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Memory exhaustion is a common problem in tableau-based OWL reasoners, when reasoning with large ontologies. One possible solution is to distribute the reasoning task across multiple machines. In this paper, we present, as preliminary work, a prototypical implementation for distributing OWL-EL ontologies over a Peer-to-Peer network, and reasoning with them in a distributed manner. The algorithms presented are based on Distributed Hash Table (DHT), a common technique used by Peer-to-Peer applications. The system implementation was developed using the JXTA P2P platform and the Pellet OWL-DL reasoner. It remains to demonstrate the efficiency of our method and implementation with respect to stand alone reasoners and other distributed systems. http://www.webont.org/owled/2009/papers/owled2009_submission_34.pdf
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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
[email protected], [email protected]
dumontierlab.com
Friday, October 23, 2009
Introduction
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• 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.
Friday, October 23, 2009
Our Approach
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• Extend Pellet for distributed reasoning and integrate it into a P2P environment.
Friday, October 23, 2009
Distributed Hash Table
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Peer 1
Peer 2
http://example.org/Person
http://example.org/Bob
100
200
34
167
Identifier Hash
Friday, October 23, 2009
Distributed KB
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• 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 properties4. Individual assertions of the form C(a) and R(a,b)
s.t. ϕ(a) ≋ ϕ(P) * GCI are not supported
Friday, October 23, 2009
Distributed KB
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Friday, October 23, 2009
Concept Satisfiability
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• 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.
Friday, October 23, 2009
Concept Satisfiability
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Example:
Female ≡ ¬Male Parent ≡ ∃hasChild.Person Mother ≡ Female ⊓ Parent
Unfold(Mother) = ¬Male ⊓ ∃hasChild.Person
Friday, October 23, 2009
Concept Satisfiability
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• 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
Friday, October 23, 2009
ABox Consistency
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• 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).
Friday, October 23, 2009
ABox Consistency
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• 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.
Friday, October 23, 2009
Summary
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• 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.
Friday, October 23, 2009