WP2: Tools

WonderWeb. Ontology Infrastructure for the Semantic Web. IST-2001-33052Project Review Meeting, 11th March, 2004.

WP2: Tools

Raphael Volz

Universität Fridericiana zu Karlsruhe (TH)


WonderWeb Tools

Tools now use OWL, the W3C standard for Web ontologies


WonderWeb Tools

KAON SERVER: Infrastructural KernelApplication Server using Semantic technologies formanagement of hosted components


• Functionality of common Application Server

• Flexible handling of Semantic Web modules(dynamic registering and unregistering)– FaCT– Racer– Ontobroker– KAON RDF stores– KAON Ontology stores– Sesame

• Extensible for future developments

• Generalization of RDF APIs (towards RDF Net API)

KAON SERVER Functionality


KAON SERVER Architecture

In terceptor

System Com ponent

Functional Com ponent

Proxy Com ponent

External M odule


Ontology is used for• component discovery• API discovery• classification of tools• implementation tasks ASSW is semantically enhanced application server!

KAON SERVER Semantic technologies

DOLCE

Core Ontology of Services

Descriptions & Situations

Several subontologies for the ASSW

Domain specific subontologies

Generic D

omain

Intermediate

Ontology Design:


WonderWeb Tools

LiftExtract light-weight ontologies from legacy information sourcesDB Schema, XML Schema, UML Models, Java Documentation


OntoLiFT

• Describes heuristics for extracting light-weight ontologies from important legacy resources:

– Relational Database Schema• Logical Schema found in running DBs

– XML Schema Languages • Generic formal approach building on

Regular Tree Grammars– UML Software Specifications

• Static Aspects of Software modelled in Class Diagrams

– JavaDoc Software Documentation• Text Mining techniques to extract ontologies from textual

Documentation


LiFT: Rel. DB Example


WonderWeb Tools

OilEdVisual Editor for creating OWL ontologies


What is OilEd?

• A simple ontology editor.

• Low cost, easy editor.

• A platform to explore how to use a reasoner.

• Originally intended as ademonstrator, now widelyused (>2000 downloads).

• Initially targeted at OIL,supports DAML+OIL,and now supports OWL.


Reasoning

• KB translated to equivalent DL model, and passed to a reasoner.• Spots inconsistent definitions

– e.g. contradictions in cardinality constraints or value restrictions.• mad cows!

• Organises the classification hierarchy– Discovering new superclasses.– Particularly useful when using defined classes.

• Subtle side-effects– Superclasses inferred due to domain/range restrictions.

• One shot connection to the reasoner. – Allows temporary inconsistency

• Communication with reasoner via KAON SERVER


WonderWeb Tools

ReasonersMultiple systems (FACT++,Hoolet, DLP) to reason with ontologiesCommon Interface (DIG) proposed and agreed upon (Racer, OWLP)


Reasoners

• Reasoners developed during the project (WP2) were crucial to the success of the standardisation activity.

• Why ? W3C standardisation requires demonstration of implementation experience, in particular:

• FaCT++• Hoolet (1st Order reasoner)• KAON DLP Prototype


DIG Interface

• A common interface to DL systems– Supported by FACT, FACT++, Racer, OWLP …

• A “new KRSS”.• XML Schema for concept language.• Using HTTP for communication.• Simple, “Level 0” approach

– Sufficient to support simple, “one-shot” applications, e.g. OilEd

• Largely developed in WonderWeb project


WonderWeb Tools

OntoDiffOntology Change DetectionMethodology plus practical tool support


Versioning tool OntoView

• Goal: tool for (ordinary) ontology engineers– helps to specify complete information about changes

• Functions:– compare versions of ontologies

• show propagation of change

• allows specification of conceptual relation

– distils the transformation operations

• patters of operations can be specified


Comparing ontology versions

• What should be compared?– not textual representation (like diff)

• formatting is not important

• could be different representations for same construct

– not logical theory

• small change might affect whole ontology

– instead look at “intended definition” of classes and properties

• groups of axioms that form a definition

• follows ideas of ontology engineer

• gives a “heuristic representation” of the change



WonderWeb Tools

Further ToolsDriving Theory and Practice of Web Ontology Field


Thank you !


about #Person

<owl:Class rdf:ID="Person"> <rdfs:subClassOf rdf:resource="#Animal"/> <rdfs:subClassOf> <owl:Restriction> <owl:onProperty rdf:resource="#hasParent"/> <owl:allValuesFrom rdf:resource="#Person"/> </owl:Restriction> </rdfs:subClassOf></owl:Class>

#Person rdf:type daml:Class#Person rdfs:subClassOf #Animal#Person rdfs:subClassOf anon_1 anon_1 rdf:type daml:Restrictionanon_1 owl:onProperty #hasParentanon_1 owl:allValuesFrom#Person

Change detection procedure

• Assume RDF-based ontology languages• Ontologies are parsed and stored as RDF triples

– group statements resulting from one “definition” (first level XML tree)

– identify group by rdf:ID / rdf:about statement


about #Person

#Person rdf:type owl:Class#Person rdfs:subClassOf #Animal#Person rdfs:subClassOf anon_1 anon_1 rdf:type owl:Restrictionanon_1 owl:onProperty #hasParentanon_1 owl:toClass #Person

v1 about #Person

#Person rdf:type owl:Class#Person rdfs:subClassOf #Animal

v2

about #parentOf

#parentOf rdf:type owl:Property#parentOf rdf:type owl:ObjectProperty

about #parentOf

#parentOf rdf:type owl:Property #parentOf rdf:type owl:ObjectProperty

Change detection - 2

• Versions are compared by aligning “groups of statements about same concept / property”– order is used in case of multiple occurrences


IF exist:old <A, Y, Z>* exist:new <X, Y, Z>* not-exist:new <X, Y, Z>*THEN change-type A

IF exist:old <X, rdfs:subClassOf, Y1> <Y1, rdf:type, owl:#Restriction> <Y1, owl:onProperty, Y2> <Y1, owl:allValuesFrom, Z> exist:new <X, rdfs:subClassOf, Y1> <Y1, rdf:type, owl:#Restriction> <Y1, owl:onProperty, Y2> not-exist:new <Y1, daml:toClass, Z>THEN logicalChange.localPropertyValue X

Change detection - 3• Rules are used to describe change types:

– language specific

– requires computation of RDFS closure

• i.e. all statements should be made explicit

• Example: find a change in a OWL slot restriction:


Change detection - 4

• Original file is used for visualisation of change– user specific formatting is preserved

• Strong points:– generic mechanism

• can be used with all RDFS based languages

– language specific parts are encoded in rules

– RDF data model hides a lot of syntactic changes

– existing tools are used for parsing, state maintenance and computation of RDFS closure

Documents

WP2: Tools