A Semantic Importing Approach to Knowledge Reuse from Multiple Ontologies
1. A Semantic Importing Approach to Knowledge Reuse from Multiple Ontologies Jie Bao, Giora Slutzki and Vasant Honavar Artificial Intelligence Research Laboratory Computer Science Department Iowa State University Ames, IA USA 50011 Email: {baojie,slutzki,honavar}@cs.iastate.edu www.cild.iastate.edu
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11. P-DL: Importing akin to Citation 1:Dog ⊑ 1:Animal 1:Cat ⊑ 1:Animal P 1 P 2 2:PetOwner ⊑ 2:owns. 1:Dog
12. P-DL: Contextualized Negation Black, White 1 White = Black 2 White = Black ⊔ Red 1 = White ⊔ Black 2 = White ⊔ Black ⊔ Red
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17. Modular Ontology Languages C Є (SHOIN(D)) OWL 1998 2002 2003 2004 2005 2006 2007 C-OWL CTXML E-Connections P-DL DDL(Distributed DL) DFOL DDL with Role Concept Mapping C Є (SHIF(D)) IHN + s DL ALCP C SHOIQP
18. Comparison Yes Yes Yes Yes P-DL Yes No N.A. Yes E-Connections Yes (bridge rule between concepts), Open (bridge rules between roles) No No Yes DDL Yes Yes Yes No OWL-DL Decidability Transitive Reusability Preservation of Unsatisfiability Contextualized Semantics
19. Comparison 1,4 Limited Support 2,3 May be simulated using syntactical encoding P-DL C C C C C C C C P P P P P P P x
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25. Analogy: Paper Writing Citation is not copy+paste, hence does not result in a single, combined document Recent development in modular ontologies… In this paper, we present two algorithms A and B to … (Alice, 2001) (Bob, 2007) Combining Ontologies Ontology Modularization Recent development in modular ontologies… In this paper, we extend the algorithm A proposed by (Alice,2001) … Same global domain: modular ontologies Multiple independent participants Possible (partial) reuse Contextualized Semantics
26. Desideratum: Contextualized Semantics People Work O 1 O 2 “ those that are not male are female” “ companies hire people”
33. Two General Approaches for Modularity Requiring explicit declaration of context; disallow axioms that might be used of context Interpreting axioms in local domains Preserve context by Compatible to existing tools Support distributed reasoning, stronger modeling ability Pros No known distributed reasoning support; restrictive language usage; context may not always be aware of Need to extend existing reasoners Cons Conservative Extension [Grau et al 2007] Example: DDL, E-Connections, P-DL Example First-order Contextualized Semantics Design Pattern Modular Ontology Languages
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Editor's Notes
Semantic importing akin to “citation” Package 2 cites package 1 for the definition of ‘1:Dog’ Interpretation of ‘1:Dog’ is the same on the “ shared” portions of the local domains of packages 1 and 2 The two packages need not agree on the interpretation of other unrelated concepts (e.g., Cats) P-DL supports selective knowledge reuse
There is an old story about an engineer, a physicist, and a mathematician hiking on a scenic trail in Scotland. They see a black cow standing on a hill in front of them. “Look,” the engineer says, “I didn’t know that all cows in Scotland are black.” “What nonsense,” replied the physicist, “You have only seen a sample of one. The best you can say is that some cows in Scotland are black. You would have to make more observations to determine the fraction of the total that are black to some accuracy.” “Excuse me, you are both wrong.” said the mathematician. “At the most, all you can say is that in Scotland at this time there is at least one cow that appears to be black on at least one side.” ============== An engineer, a physicist, and a mathematician were riding in a train in Scotland, when out the window they saw a black sheep. Said the engineer, "The sheep in Scotland are black." Said the physicist, "Some of the sheep in Scotland are black." Said the mathematician, "At least one sheep in Scotland is black on at least one side."
Localize Semantics No global model should be needed Context of knowledge should be kept Reasoning can be performed with local knowledge Distributed or parallel reasoning enabled