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Research Activity

including

Geographical Ontology Modules forEfficient Semantic Web Reuse

David George, University of Central Lancashire

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Research Activities

• Semantic Heterogeneity

– Structural and Semantic discrepancies in database conceptualisation and development

• Data and Information Integration

– Federated Databases

– Mediators: Global-as-View, Local-as-View

– Information Brokering Systems and use of Ontology

• Semantic Web and Ontology

• Practical interaction with Semantic Web Technologies

– Protégé, FaCT++, SWOOP, and Jena API Toolkit

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Research Activities

• Development of Jena-based Java Browser Interface: inc

– Reading OWL and querying SPARQL

– RDF storage in MySQL

• Foundation Ontology: SUMO, DOLCE, CyC, BFO (Snap and Span)

• Design Best-Practice: Modularity in Ontology development (Rector, 2003)

• Experimentation with small-scale OWL ontologies

• Formal Concept Analysis - using Concept Explorer

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Structural & Semantic Heterogeneity

• Abstraction Level Conflicts– generalisation/specialisation/aggregation

• Schematic Discrepancies– Objects represented differently

– Data, attributes, entity

• Entity Definition Conflicts– naming conflicts (synonyms and homonyms)

– database identifier conflicts e.g. id# v. name

• Data Value Conflicts– temporal Inconsistency (last update)

– data representation (integer v. string/precision/scale)

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Data Integration

System

Knowledge

Data

Information

Federated DBS Federated IS (inc Mediators) Information Brokering

Global DomainAgreements

Global DomainAgreements

Local TaskSchemas

Local TaskSchemas

1985 1995

Digital mediaVisual/Spatial/Temporal Data[Kiosk/Geographic/Flights/Forecasting]

Structured,Semi-structuredText repositories

Structured DBs, Files

Virtual IntegrationSingle Ontologies

Multiple ontologies,Inter-ontological

Focus – SemanticsDomain-specific

Focus – Systems& Communications

Schema IntegrationCommon Data Models

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Jena Toolkit – OWL interface

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Ontology Specification: Best Practice

Ontology elements can be described as:

RailwayBridge ≡ Bridge ⊓ (hasForm ∃ Structure ⊓ hasRole ∃ RailTransportRole)

– Primitives: self-standing entities (objects/forms) e.g. Structure, Process, System, Organisation

– Relations: concept-linking properties e.g. X hasForm Y, hasRole …

– Roles: functions e.g. RailTransportRole

and– Definables: dependent concepts defined by combining Primitives,

Relations, and Roles:

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Formal Concept Analysis

• Using Concept Explorer

• Examined how Concept Analysis may be useful in identifying Classes and Instances in database tables

• Considered structural heterogeneity:

– Classes represented by single entity (table)

– Classes represented by table joins

– Classes as subset of table records

– Instances represented by entity, attribute, data (record)

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Formal Concept Analysis

Example:

Classes represented by table joins

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Creating Geographical Ontology Modules for

Efficient Semantic Web Reuse

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Ontology and Integration

• Ontology Reuse is a key Integration benefit (Noy and Hafner, 1997 ).

• Ontology development still at a stage where little interchange between organisations?

• Merger, Alignment and Mapping complexity issues with Integration.

• Developer reluctance – easier to re-invent own local ontology than reuse.

• Reuse of an external ontology will likely result in descriptive and structural irrelevances.

• Smaller component ontology modules –improvised as required – may encourage wider usage/take-up

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Ontology Integration

Possible Ontology [ On ] Objectives

1. Merger: OA + OB → OC

2. Alignment: OA ≡ OB ≡ OC

3. Mapping: a virtual integration where OA, OB and OC concepts are semantically related.

Methods– 1 and 2 are achieved by rewriting (reformulation).

– Original ontologies are subsumed or made consistent (respectively).

– 3 is achieved by mappings between concepts of imported ontologies. A, B and C endure autonomously.

– Ontology Reuse, in this presentation, refers to 3: Mapping.

(Pinto et al., 1999, Noy and Musen, 1999, de Bruijn et al., 2004, Visser and Tamma, 1999, Kalfoglou and Schorlemmer, 2003, Ding et al., 2002)

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1 - “Informal” specific Class Reuse

• Using namespace declaration to explicitly specify a single external concept, e.g.

<rdf:RDF xmlns="http://www.livewiredg.myby.co.uk/rdf/geo-layers/rail.owl#" xmlns:cyc="http://www.cyc.com/2003/04/01/cyc#" > <owl:Class rdf:about="&cyc;TransportationCompany"/> <owl:Class rdf:ID="RailOperator"> <rdfs:subClassOf rdf:resource="#RailwayComponent"/> <rdfs:subClassOf rdf:resource="&cyc;TransportationCompany"/> </owl:Class> ……..

<rdf:RDF xmlns="http://www.livewiredg.myby.co.uk/rdf/geo-layers/rail.owl#" xmlns:cyc="http://www.cyc.com/2003/04/01/cyc#" > <owl:Class rdf:about="&cyc;TransportationCompany"/> <owl:Class rdf:ID="RailOperator"> <rdfs:subClassOf rdf:resource="#RailwayComponent"/> <rdfs:subClassOf rdf:resource="&cyc;TransportationCompany"/> </owl:Class> ……..

• How would an agent understand the Cyc context of the superclass of “cyc:TransportationCompany”

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2 - “Formalised” specific Class Reuse

E-Connections

• Representation and reasoning with foreign ontologies (Grau et al, 2006)

• Allows specific concept linking. Few tools available e.g. SWOOP (OWL Ontology Editor)

<rdf:RDF xmlns:global="http://www.livewiredg.myby.co.uk/rdf/geo-layers/global.owl#" xmlns=http://www.owl-ontologies.com/flight.owl# ……..>

<owl:Class rdf:about=“&global;Artifact"/> <owl:Class rdf:ID="Helicopter"> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty> <owl:LinkProperty rdf:about="#hasForm"/> </owl:onProperty> <owl:someValuesFrom rdf:resource="&global;Artifact"/> </owl:Restriction> </rdfs:subClassOf> </owl:Class>

<owl:LinkProperty rdf:ID="hasForm"> <owl:foreignOntology rdf:resource="&global;"/> <rdfs:domain rdf:resource="#Helicopter"/> <rdfs:range> <owl:foreignClass rdf:about="&global;Artifact"> <owl:foreignOntology rdf:resource="&global; "/> </owl:foreignClass> </rdfs:range> </owl:LinkProperty>

<rdf:RDF xmlns:global="http://www.livewiredg.myby.co.uk/rdf/geo-layers/global.owl#" xmlns=http://www.owl-ontologies.com/flight.owl# ……..>

<owl:Class rdf:about=“&global;Artifact"/> <owl:Class rdf:ID="Helicopter"> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty> <owl:LinkProperty rdf:about="#hasForm"/> </owl:onProperty> <owl:someValuesFrom rdf:resource="&global;Artifact"/> </owl:Restriction> </rdfs:subClassOf> </owl:Class>

<owl:LinkProperty rdf:ID="hasForm"> <owl:foreignOntology rdf:resource="&global;"/> <rdfs:domain rdf:resource="#Helicopter"/> <rdfs:range> <owl:foreignClass rdf:about="&global;Artifact"> <owl:foreignOntology rdf:resource="&global; "/> </owl:foreignClass> </rdfs:range> </owl:LinkProperty>

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3 - “Modularity” by sub-domain separation

• SWOOP permits ontology partitioning (module extraction)

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4 - Class reuse by Ontology Import

Objective:

Map Rail Ontology class “RailOperator” to Cyc Ontology class “TransportationCompany”

Action:

Import Opencyc into Rail > 6.8MB

Effect:

Adds:2843 classes1256 propertiesload time 1.5 to 7.5 minsProtégé “out of memory”

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Alternative Reuse approach?

• Consider the way Ontologies conceptualised and developed?

• Break down domain ontologies into sub-domains (modules)

• Try to achieve disjoint structures – minimise redundancy

• Can be demonstrated using Geographical context

• Geographical concepts interface with virtually every aspect of daily life and feature prominently in information management systems.

• Geographical ontologies offer a logical vehicle, to examine how modules can be specified efficiently and effectively.

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Ontological Inefficiency

• Ontology Reuse - Imports– E.g. if OTN 1 is imported: what do we

see?– Ontology much smaller than Cyc, but still

multiple sub-domains

• Potential redundancy• Vulnerability to change• How relevant are they?

• Only for an application that uses ALL concepts

• Only for an application that uses ALL concepts

1 OTN - Ontology of Transportation Networks (Lorenz et al, 2005)

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Ontology Permanence

Fixed Classes

Variable Classes

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Transportation Tourism

Ontology “Geo-Modules”

Geo-Modules

Multi-modal

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Land Transport

multimodal

single-mode ?

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Transport Interchange

• multimodal: road-rail • within a town, service facility

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Visualising Our Transportation Domain

M67M6

A6

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Rail Transport Ontology

City

endsAt*

startsFrom*

Road domain

PopulationGroupConcept

City

endsAt*

startsFrom*

Q: rename LevelCrossing → RoadCrossing? But we don’t do Roads in Rail!

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Road Transport Ontology

Rail domain

Q: reclassify ChannelTunnelTerminal → Road Concept? But we don’t do Rail in Roads!

PopulationGroupConcept

City

endsAt*

startsFrom*

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LandTransport Ontology

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LandTransport: Import Consequences

• We would need to import: Road, Rail, PopGroups into LandTransport

• For just Road and Rail it results in duplications and redundancy

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Revisualisation: Transportation Layers

M67M6

A6

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How do we develop “Geo-Modules”

• Need to “de-integrate” to allow low-cost integration

• Aim towards “effectively” disjoint domains

• Deliver by removing concept duplication between modules – redundancy

• Need to promote/relegate multi or single-context concepts and relations

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Transportation Domain Layers

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Modular Ontology: +ve/-ve

• Advantages– Small is manageable– Select only required building block modules– Independent therefore less vulnerable to change– Change is isolated to the module and subsuming

domain?

• Disadvantages– Increased mappings?– Needs to be examined

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References

DE BRUIJN, J., DING, Y., ARROYO, S. & FENSEL, D. (2004) Semantic Information Integration in the COG project [online]. Digital Enterprise Research Institute (DERI), University of Innsbruck. Available from: http://www.cogproject.org/publications/sii-wp.pdf. [Accessed 19 December 2004].

DING, Y., FENSEL, D., KLEIN, M. & OMELAYENKO, B. (2002) The semantic web: yet another hip? Data & Knowledge Engineering, 41(2), pp. 205-227.

DING, Y. & FOO, S. (2002) Ontology Research and Development: Part 2 - A Review of Ontology mapping and evolving. Journal of Information Science, 28(5), pp. 383-396.

GRAU, B. C., PARSIA, B. & SIRIN, E. (2006) Combining OWL ontologies using E-Connections. Journal of Web Semantics: Science, Services and Agents on the World Wide Web, 4(1), pp. 40-59.

KALFOGLOU, Y. & SCHORLEMMER, M. (2003) Ontology mapping: the state of the art. The Knowledge Engineering Review, 18(1), pp. 1-31.

NOY, N. F. & HAFNER, C. D. (1997) The State of the Art in Ontology Design - A Survey and Comparative Review. AI Magazine, 18(3), pp. 53-74.

NOY, N. F. & MUSEN, M. A. (1999) SMART: Automated Support for Ontology Merging and Alignment Stanford, MA, Stanford Medical Informatics. Available from: http://www-smi.stanford.edu/pubs/SMI_Reports/SMI-1999-0813.pdf. [Accessed 22 December 2004].

PINTO, H. S., GÓMEZ-PÉREZ, A. & MARTINS, J. P. (1999) Some Issues on Ontology Integration. In: Proceedings of IJCAI-99 workshop on Ontologies and Problem-Solving Methods (KRR5). Stockholm, Sweden, August 2 1999. CEUR-WS, pp. 7.1-7.12.

RECTOR, A. L. (2003) Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In: Proceedings of 2nd International Conference On Knowledge Capture. Sanibel Island, FL, USA, 2003. ACM Press, New York, NY, USA, pp. 121-128.

VISSER, P. R. S. & TAMMA, V. A. M. (1999) An Experience with Ontology-based Agent Clustering. In: Proceedings of IJCAI-99 workshop on Ontologies and Problem-Solving Methods (KRR5). Stockholm, Sweden, 2 August 1999. CEUR-WS, pp. 12.1-12.13.