JXTA + Pellet =  P2P OWL Reasoning  P2P OWL Reasoning  <ul><li>Alexander De Leon </li></ul><ul><li>School of Computer Scie...
Review of the Tableau Algorithm  <ul><li>Used by most OWL reasoner (sound & complete) </li></ul><ul><li>In its basic form ...
Review of the Tableau Algorithm  <ul><li>Can be view as a directed graph where each node represent an individual and edges...
Review of the Tableau Algorithm  Mary {Person,  Female, ∃hasChild.Person} Peter {Person,  Male} hasChild
Review of the Tableau Algorithm  <ul><li>Rules are applies to the graph until no more rules can be applied or a  clash  is...
Review of the Tableau Algorithm
Review of the Tableau Algorithm  <ul><li>For concept satisfiability the algorithm starts with a generated individual for t...
Distributed Hash Table Peer 1 Peer 2 http://example.org/Person http://example.org/Bob 100 200 34 167 Identifier Hash key
Distributed Knowledge Base
Distributed Knowledge Base Peer 1 Peer 2 a { Automobile } e {_Remote_} hasPart b {Bicycle} e {Engine} Names in  red  are k...
Distributed Unfolding  <ul><li>Unfolding is a well known technique to allow satisfiability test of concepts with having the...
Distributed Unfolding  Female ≡ ¬Male  Parent ≡ ∃hasChild.Person  Mother ≡ Female ⊓ Parent  The expansion of  Mother  is :...
Distributed Unfolding  <ul><li>Unfold the concept locally (using pellet) </li></ul><ul><li>Each remote concept in the resu...
Distributed Unfolding  <ul><li>Unfold the concept locally (using pellet) </li></ul><ul><li>Each remote concept in the resu...
Distributed Unfolding
Software Architecture
The network is the reasoner
Current Work <ul><li>Finishing subsumption using the already implemented concept satisfiability procedure. </li></ul><ul><...
Future Work <ul><li>Implement query answering. </li></ul><ul><li>Smart distribution. Using ideas from ontology modularizat...
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Jxta Owl : Towards P2P OWL reasoning

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Jxta Owl : Towards P2P OWL reasoning

  1. 1. JXTA + Pellet = P2P OWL Reasoning P2P OWL Reasoning <ul><li>Alexander De Leon </li></ul><ul><li>School of Computer Science </li></ul><ul><li>Carleton University </li></ul>
  2. 2. Review of the Tableau Algorithm <ul><li>Used by most OWL reasoner (sound & complete) </li></ul><ul><li>In its basic form it is used for concept satisfiability. </li></ul><ul><li>Other reasoning tasks such as subsumption and ABox consistency checking can then be reduced to satisfiability test. </li></ul>
  3. 3. Review of the Tableau Algorithm <ul><li>Can be view as a directed graph where each node represent an individual and edges are roles between individuals. </li></ul><ul><li>Each node is annotated with the set of concepts the individual is member of. </li></ul>
  4. 4. Review of the Tableau Algorithm Mary {Person, Female, ∃hasChild.Person} Peter {Person, Male} hasChild
  5. 5. Review of the Tableau Algorithm <ul><li>Rules are applies to the graph until no more rules can be applied or a clash is found. </li></ul><ul><li>A clash is a trivial inconsistency. For instance: </li></ul>Bob {Person, Male , ∃hasChild.Person, ¬Male } Peter {Person, Male} hasChild
  6. 6. Review of the Tableau Algorithm
  7. 7. Review of the Tableau Algorithm <ul><li>For concept satisfiability the algorithm starts with a generated individual for the class been tested. </li></ul>_:person0 {Person}
  8. 8. Distributed Hash Table Peer 1 Peer 2 http://example.org/Person http://example.org/Bob 100 200 34 167 Identifier Hash key
  9. 9. Distributed Knowledge Base
  10. 10. Distributed Knowledge Base Peer 1 Peer 2 a { Automobile } e {_Remote_} hasPart b {Bicycle} e {Engine} Names in red are known to be remote.
  11. 11. Distributed Unfolding <ul><li>Unfolding is a well known technique to allow satisfiability test of concepts with having the full TBox: </li></ul><ul><li>The concept C ′ is called the expansion of C , and it is obtained recursively from C by replacing each non base symbol A in by the concept D , where D is the expansion of A </li></ul>C is satisfiable w.r.t TBox iff C ′ is satisfiable.
  12. 12. Distributed Unfolding Female ≡ ¬Male Parent ≡ ∃hasChild.Person Mother ≡ Female ⊓ Parent The expansion of Mother is : ¬Male ⊓ ∃hasChild.Person It follows that: Mother ≡ ¬Male ⊓ ∃hasChild.Person
  13. 13. Distributed Unfolding <ul><li>Unfold the concept locally (using pellet) </li></ul><ul><li>Each remote concept in the result is replaced by its unfolding provided by the remote responsible peer. </li></ul>
  14. 14. Distributed Unfolding <ul><li>Unfold the concept locally (using pellet) </li></ul><ul><li>Each remote concept in the result is replaced by its unfolding provided by the remote responsible peer. </li></ul>
  15. 15. Distributed Unfolding
  16. 16. Software Architecture
  17. 17. The network is the reasoner
  18. 18. Current Work <ul><li>Finishing subsumption using the already implemented concept satisfiability procedure. </li></ul><ul><li>Finish full ABox consistency. </li></ul>
  19. 19. Future Work <ul><li>Implement query answering. </li></ul><ul><li>Smart distribution. Using ideas from ontology modularization to distribute axioms in a way that peers contain axioms that are strongly related to each other. This will reduce the amount of messages between peers. </li></ul><ul><li>Explore parallelism </li></ul>

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