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Research Activity including Geographical Ontology Modules for Efficient Semantic Web Reuse

Research Activity including Geographical Ontology Modules for Efficient Semantic Web Reuse. David George, University of Central Lancashire. Research Activities. Semantic Heterogeneity Structural and Semantic discrepancies in database conceptualisation and development

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Research Activity including Geographical Ontology Modules for Efficient Semantic Web Reuse

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  1. Research ActivityincludingGeographical Ontology Modules forEfficient Semantic Web Reuse David George, University of Central Lancashire

  2. 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

  3. 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

  4. 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)

  5. Data Integration Global Domain Agreements Knowledge Digital media Visual/Spatial/Temporal Data [Kiosk/Geographic/Flights/Forecasting] Focus – Semantics Domain-specific Information Structured, Semi-structured Text repositories Data Structured DBs, Files Focus – Systems & Communications System Schema Integration Common Data Models Virtual Integration Single Ontologies Multiple ontologies, Inter-ontological Local Task Schemas Federated DBS Federated IS (inc Mediators) Information Brokering 1985 1995

  6. Jena Toolkit – OWL interface

  7. Ontology Specification: Best Practice Ontology elements can be described as: • Primitives: self-standing entities (objects/forms) e.g. Structure, Process, System, Organisation • Relations: concept-linking properties e.g. XhasFormY, hasRole … • Roles: functions e.g. RailTransportRole and • Definables: dependent concepts defined by combining Primitives, Relations, and Roles: • RailwayBridge≡Bridge⊓ (hasForm∃ Structure⊓ • hasRole∃ RailTransportRole)

  8. 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)

  9. Formal Concept Analysis Example: Classes represented by table joins

  10. Creating Geographical Ontology Modules forEfficient Semantic Web Reuse

  11. 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

  12. Ontology Integration Possible Ontology [ On ] Objectives • Merger: OA + OB→ OC • Alignment: OA≡ OB≡ OC • 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)

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

  14. 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>

  15. 3 - “Modularity” by sub-domain separation • SWOOP permits ontology partitioning (module extraction)

  16. 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 classes 1256 properties load time 1.5 to 7.5 mins Protégé “out of memory”

  17. 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.

  18. Ontological Inefficiency • Potential redundancy • Vulnerability to change • How relevant are they? • Ontology Reuse - Imports • E.g. if OTN 1 is imported: what do we see? • Ontology much smaller than Cyc, but still multiple sub-domains • Only for an application that uses ALL concepts 1OTN - Ontology of Transportation Networks (Lorenz et al, 2005)

  19. Fixed Classes Variable Classes Ontology Permanence

  20. Ontology “Geo-Modules” Transportation Tourism Multi-modal Geo-Modules

  21. multimodal single-mode ? Land Transport

  22. Transport Interchange • multimodal: road-rail • within a town, service facility

  23. M6 M67 A6 Visualising Our Transportation Domain

  24. PopulationGroupConcept Road domain endsAt* endsAt* City City startsFrom* startsFrom* Rail Transport Ontology Q: rename LevelCrossing → RoadCrossing? But we don’t do Roads in Rail!

  25. PopulationGroupConcept Rail domain endsAt* City startsFrom* Road Transport Ontology Q: reclassify ChannelTunnelTerminal → Road Concept? But we don’t do Rail in Roads!

  26. LandTransport Ontology

  27. LandTransport: Import Consequences • We would need to import: Road, Rail, PopGroups into LandTransport • For just Road and Rail it results in duplications and redundancy

  28. M6 M67 A6 Revisualisation: Transportation Layers

  29. 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

  30. Transportation Domain Layers

  31. 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

  32. 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.

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