(x,y) sameas belongs to the OWL vocabulary holds iff x is interpreted as the same object y sameas(?x,?y) ece#627,#winter# 13# 25# of#35# ece#627,#winter# 13# 26# of#35# atoms (predicates) 4 differentfrom(x,y) differentfrom belongs to the OWL vocabulary holds iff x and y are interpreted as different objects differentfrom(?x,?y) atoms (predicates) 5 builtin(r,x, ) r is a built-in relation holds iff the built-in relation r holds for the interpretations of the arguments swrlb:greaterthan(?x,?y) (builtin(greaterthan,?x,?y)) swrlb:startswith(?x, "+") ece#627,#winter# 13# 27# of#35# ece#627,#winter# 13# 28# of#35# rule example reclassification rule example property value assignment Man(?m) Person(?m) Person(?p) hassibling(?p,?s) Man(?s) hasbrother(?p,?s) ece#627,#winter# 13# 29# of#35# ece#627,#winter# 13# 30# of#35#

6 rule example named individuals rule example with individuals & literals Person(Fred) hassibling(fred,?s) Man(?s) hasbrother(fred,?s) Person(Fred) hassibling(fred,?s) hasage(?s, 40) has40yearoldbrother(fred,?s) Man(?s) ece#627,#winter# 13# 31# of#35# ece#627,#winter# 13# 32# of#35# rule example with built-ins rule example with built-ins (2) hasbrother(?x1,?x2) hasage(?x1,?age1) hasage(?x2,?age2) swrlb:greaterthan(?age2,?age1) hasolderbrother(?x1,?x2) hasbrother(?x1,?x2) hasage(?x1,?age1) hasage(?x2,?age2) swrlb:subtract(10,?age2,?age1) hasdecadeolderbrother(?x1,?x2) ece#627,#winter# 13# 33# of#35# ece#627,#winter# 13# 34# of#35# characteristics - W3C Submission in rules saved as part of ontology - increasing tool support: Bossam, R2ML, Hoolet, Pellet, KAON2, RacerPro, Tab - can work with reasoners ece#627,#winter# 13# 35# of#35#

SWRL Semantic Web Rule Language. Susana R. Novoa UNIK4710

SWRL Semantic Web Rule Language Susana R. Novoa UNIK4710 What is SWRL? What is Jess? Installing Jess Creating rules SWRL Rules Atom Types SWRLTab SQWRL SQWRLTab SWRL Resources Overview What is SWRL? SWRL