Package-based Description Logics – Preliminary Results
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Transcript of Package-based Description Logics – Preliminary Results
International Semantic Web Conference (ISWC) 2006. Doctoral Consortium Track, Nov 5, 2006 Athens, GA 1
Iowa State University Department of Computer ScienceArtificial Intelligence Research Laboratory
Package-based Description Logics – Preliminary Results
Jie Bao, Doina Caragea, Vasant Honavar
Artificial Intelligence Research LaboratoryComputer Science Department
Iowa State University Ames, IA USA 50011
Email: [email protected]
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Modular Ontologies
• What is modular ontology?– An ontology that contains a set of smaller,
(semantically) connected component ontologies
• Why modular ontology ?– A Distributed Semantic Web– Collaborative Ontology Building (COB)– Selective Ontology Reuse– Large Ontology Storage and Reasoning
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Berners-Lee, T., Hendler, J., and Lassila, O. (2001).The semantic web. Scientific American, 284(5):34-43.
A Distributed Semantic Web
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A COB Example
Swine
Cattle Chicken
Horse
Each group works on an ontology module for a particular species (according to the group’s best expertise)
Collaborative building of an animal trait ontology that involves multiple research groups across the world
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Ontology Languages Needed
• Has localized semantics– Allows distributed reasoning
• Supports fine-grained ontology organizational structure – Allows partial ontology reuse– Supports selective knowledge hiding
• Enables collaborative and scalable tools
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Modular Ontology Languages Today
OWL
2002 2003 2004 2005 2006
C-OWLC-OWLCTXWL
E-ConnectionsE-Connections
Our approach
DDL based
? ?
(E-connection can also work other logics e.g. modal logic)
P-DL
(to be discussed at the WoMO workshop)
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Modular Ontology Languages Today (2)
• E-Connections– Connects DL modules with
special types of roles called “links”
PetOwner
Petowns
• Distributed Description Logics (DDL) & C-OWL
– Allows “bridge rules” between concepts across ontology modules
PetAnimal
Dog
(onto)
(into)
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Expressivity Comparison
[Baot et al. ASWC 2006]
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Open problems
• How to obtain stronger expressiveness?
• How to enable distributed reasoning without required global knowledge?
• How to ensure the reasoning exactness w.r.t. standard reasoning with integrated ontology?
• How to create modular ontologies?
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Package
• Packages of an ontology– Are defined in subsets of the same
decidable DL,e.g., SHOIQ– May contain both local terms and
imported terms;
• Each term has a home package• P :Package extension
– PC: Package extension with only concept name importing
– E.g., SHOIQP= SHOIQ +P ALCPC = ALC + PC
General Pet
Wild Livestock
Animal ontology
PetDogPet
DogGeneral
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Package: Example
O1 (General Animal) O2 (Pet)
It uses ALCP, but not ALCPC
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Ongoing work: Scope Limitation
• SLM of an ontology term or axiom t– is a boolean function that
defines the visible scope of a term or axiom.
• Example SLMs– Public (t,r): t is accessible from
anywhere
– Private (t,r): t is only available in the home package
P3
P1
P2
public
private
P1
P2
public
private
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Localized Semantics
O1 O2
AnimalI
CarnivoreI
DogI
fooI
DogI
PetIPetDogI
x
eatsI
1
1
1
2
2
2
22
DogFoodI 2
AnimalI2
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Semantics of Importing
O1 O2importing
AnimalI
CarnivoreI
DogI
x fooI
DogI
PetIPetDogI
x
eatsI
1
1
1
2
2
2
22
DogFoodI 2
AnimalI2
Image domain relation
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Global Interpretations
AnimalI
CarnivoreI
DogI
I
PetDogI
x
PetI
eatsI
g
g
g
g
g
g
fooIg
DogFoodI g
• The (conceptual) global interpretation for the (virtually) integrated ontology• It can be combined from local interpretations
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Partially Overlapped ModelΔI1 ΔI2
x x’
CI1 CI2
r12
ΔI3
r13 r23
x’’CI3
x
CI
Global interpretation obtained from localInterpretations by merging shared individuals
bijective(one-to-one)
Transitive(Compositional consistent)
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P-DL Semantics Features
• Localized Semantics– Local “top” concepts are not the same– Each package explains the world based on its
transitive importing closure (local point of view).
• Stronger expressivity– Supports both inter-module concept subsumption and
inter-module role usage.
• Decidable (when all modules are from the same decidable DL)
• Solves some reasoning diffculities in other approaches
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Reasoning for Modular Ontology
• Major Consideration: should not require the integration of ontology modules.– High communication cost– High local memory cost– May violate module autonomy, e.g., privacy
• Question: can we do reasoning for P-DL without – (syntactic level) an integrated ontology ?– (semantic level) a (materialized) global tableau ?
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Distributed Reasoning
Stan: Hey, Chef. Is Kyle’s new home far from us?
Chef: Hello there, children! Where does Kyle move to?
Cartman: San Francisco, I guess.
Chef: • We are in South Park, Colorado; • San Francisco is in California; • Colorado is far from California.
Stan: So they are far from us. Too Bad.
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Federated Reasoning for P-DL
Basic strategy• Use multiple local reasoners, each
for a single package• Each local reasoner creates and
maintains a local tableau based on (only) local knowledge
• A local reasoner may query other reasoners if its local knowledge is incomplete
• Global relation among tableaux is created by messages
(1)
(2)(3)
(4)
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T3
x
ALCPC Expansion Example
• P1: 1:A 1:B• P2: 1:B 2:C• P3: 2:C 3:D• Query: if A D
(witnessed by P3)
L3(x)={A⊓
D, C D⊔A,C, D}
r(x,C)
x x
r(x,A)
T2 T1
L2(x)={B C⊔C, B}
L1(x)={A B⊔A, B }
r(x,B)
(x)
(x) (x)
Transitive Subsumption Propagation
Messages:• m(x,C): if copy of x has label C• r(x,C): add C into the label of x (or its copy) • Message Target: C’s home package reasoner
, B
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ALCPC Expansion Example (2)
x1
{A1}
x1
{B1}
{A3}
x4
Local Reasonerfor package A
Local Reasonerfor package B
{A2}
x2
rA
{B2}x3
rB
{B3}
x4
rB
x1
{A1,B1}
{A2}
{A3,B3}
{B2}x2 x3
x4
The (conceptual) global tableau
rA rB
rB
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More complex situations
[Bao & Honavar, WI2006]
• Cyclic name importing
• Asynchronous parallel reasoning
[Bao etal, (to be submitted)]
• Role, nominal importing
• Component languages in SHOIQ
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Ongoing: Concealable Reasoning
• A reasoner should not expose hidden knowledge
• However, such hidden knowledge may still be (indirectly) used in safe queries.
QueriesYes
Unknown
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Collaborative Ontology Building
Ontology modularity facilitates collaborative building
• Each package can be independently developed
• Multiple users can concurrently edit the ontology on different packages
• Ontology can be only partially loaded• Unwanted interactions are minimized by
limiting term and axiom visibility
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Iowa State University Department of Computer ScienceArtificial Intelligence Research LaboratoryThe COB Editor
Pig Package
Cattle Package
Chicken Package
http://sourceforge.net/projects/cob/
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WikiOnt 2 (under development)
A Wiki-based Ontology Editor with GUI
Will be on http://sourceforge.net/projects/wikiont/
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Outline
• Motivation
• Language Features
• Semantics
• Reasoning
• Applications
• Conclusions
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Main Contributions
• Investigate the requirement and formal semantics of modular ontologies
• Present a formal modular ontology language, P-DL, that can overcome many limitations in existing approaches– Stronger expressivity– Solve some inference difficulties
• Present a federated reasoning algorithm for P-DL that can – strictly avoid integration of ontology modules– handle reasoning tasks not solvable in existing approaches
• Apply the notion of modular ontology in collaborative ontology building
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Ongoing work
• Reasoning with OWL (SHOIQ) + Package extension
• Reasoning with selectively hidden knowledge
• The implementation of the distributed reasoner (based on Pellet)
• WikiOnt 2
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PublicationsLanguage Features• Bao, J.; Caragea, D.; and Honavar, V. (2006) Towards
collaborative environments for ontology construction and sharing. In International Symposium on Collaborative Technologies and Systems (CTS 2006). IEEE Press. 99–108.
Semantics• Bao, J.; Caragea, D.; and Honavar, V. (2006) Modular ontologies -
a formal investigation of semantics and expressivity. In R. Mizoguchi, Z. Shi, and F. Giunchiglia (Eds.): Asian Semantic Web Conference 2006, LNCS 4185, 616–631.
• Bao, J.; Caragea, D.; and Honavar, V. (2006) On the semantics of linking and importing in modular ontologies. In I. Cruz et al. (Eds.): ISWC 2006, LNCS 4273. 72–86.
http://boole.cs.iastate.edu:9090/popeye/Wiki.jsp?page=Academic.Basic.CV.Publication
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Publications
Reasoning5. Bao, J.; Caragea, D.; and Honavar, V. (2006) A tableau-based federated
reasoning algorithm for modular ontologies. 2006 IEEE/WIC/ACM International Conference on Web Intelligence (In Press).
6. Bao, J.; Caragea, D.; and Honavar, V. (2006) A distributed tableau algorithm for package-based description logics. In the 2nd International Workshop On Context Representation And Reasoning (CRR 2006).
Collaborative Ontology Building7. Bao, J.; and Honavar, V. (2004) Collaborative ontology building with
WikiOnt - a multi-agent based ontology building environment. In Proc. of 3rd International Workshop on Evaluation of Ontology-based Tools, at ISWC 2004, pages 37–46.
8. Bao, J.; Hu, Z.; Caragea, D.; Reecy, J.; and Honavar, V. (2006) Developing frameworks and tools for collaborative building of large biological ontologies. In The 4th International Workshop on Biological Data Management (BIDM’06). 191-195.
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References (Related Work)DDL:9. A. Borgida and L. Serafini. Distributed description logics: Directed domain
correspondences in federated information sources. InCoopIS/DOA/ODBASE, pages 36-53, 2002.
10. P. Bouquet, F. Giunchiglia, and F. van Harmelen. C-OWL: Contextualizing ontologies. In Second International Semantic Web Conference, volume 2870 of Lecture Notes in Computer Science, pages 164-179. Springer Verlag, 2003.
11. L. Serafini, A. Borgida, and A. Tamilin. Aspects of distributed and modular ontology reasoning. In IJCAI, pages 570-575, 2005
12. L. Serafini and A. Tamilin. Local tableaux for reasoning in distributed description logics. In Description Logics Workshop 2004, CEUR-WS Vol 104, 2004.
13. L. Serafini and A. Tamilin. Drago: Distributed reasoning architecture for the semantic web. In ESWC, pages 361-376, 2005.
E-Connections:14. B. C. Grau. Combination and Integration of Ontologies on the Semantic Web. PhD
thesis, Dpto. de Informatica, Universitat de Valencia, Spain, 2005.15. O. Kutz, C. Lutz, F. Wolter, and M. Zakharyaschev. E-connections of abstract
description systems. Artif. Intell., 156(1):1-73, 2004.
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Thanks!
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SLM: exampleA schedule ontology
Hidden: details of the activity
Visible: there is an activity
[CTS06 Paper] a.k.a [1]
Package Package Hierarchy Scope Limitation
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DL Interpretation - Example
Interpretation: In any world (or called model) that conforms to the ontology
Ontology:
Dog I
AnimalI
• For any instance x of Dog, x is also an instance of Animal.
goofyI
• The individual goofy in the world is a Dog.
eatsI
• There is a y in the world, that a Dog x eats y and y is a DogFood
DogFoodI
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Messages
y y{C?}T1 T2
y y{C}
C(y)T1 T2
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Tableau ExpansionTableau Expansion for ALCPC with acyclic concept importing
More expressive extensions in action: SHOIQ + P