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A platform for distributing
                    and reasoning with OWL-EL
                   knowledge bases in a Peer-to-
                         Peer environment
                                       Alexander De Leon1 , Michel Dumontier1,2,3

                                              1  School of Computer Science
                                                   2 Department of Biology
                                                 3 Instititute of Biochemistry

                           Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Canada

                                 adlbatti@scs.carleton.ca, michel_dumontier@carleton.ca




             dumontierlab.com

Friday, October 23, 2009
Introduction


     • Reasoning with expressive ontologies is inherently
     intractable.

     • We have highly optimized domain-independent
     reasoner implementations (e.g. Pellet, Fact++).

     •These do not scale well for large KBs.


             dumontierlab.com

Friday, October 23, 2009
Our Approach

     • Extend Pellet for distributed reasoning and integrate
     it into a P2P environment.




             dumontierlab.com

Friday, October 23, 2009
Distributed Hash Table

                                Identifier           Hash
                                  Peer 1             100

                                  Peer 2            200

                           http://example.org/Person 34
                           http://example.org/Bob   167



             dumontierlab.com

Friday, October 23, 2009
Distributed KB
     • Let ϕ: string ⟶ ℤ be the hash function.
     • ≋ means numerically closest.
     • Each peer P is responsible for:
           1. The subset of base concepts C s.t. ϕ(C) ≋ ϕ(P)
           2. The subset of terminological axioms of the form
              equivalentTo(C,D) and subClassOf(C,D) s.t. ϕ(C)* ≋
              ϕ(P)
           3. All axioms about properties
           4. Individual assertions of the form C(a) and R(a,b)
              s.t. ϕ(a) ≋ ϕ(P)
       * GCI are not supported


             dumontierlab.com

Friday, October 23, 2009
Distributed KB




             dumontierlab.com

Friday, October 23, 2009
Concept Satisfiability

     • Want to prove that a concept C is satisfiable/
     unsatisfiable w.r.t. a TBox T :

     • Unfolding Technique:
     • C is satisfiable w.r.t        TBox T iff Unfold(C) is
     satisfiable.

     • Unfolding is a recursive procedure which remove all
     non-based symbols from the definition of a concept.


             dumontierlab.com

Friday, October 23, 2009
Concept Satisfiability


       Example:

                                  Female ≡ ¬Male
                             Parent ≡ ∃hasChild.Person
                             Mother ≡ Female ⊓ Parent


           Unfold(Mother) = ¬Male ⊓ ∃hasChild.Person



             dumontierlab.com

Friday, October 23, 2009
Concept Satisfiability




     • Caveat: The stack of unfold calls need to be passed to avoid falling into a cycle. The
     condition in line 7 needs to be expanded with: AND {d} ∉ STACK

             dumontierlab.com

Friday, October 23, 2009
ABox Consistency
     • Concepts satisfiability is reduced to ABox
     consistency. Unfolding is not enough if we want to
     support nominals.

     • Some cases where peers would need to exchange
     information:

         ‣ Resolving the class membership of a remote
         individual.

         ‣ Obtaining the set of edges that are connected to a
         remote individual (i.e. for role transitivity).

             dumontierlab.com

Friday, October 23, 2009
ABox Consistency

     • Our idea to solve this:
         • Assert each remote individual i as _REMOTE_(i), as a
         marker.

         • Apply a tableau rule at each fragment simultaneously
         and sync before applying the next.

         • Peer exchange information about labels of remote
         individuals.


             dumontierlab.com

Friday, October 23, 2009
Summary

     • Goal is to make OWL reasoning more scalable by
     using a P2P approach where new peers can easily be
     added as more resources are needed.

     • Our approach is to reuse current reasoner
     implementations and apply new methodologies for
     distributed DL reasoning.

     • Concept satisfiability checking was implemented
     without support for nominals.


             dumontierlab.com

Friday, October 23, 2009

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OWLED2009: A platform for distributing and reasoning with OWL-EL knowledge bases in a Peer-to- Peer environment

  • 1. A platform for distributing and reasoning with OWL-EL knowledge bases in a Peer-to- Peer environment Alexander De Leon1 , Michel Dumontier1,2,3 1 School of Computer Science 2 Department of Biology 3 Instititute of Biochemistry Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Canada adlbatti@scs.carleton.ca, michel_dumontier@carleton.ca dumontierlab.com Friday, October 23, 2009
  • 2. Introduction • Reasoning with expressive ontologies is inherently intractable. • We have highly optimized domain-independent reasoner implementations (e.g. Pellet, Fact++). •These do not scale well for large KBs. dumontierlab.com Friday, October 23, 2009
  • 3. Our Approach • Extend Pellet for distributed reasoning and integrate it into a P2P environment. dumontierlab.com Friday, October 23, 2009
  • 4. Distributed Hash Table Identifier Hash Peer 1 100 Peer 2 200 http://example.org/Person 34 http://example.org/Bob 167 dumontierlab.com Friday, October 23, 2009
  • 5. Distributed KB • Let ϕ: string ⟶ ℤ be the hash function. • ≋ means numerically closest. • Each peer P is responsible for: 1. The subset of base concepts C s.t. ϕ(C) ≋ ϕ(P) 2. The subset of terminological axioms of the form equivalentTo(C,D) and subClassOf(C,D) s.t. ϕ(C)* ≋ ϕ(P) 3. All axioms about properties 4. Individual assertions of the form C(a) and R(a,b) s.t. ϕ(a) ≋ ϕ(P) * GCI are not supported dumontierlab.com Friday, October 23, 2009
  • 6. Distributed KB dumontierlab.com Friday, October 23, 2009
  • 7. Concept Satisfiability • Want to prove that a concept C is satisfiable/ unsatisfiable w.r.t. a TBox T : • Unfolding Technique: • C is satisfiable w.r.t TBox T iff Unfold(C) is satisfiable. • Unfolding is a recursive procedure which remove all non-based symbols from the definition of a concept. dumontierlab.com Friday, October 23, 2009
  • 8. Concept Satisfiability Example: Female ≡ ¬Male Parent ≡ ∃hasChild.Person Mother ≡ Female ⊓ Parent Unfold(Mother) = ¬Male ⊓ ∃hasChild.Person dumontierlab.com Friday, October 23, 2009
  • 9. Concept Satisfiability • Caveat: The stack of unfold calls need to be passed to avoid falling into a cycle. The condition in line 7 needs to be expanded with: AND {d} ∉ STACK dumontierlab.com Friday, October 23, 2009
  • 10. ABox Consistency • Concepts satisfiability is reduced to ABox consistency. Unfolding is not enough if we want to support nominals. • Some cases where peers would need to exchange information: ‣ Resolving the class membership of a remote individual. ‣ Obtaining the set of edges that are connected to a remote individual (i.e. for role transitivity). dumontierlab.com Friday, October 23, 2009
  • 11. ABox Consistency • Our idea to solve this: • Assert each remote individual i as _REMOTE_(i), as a marker. • Apply a tableau rule at each fragment simultaneously and sync before applying the next. • Peer exchange information about labels of remote individuals. dumontierlab.com Friday, October 23, 2009
  • 12. Summary • Goal is to make OWL reasoning more scalable by using a P2P approach where new peers can easily be added as more resources are needed. • Our approach is to reuse current reasoner implementations and apply new methodologies for distributed DL reasoning. • Concept satisfiability checking was implemented without support for nominals. dumontierlab.com Friday, October 23, 2009