The Semantic Weband

Efficient Reuse ofOntology Modules

MSc CO3701 Advanced Database Systems Research Topics

5 March 2008

David George, Dept. Computing, UCLan.

What is the Semantic Web?

• A project aimed to make web pages machine understandable.

“An extension of the current Web, … information given well-defined meaning, …enabling computers and people to work in co-operation”

(Berners-Lee et al, 2001)

• A universal medium for information integration and exchange.

• Uses Ontology – a formal domain representation that specifies the meaning (semantics) of a domain or context.

We have the Web: a Global Information Space

Some current Web statistics• Approx. 70m web sites• Circa 15-20 billion pages (files)

Semantic Web share• 0.004% usable Semantic Web files (800k)• 0.00005% are Ontology files (10k)

Swoogle

Visualising the Semantic Web?

DE BRUIJN, J. (2003) Using Ontologies - Enabling Knowledge Sharing and Reuse on the Semantic Web [online]. DERI – Digital Enterprise Research Institute. Available from: http://www.deri.ie/publications/techpapers/documents/DERI-TR-2003-10-29.pdf. [Accessed 4 March 2008].

What is an Ontology?

• “An Ontology is a formal, explicit specification of a shared conceptualization”

(Gruber, 1993 & Borst, 1997).

constraints on those relationships

makesSolarFlightTo

Moon

moonRocket [ hasWeight = 100t ]

Every moonRocket makesSolarFlightTo only Moon

• Ontology specifies the vocabulary of a “Domain”

concepts and their attributes relationships between concepts

What does an Ontology look like?

Biblio-Thing

Document

Book

Periodical-Publication

Journal

Magazine

Newspaper

Thesis

Doctoral-Thesis

Master-Thesis

Agent

PersonAuthor Organisation

Publisher University

A useful source for ontologies:http://protegewiki.stanford.edu/index.php/Protege_Ontology_Library

An example of a Bibliographic Ontology

Semantic Web Technologies

• Based on “XML-based” RDF (Resource Description Framework) and OWL Ontology languages (W3C, 2004).

• OWL has foundations in Description Logics (DL)

– decidable fragments of First Order Logic.

• OWL can be reasoned with using DIG Reasoners (short for DL Implementation Group)

– Reasoner can establish subclass/superclass relationship of concept.

– Can infer equivalence, transitivity of classes and relations class

– Can determine ontology consistency.

• Built on subject, predicate, object triples [a statement]

• A statement may say: <student> <lastname> is <George>

• For example:

RDF (Resource Description Framework)

subject

objectpredicate

Uses for the Semantic Web?

• Data integration e.g. integrating heterogeneous database structures/schemas and semantics?

• Annotation of Internet resources i.e. Web pages – to assist Web crawler/robot/spiders. Semantic (Shadow) Web?

• Support Search Engine queries – to improve relevance of retrieval hits?

• Facilitation of understanding between e-government portal terminology and users natural language?

Typical Search Engine Query

Search Hits

Semantic

Semantic

KB

DB

a

a

a

a

a

a

a

a

Ontology Development

One large ontology or many?

– Complexity of ontology specification makes it impractical.

– How do you describe the world!!

– Ontologies conceptualised by domain specialists.

– Applications will require ontology integration capability.

– Fulfils Reuse capability

– Risk of redundancy through overlapping class sets.

So let’s consider Land Transport ….

Our Transport Ontology

Possible Application uses:

– Public transport services

– Commercial Freight services

– Linking towns and cities by road and rail

– We may need to consider bringing together road, rail and population centre ontologies.

But first, why not use an existing ontology?

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

see?– Small Ontology but describes multiple

sub-domains

• Potential redundancy• Vulnerability to change• How relevant are they?• Only for an application that uses

ALL concepts

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

Our Land Transport scenario

The Channel Tunnel Rail Link (CTRL) is the international connection and, whilst essentially a single mode of transport, it also interfaces with road transport. Other road-rail interfaces, not shown, might be level crossings and transport interchanges.     

    

Cheriton Channel Tunnel Terminal © OS Get-a-Map.The multimodal element of CTRL operation is the Channel Tunnel transport interchange in Cheriton, accessed by road and rail for its drive-on drive-off service

Let us assume the Rail domain contains various concept and relationship statements:

• RailRoute startsFrom RailwayStation• RailwayStation locatedIn City• RailRoute hasRailComponent RailwayLine• RailwayLine meetsObstacle LevelCrossing• LevelCrossing intersectionBetween (RailwayLine ⊓ Highway)• RailwayStation accessedVia Highway

These statements are combined to form the Rail model

NB: certain concepts (City, Highway) are likely to be logical concepts in Road and PopGroup sub-domains.

For the Road module fragment we have described that:

- a highway provides access to a city and transport facility- a drive-on/drive-off facility is available at a transport interchange- our highway encounters a railway (level crossing)- various operators use the transport interchange.

    

   

Again, for the Road domain we see that certain concepts (City, Highway) replicate the Rail sub-domain.

The PopGroup sub-domain shows various travel relationships including City and Town, and the DormitoryTownRole the latter may fulfil.

PopGroup would specify how concepts might be accessed from each other, again resulting in similar relationships as Rail and Road.

LandTransport OntologyWe have three sub-domains created as modules or contexts.

These Contexts might now be logically clustered within a multimodal LandTransport application ontology, itself containing general transport concepts: TransportInterchange, TransportOperator and various transport roles.

Import implications?: Road, Rail, PopGroup modules into LandTransport

Concept duplication and redundancy, e.g: rail:RailwayStation, road:RailwayStation and pop:RailwayStation; also between rail:City, road:City and pop:City.

We see:

Relation duplications, such as rail:encountersHazard and road:encountersHazard.

Land Transport + Contexts

So 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

Visualising de-integration of domains

This process of semantic-layering represents a conceptual process of module de-integration to make distinctions.

We reduce each sub-domain to a single context, e.g. the Rail model is depicted (next page).

Rail is now stated more formally:

Let a domain ontology O that contains concepts C, relations R and has a domain context CT be a set O = <<C(1,,,n)>, <R(1,,,n)>, CT>.

The multi sub-domain ontology set can then be represented as:O = <<(CP1,,,CPn),(CS1,,,CSn)>,<(RP1,,,RPn),(RS1,,,RSn)>,<CTP ,(CTS1,,,CTSn)>>

Transportation Domain Layers

In each sub-domain we differentiate between the primary concepts and relations and secondary. Any secondary concepts and relations are removed to be primary concepts and relations in their own contexts.

Comparisons show a reduction in classes (from 17 to 11) and in relations (34 to 20)

End