DRAOn : A Distributed Reasoner for Aligned Ontologies Chan LE DUC , - PowerPoint PPT Presentation

Motivation IDDL semantics Architecture Experiments DRAOn : A Distributed Reasoner for Aligned Ontologies Chan LE DUC , Myriam LAMOLLE , Antoine ZIMMERMANN and Olivier CURE e Paris8-IUT de Montreuil, ´ Universit´ Ecole Nationale Sup´ erieure des Mines, Universit´ e Marne La Vall´ ee OWL Reasoner Evaluation Workshop, 2013 ORE 2013 1/12

Motivation IDDL semantics Architecture Experiments Motivation O 1 O 2 O 4 O 3 SemWeb client ORE 2013 2/12

Motivation IDDL semantics Architecture Experiments Motivation O 1 O 2 | = α 1 ? | = α 2 ? O 4 | = α 4 ? | = α 3 ? O 3 SemWeb client ORE 2013 2/12

Motivation IDDL semantics Architecture Experiments Motivation O 1 O 2 A 12 A 13 A 23 O 4 A 43 O 3 SemWeb client ORE 2013 2/12

Motivation IDDL semantics Architecture Experiments Motivation O 1 O 2 A 12 Is this network consistent ? A 13 A 23 O 4 | = ? A 43 O 3 SemWeb client ORE 2013 2/12

Motivation IDDL semantics Architecture Experiments Formalizing a network of aligned ontologies Standard DL (merge of all ontologies and alignments) ; DDL (Distributed Description Logics) : Drago ; E -connections : Pellet ; ... IDDL (Integrated Distributed Description Logics) : The decision procedure for IDDL (RR2008) can be implemented in a distributed way. ORE 2013 3/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics A n − 1 , n A 12 . . . Syntax level O 1 O 2 O n − 1 O n ORE 2013 4/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics A n − 1 , n A 12 . . . Syntax level O 1 O 2 O n − 1 O n I 1 I 2 I n − 1 I n D 1 D 2 D n − 1 D n Local semantic level ORE 2013 4/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics A n − 1 , n A 12 . . . Syntax level O 1 O 2 O n − 1 O n I 1 I 2 I n − 1 I n D 1 D 2 D n − 1 D n Local semantic level Equalising ǫ 1 ǫ n ǫ 2 ǫ n − 1 functions Global semantic level D ORE 2013 4/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics A n − 1 , n A 12 . . . Syntax level O 1 O 2 O n − 1 O n I 1 I 2 I n − 1 I n D 1 D 2 D n − 1 D n Local semantic level Equalising ǫ 1 ǫ n ǫ 2 ǫ n − 1 functions Global semantic level D Global interpretation : I = � ( I i ) , ( ǫ i ) � ORE 2013 4/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics cross-ontology subsumption ⊑ I = � ( I i ) , ( ǫ i ) � | = j : D i : C I i I j ∆ j ∆ i ǫ j ǫ i ∆ ǫ i ( C I i ) ⊆ ǫ j ( D I j ) ORE 2013 5/12

Motivation IDDL semantics Architecture Experiments IDDL Semantics cross-ontology disjointness ⊥ I = � ( I i ) , ( ǫ i ) � | = j : D i : C I i I j ∆ j ∆ i ǫ i ǫ j ∆ ǫ i ( C I i ) ∩ ǫ j ( D I j ) = ∅ � O , A � consistent iff there is a I = � ( I i ) , ( ǫ i ) � satisfying local axioms and correspondences ORE 2013 5/12

Motivation IDDL semantics Architecture Experiments Global concepts and alignment ontology Global concepts are concepts that appear on the right or left side of a correspondence : ⊑ ← → A 12 : 1: Superman 2: Person ⊑ ← → A 23 : 2: Person 3: Vertebrate The global concepts are 1: Superman , 2: Person and 3: Vertebrate The alignment ontology renders the correspondences in the form of DL axioms : The alignment ontology � A contains the axioms 1: Superman ⊑ 2: Person 2: Person ⊑ 3: Vertebrate ORE 2013 6/12

Motivation IDDL semantics Architecture Experiments Configuration With only cross-ontology concept subsumption : Definition A configuration Ω asserts explicitly the emptiness or non emptiness of global concepts. Example Ω = { 1: Superman ⊑ ⊥ , 2: Person ⊑ ⊥ , a is a new individual name. 3: Vertebrate ( a ) } . ORE 2013 7/12

Motivation IDDL semantics Architecture Experiments Algorithm (sketched) With only cross-ontology concept subsumption : 1 Choose a configuration Ω ; 2 If Not Consistent( � A ∪ Ω), Go To 1 3 For All i , If Not LocallyConsistent(Ω ∪ O i ), Go To 1 4 Return TRUE ; If all configurations were tested, Return FALSE ; ORE 2013 8/12

Motivation IDDL semantics Architecture Experiments Properties of The Algorithm Encapsulated and parallelised local reasoners ; No upper bound on local expressiveness ; If a local reasoner is in EXPTIME class or higher, global consistency remains in the same class : EXPTIME (DL 1 , ··· , DL n ) (no disjoint correspondences). ORE 2013 9/12

Motivation IDDL semantics Architecture Experiments Architecture of DRAOn O 1 O 2 O n . . . OWL OWL OWL Reasoner 1 Reasoner 2 Reasoner n Wrapper Wrapper Wrapper configuration i configuration i configuration i Global Reasoner ORE 2013 10/12

Motivation IDDL semantics Architecture Experiments Optimizations and Experiments Optimizations : Eliminating from configurations equivalent concepts and roles Eliminating from configurations i : C if O | = i : C ( x ) or = ( i : C ⊑ ⊥ ) where O = � O | A or O = O i Testing configurations containing ( i : C ( x )) prior to ( i : C ⊑ ⊥ ) Building configurations in an incremental way ORE 2013 11/12

Motivation IDDL semantics Architecture Experiments Optimizations and Experiments Optimizations : Eliminating from configurations equivalent concepts and roles Eliminating from configurations i : C if O | = i : C ( x ) or = ( i : C ⊑ ⊥ ) where O = � O | A or O = O i Testing configurations containing ( i : C ( x )) prior to ( i : C ⊑ ⊥ ) Building configurations in an incremental way Experiments : Ontology 1 Ontology 2 Alignment DL non-distr. IDDL distr. IDDL Small NCI Small FMA Alcomo Map. 7,5s 46s 30s (10,000 axioms, (3,800 axioms, (2,800 corr.) 6,500 entities) 3,700 entities) Human Mouse Ref. Map. 6s 4.5s 4s (5,500 axioms, ( 4,500 axioms, (1516 corr.) 3,300 entities) 2,750 entities) ORE 2013 11/12

Motivation IDDL semantics Architecture Experiments Further Work Further experiments for a large network of aligned ontologies Optimizations for disjoint correspondences Performance of DRAOn depends on services offered by OWL Reasoners : DRAOn has to use OWLReasoner.getUnsatisfiableClasses() OWLReasoner.getTypes(OWLNamedIndividual) to check whether a given set of concepts is unsatisfiable or non-empty. ORE 2013 12/12