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Final presentation of the project I developed at the IRSS2013 in Athens, July 2013
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COLLONACollaborative Ontology AlignmentFinal Project Presentation
IRSS13 | 4-31 July | NCSR D
emokritos
Giorgos PapoutsakisJaakko Lapplaianen
Outline• Ontology• Ontology Alignment• COLLaborative ONtology Alignment• Future Work
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COLLONAOntologies 101
IRSS13 | 4-31 July | NCSR D
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Ontologies - What• Definition:“An ontology is defined as a formal explicit specification of a
shared conceptualization”• What kinds of things exist or can exist in the world?• what manner of relations can those things have to each other?• Ontology is more concerned with what is possible
• Ontology in Computer Science“An ontology formally represents knowledge as a set of
concepts within a domain, and the relationships between pairs of concepts.”• model a domain • support reasoning about concepts.
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Ontologies - Web Ontology Language
• Functional syntax• XML syntax• Manchester syntax• RDF/XML syntax• RDF/Turtle syntax
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Ontology(<http://example.com/tea.owl> Declaration( Class( :Tea ) ) )<http://example.com/tea.owl> rdf:type owl:Ontology .
:Tea rdf:type owl:Class .Ontology: <http://example.com/tea.owl> Class: Tea
<rdf:RDF ...> <owl:Ontology rdf:about=""/> <owl:Class rdf:about="#Tea"/>
</rdf:RDF>
<Ontology ontologyIRI="http://example.com/tea.owl" ...> <Prefix name="owl" IRI="http://www.w3.org/2002/07/owl#"/>
<Declaration> <Class IRI="Tea"/> </Declaration> </Ontology>
Ontologies - Example
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IRSS13 | 4-31 July | NCSR D
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Ontology - Applications• Semantic web• Specify a data modeling representation• Specify standard conceptual vocabularies• Provide services for answering queries• Publish reusable knowledge bases• Offer services to facilitate interoperability across multiple
heterogeneous systems and databases
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IRSS13 | 4-31 July | NCSR D
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COLLONAOntology alignment
IRSS13 | 4-31 July | NCSR D
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Alignment• Sets of correspondences between elements of two ontologies• Classes • Properties
• 3 kind of mappings• Equivalence• Subsumption• Supersumption
• Examples• Human = Person• Lion < Animal
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IRSS13 | 4-31 July | NCSR D
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Alignment API
“The Alignment API is a set of abstractions for expressing, accessing and sharing ontology alignments”
• Framework for communication• Well supported• Representation Classes• Ontology network• Alignment• Cell• Relation
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IRSS13 | 4-31 July | NCSR D
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Alignment applications• Avoid ontology merging• Use alignments as links between ontologies
• Distributed information retrieval• At query transformation step
• Understanding the semantics of the question• At result fusion step
• Putting together the results
• Human – Machine dialogues • Ontology evolution• Instance migration
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IRSS13 | 4-31 July | NCSR D
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COLLONAOur work
IRSS13 | 4-31 July | NCSR D
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COLLONA• Automatic alignment methods are not very accurate• Humans can not handle heavy work load • Humans are slow
• Automatic methods and humans need to collaborate to produce accurate results
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COLLONA – Core Tasks• Review of the main concepts regarding semi-automatic
alignment systems and standard APIs.
• Visualization of Ontological pairs.
• Authoring of mappings by users.
• Visualization of automatically produced mapping.
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COLLONA – Arch. & Data Flows
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COLLONA – Standard data formats
• Import• From ontologies files• From URI• From alignment file
• Export• Alignment file
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COLLONA – First problems
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COLLONA – Further problems
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COLLONA - Divide & Conquer• Graph shows only the class herierarchy
• Panels for class information• Properties• Axioms
• Panels for mappings• Class mappings• Property Mappings
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COLLONA – More features
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COLLONA today
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COLLONAFuture work
IRSS13 | 4-31 July | NCSR D
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Future work - Synergies
• The tool does not distinguish between machines and users when importing/exporting mappings• The user becomes a new alignment method• This homogeneous feature allows• Machine alignment / user validator• Machine / user competition• Hybrid approaches, complex data flows for iterative
mapping refinement• Alignment as a Service – Synergy with CLIC project
• This is a step forward on ontology mapping quality
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User validation• Supervised alignment• Algorithm evaluation and refinement
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Bad computer!
Stupid Computer!
Machine-user competition• Expert evaluation and training
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Hybrid approaches• Combine human and machine workflows to iteratively refine
ontology mappings
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Customer
Mappings
Alignment service 2 Alignment service 3Alignment service 1
ALIGN!
Negotiation layer
New Mappings
Mapping requestCustomerMappings
Customer
Service registration, data
Negotiation
COLLONA @ CLIC Framework
COLLONAThank you!!
IRSS13 | 4-31 July | NCSR D
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