WonderWeb. Ontology Infrastructure for the Semantic Web. IST-2001-33052 Project Review Meeting, 11 th March, 2004. WP2: Tools Raphael Volz Universität.

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Presentation transcript:

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WP2: Tools Raphael Volz Universität Fridericiana zu Karlsruhe (TH)

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools Tools now use OWL, the W3C standard for Web ontologies

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools KAON SERVER:Infrastructural Kernel Application Server using Semantic technologies for management of hosted components

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

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, KAON SERVER Architecture

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, 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 Domain Intermediate Ontology Design:

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools Lift Extract light-weight ontologies from legacy information sources DB Schema, XML Schema, UML Models, Java Documentation

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

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, LiFT: Rel. DB Example

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools OilEd Visual Editor for creating OWL ontologies

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, What is OilEd? A simple ontology editor. Low cost, easy editor. A platform to explore how to use a reasoner. Originally intended as a demonstrator, now widely used (>2000 downloads). Initially targeted at OIL, supports DAML+OIL,and now supports OWL.

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, 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. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools Reasoners Multiple systems (FACT++,Hoolet, DLP) to reason with ontologies Common Interface (DIG) proposed and agreed upon (Racer, OWLP)

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, 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 (1 st Order reasoner) KAON DLP Prototype

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, 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. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools OntoDiff Ontology Change Detection Methodology plus practical tool support

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

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

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WonderWeb Tools Further Tools Driving Theory and Practice of Web Ontology Field

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, Thank you !

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, about #Person #Personrdf:type daml:Class #Personrdfs:subClassOf#Animal #Personrdfs:subClassOfanon_1 anon_1rdf:typedaml:Restriction anon_1owl:onProperty#hasParent anon_1owl: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

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, about #Person #Personrdf:typeowl:Class #Personrdfs:subClassOf#Animal #Personrdfs:subClassOfanon_1 anon_1rdf:typeowl:Restriction anon_1owl:onProperty#hasParent anon_1owl:toClass#Person v1v1 about #Person #Personrdf:typeowl:Class #Personrdfs:subClassOf#Animal v2v2 about #parentOf #parentOfrdf:typeowl:Property #parentOfrdf:typeowl:ObjectProperty about #parentOf #parentOfrdf:typeowl:Property #parentOfrdf:typeowl:ObjectProperty Change detection - 2 Versions are compared by aligning “groups of statements about same concept / property” –order is used in case of multiple occurrences

WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, IF exist:old * exist:new * not-exist:new * THEN change-type A IF exist:old exist:new not-exist:new 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:

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