Research activity including geographical ontology modules for efficient semantic web reuse
This presentation is the property of its rightful owner.
Sponsored Links
1 / 32

Research Activity including Geographical Ontology Modules for Efficient Semantic Web Reuse PowerPoint PPT Presentation


  • 47 Views
  • Uploaded on
  • Presentation posted in: General

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

Download Presentation

Research Activity including Geographical Ontology Modules for Efficient Semantic Web Reuse

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Research activity including geographical ontology modules for efficient semantic web reuse

Research ActivityincludingGeographical Ontology Modules forEfficient Semantic Web Reuse

David George, University of Central Lancashire


Research activities

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


Research activities1

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


Structural semantic heterogeneity

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)


Data integration

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


Research activity including geographical ontology modules for efficient semantic web reuse

Jena Toolkit – OWL interface


Ontology specification best practice

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)


Formal concept analysis

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)


Formal concept analysis1

Formal Concept Analysis

Example:

Classes represented by table joins


Creating geographical ontology modules for efficient semantic web reuse

Creating Geographical Ontology Modules forEfficient Semantic Web Reuse


Ontology and integration

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


Ontology integration

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)


1 informal specific class reuse

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”


2 formalised specific class reuse

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>


3 modularity by sub domain separation

3 - “Modularity” by sub-domain separation

  • SWOOP permits ontology partitioning (module extraction)


4 class reuse by ontology import

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”


Alternative reuse approach

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.


Ontological inefficiency

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)


Ontology permanence

Fixed Classes

Variable Classes

Ontology Permanence


Ontology geo modules

Ontology “Geo-Modules”

Transportation

Tourism

Multi-modal

Geo-Modules


Land transport

multimodal

single-mode ?

Land Transport


Transport interchange

Transport Interchange

  • multimodal: road-rail

  • within a town, service facility


Visualising our transportation domain

M6

M67

A6

Visualising Our Transportation Domain


Rail transport ontology

PopulationGroupConcept

Road domain

endsAt*

endsAt*

City

City

startsFrom*

startsFrom*

Rail Transport Ontology

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


Road transport ontology

PopulationGroupConcept

Rail domain

endsAt*

City

startsFrom*

Road Transport Ontology

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


Landtransport ontology

LandTransport Ontology


Landtransport import consequences

LandTransport: Import Consequences

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

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


Revisualisation transportation layers

M6

M67

A6

Revisualisation: Transportation Layers


How do we develop geo modules

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


Transportation domain layers

Transportation Domain Layers


Modular ontology ve ve

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


References

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.


  • Login