Lifecycle Support for Networked Ontologies And related research in KMi Mathieu dAquin and Marta...

Lifecycle Support for Networked OntologiesLifecycle Support for Networked Ontologies

And related research in KMi

Mathieu d’Aquin and Marta Sabou

And also Enrico Motta, Martin Dzbor, Lucia Sepia, Sofia Angeletou, Laurian Gridinoc and Claudio Baldassarre

IST-2005-027595NeOn-project.org

The Semantic WebThe Semantic Web

A large scale, heterogenous collection of formal, machine processable, ontology-based statements (semantic metadata) about web resources and other entities in the world, expressed in a XML-based syntax

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2003 2004

#SW Pages

Lee, J., Goodwin, R. (2004) The Semantic Webscape: a View of the Semantic Web. IBM Research Report.

Ontology

Metadata

UoD

<rdf:RDF><channel rdf:about=“http://watson.kmi.open.ac.uk/blog”><title>Elementaries - The Watson Blog</title><link>http://watson.kmi.open.ac.uk:8080/blog/</link><description>"Oh dear! Where the Semantic Web is going to go now?" -- imaginary user 23</description><language>en</language><copyright>Watson team</copyright><lastBuildDate>Thu, 01 Mar 2007 13:49:52 GMT</lastBuildDate><generator>Pebble (http://pebble.sourceforge.net)</generator><docs>http://backend.userland.com/rss</docs>…

<rdf:RDF><channel rdf:about=“http://watson.kmi.open.ac.uk/blog”><title>Elementaries - The Watson Blog</title><link>http://watson.kmi.open.ac.uk:8080/blog/</link><description>"Oh dear! Where the Semantic Web is going to go now?" -- imaginary user 23</description><language>en</language><copyright>Watson team</copyright><lastBuildDate>Thu, 01 Mar 2007 13:49:52 GMT</lastBuildDate><generator>Pebble (http://pebble.sourceforge.net)</generator><docs>http://backend.userland.com/rss</docs>…

<rdf:RDF> <foaf:Image rdf:about='http://static.flickr.com/132/400582453_e1e1f8602c.jpg'> <dc:title>Zen wisteria</dc:title> <dc:description></dc:description> <foaf:page rdf:resource='http://www.flickr.com/photos/xcv/400582453/'/> <foaf:topic rdf:resource='http://www.flickr.com/photos/tags/vittelgarden/'/> <foaf:topic rdf:resource='http://www.flickr.com/photos/tags/wisteria/'/> <dc:creator> <foaf:Person><foaf:name>Mathieu d'Aquin</foaf:name> …

<rdf:RDF> <foaf:Image rdf:about='http://static.flickr.com/132/400582453_e1e1f8602c.jpg'> <dc:title>Zen wisteria</dc:title> <dc:description></dc:description> <foaf:page rdf:resource='http://www.flickr.com/photos/xcv/400582453/'/> <foaf:topic rdf:resource='http://www.flickr.com/photos/tags/vittelgarden/'/> <foaf:topic rdf:resource='http://www.flickr.com/photos/tags/wisteria/'/> <dc:creator> <foaf:Person><foaf:name>Mathieu d'Aquin</foaf:name> …

<rdf:RDF> <owl:Ontology rdf:about=""> <owl:imports rdf:resource="http://usefulinc.com/ns/doap#"/> </owl:Ontology> <j.1:Organization rdf:ID="KMi"> <rdfs:comment rdf:datatype="http://www.w3.org/2001/XMLSchema#string" >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment> </j.1:Organization> <j.1:Document rdf:ID="KMiWebSite"> …

<rdf:RDF> <owl:Ontology rdf:about=""> <owl:imports rdf:resource="http://usefulinc.com/ns/doap#"/> </owl:Ontology> <j.1:Organization rdf:ID="KMi"> <rdfs:comment rdf:datatype="http://www.w3.org/2001/XMLSchema#string" >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment> </j.1:Organization> <j.1:Document rdf:ID="KMiWebSite"> …

DOAP

FOAFDC

RSS TAPWORDNET

NCI GalenMusic

…

…… …

…

…


SW = A Conceptual Layer over the webSW = A Conceptual Layer over the web


SW is Heterogeneous!SW is Heterogeneous!


The NeOn ProjectThe NeOn Project

NeOn is not 100% dependent on the SW– NeOn is really about developing large scale semantic applications.

However the SW as a large-scale, heterogeneous semantic layer over the web provides a natural focus for characterizing the NeOn project.

In other Words, the issues characterizing the NeOn project…– heterogeneity, – large-scale semantics, – metadata and ontology dynamics, – distributed development, etc.

…perfectly fit the emerging semantic web scenario


Economic vision underpinning NeOnEconomic vision underpinning NeOn

The vision of a knowledge-based economy supported by the availability of large scale semantic information

– Key is the ability to build open, ontology-based applications able to scale up to large quantities of data and to evolve, as heterogeneous data are dynamically generated on the (semantic) web

Ontologies become central– Semantic web built around ontologies– Ontologies key enablers for handling interoperability


Current technological limitationsCurrent technological limitations

No adequate infrastructure for the whole application development lifecycle of the envisaged applications

Specifically, current infrastructures not effective – Do not scale up – Poor support for rapid development of large applications by reuse

• Reuse typically so expensive that people prefer to re-build from scratch• Problem concerns both the lack of methodologies as well

tools/techniques

– Poor support for managing the evolution of an application– Poor support for collaborative development – Limitations of current user interfaces

• E.g., support for navigating several large ontologies at the same time

Software crisis all over again?


AmbitionAmbition

Overall goals– major integrative effort aiming at providing a radical ‘leap forward’ by

developing the infrastructure needed to make large-scale semantic application development feasible and cost-effective

– lowering the entry barrier for organizations needing semantic solutions– targeting robustness, scalability, multi-ontology scenarios, multi-

user development, multi-lingual solutions, ..

Emphasis– On concrete engineering solutions– On concrete support for life-cycle activities– On measurable improvements

Ambition on the technology level (4 yrs)– NeOn as the standard reference infrastructure for large-scale

semantic web application development


Key Planned OutputsKey Planned Outputs

System-level contributions (methodology, architecture, toolkit)– An open, service-centred reference architecture for managing the

complete lifecycle of networked ontologies and meta-data– The NeOn toolkit for system development with NOs– The NeOn methodology for sys. development with NOs

Contributions to foundational research – Methods and tools for managing dynamic, evolving, possibly

inconsistent and contextually grounded networked ontologies– Methods and tools for supporting large-scale collaborative

development

Also…– Sector-level: Three innovative testbeds in two sectors– Community-level: Creation of an active community of users and

developers


TestbedsTestbeds

Managing fishery knowledge to support automatic alert mechanisms

– United Nations Food and Agriculture Organization

E-Invoice management in the pharmaceutical sector– AECE/PharmaInnova

Integration and management of information about pharmaceutical products

– Atos Origin


PartnersPartners

• KMi, the Open University• University of Sheffield

• Universität Koblenz-Landau• Software AG• Universität Karlsruhe• Ontoprise GmbH

•Institute 'Jozef Stefan’

• Institut National de Recherche en Informatique et en Automatique

•Asociación Española de Comercio Electrónico - PharmaInnova Cluster• Universidad Politécnica de Madrid • Atos Origin SAE• Intelligent Software Components SA

• Consiglio Nazionale delle Ricerche• Food and Agriculture Organization of the United Nations


NeOn at KMi:

Supporting and developing next generation Semantic Web applications


Example: MagpieExample: Magpie


Example: PowerAquaExample: PowerAqua


Next Generation Semantic Web Next Generation Semantic Web ApplicationsApplications


Next Generation Semantic Web Next Generation Semantic Web ApplicationsApplications

NG SW Application

Able to exploit the SW at large – Dynamically retrieving the relevant semantic

resources – Combining several, heterogeneous Ontologies– …

Need tools to efficiently access the knowledge available on the SW: a Gateway…


Swoogle…Swoogle…

Existing Semantic Web Gateway, but…


Limitations of SwoogleLimitations of Swoogle

No quality control mechanisms– Many ontologies are duplicated– No quality information provided

Limited Query/Search mechanisms– Only keyword search, we need more powerful query methods (e.g.,

ability to pose formal queries)

Limited range of ontology ranking mechanisms– Swoogle only uses a 'popularity-based' one

No support for relations between ontologies– Duplication, incompatibility (contradiction), modularization, versioning,

etc.


Watson: (truly) a Gateway to the SWWatson: (truly) a Gateway to the SW


Watson ArchitectureWatson Architecture

Keyword Search

SPARQLQuery

Crawling Parsing(Jena)

Validation/Analysis

Indexing

RepositoryURLs Metadata Indexes

populates populates populates populatesusedextractedretrieved

OntologyExploration

queries queriesqueriesqueries queries

request

WWW

discovered

Collecting Analyzing

Querying


The current content of WatsonThe current content of Watson

The current demo version of Watson have collected more than 7500 (syntactically unique) semantic documents

– Could do more, but limited by our current test server…– 2983 RDF or RDF(S), 1997 OWL, 1391 DAML, 302 RSS, 83 FOAF, 133

mixed (e.g, OWL+DAML(5) or OWL+FOAF+RSS(1))– Lots of ontologies are in OWL FULL (3x the number of OWL Lite)– … but most of the ontologies use only a very restricted sub-part of the

expressivity of OWL and DAML, e.g.,• only 147 go beyond ALC• role transitivity is used in only 11 ontologies

– 1304 (semantic) duplications detected (to be refined)– About 300,000 entities extracted– typeOf and subClassOf are the most popular relations– Language information is rarely used but:

• English is clearly the most employed language • Then come in this order de, fr, fi, pt, es, tr, nl


Example: selection of the Example: selection of the complementary ontologies complementary ontologies


Formal Queries and relation discovery…Formal Queries and relation discovery…


Going Further: Knowledge SelectionGoing Further: Knowledge Selection

t2

t1tn

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OntologySelection

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…tn

Web

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The ideal world (Web)The real world (Web)Knowledge Selection

Ontology Modularization

t1tn

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Ontology Modularization

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Ontology Modularization t3

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tnOntology Merging


Modularization: Example 2Modularization: Example 2http://www.co-ode.org/ontologies/test/breaksmetrics.owlhttp://www.co-ode.org/ontologies/test/breaksmetrics.owl

…


Modularization: Example 2Modularization: Example 2Resulting moduleResulting module

Cancer

Lung

AdenoCarcinoma


ImplementationImplementation


ImplementationImplementationIntegration with ontology selectionIntegration with ontology selection


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–Label similarity methods •e.g., Full_Professor = FullProfessor

–Structure similarity methods•Using taxonomic/property related information

Ontology MatchingOntology Matching


New paradigm: use of background New paradigm: use of background knowledgeknowledge

A B

Background Knowledge(external source)

A’ B’R

R


Where the background knowledge comes from?Where the background knowledge comes from?

Aleksovski et al. EKAW’06• A richly axiomatized domain ontology • Assumes that a suitable domain ontology is available.

van Hage et al. ISWC’05• Google and an online dictionary in the food domain• Noise introduce by the use of IR technique on a Web corpus

A Brel

+ OnlineDictionary

IR Methods


• rely on online ontologies (Semantic Web) to derive mappings• ontologies are dynamically discovered and combined

A Brel

Semantic Web

Our Approach:Our Approach:Using the SW as background knowledgeUsing the SW as background knowledge

• Exploit the Semantic Web: next generation Semantic Web application• Does not rely on any pre-selected knowledge sources.


ExamplesExamples

ka2.rdf

Researcher AcademicStaff

Sem

anti

c W

eb

Researcher

AcademicStaff

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⊆

ISWC SWRC

Both concepts are found in one ontology

Ham SeaFoodS

eman

tic

Web

HamSeaFood

Meat

Meat

SeaFood

Concepts are related across several ontologies

Agrovoc NALT

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€

⊥

€

⊥

€

⊥

pizza-to-go

wine.owl

NALT


Evaluation: 1600 mappings, two teams

Average precision: 70% (comparable/better than standard)

(derived from 180 different ontologies)

Matching AGROVOC (16k terms) and NALT(41k terms)

Large Scale EvaluationLarge Scale Evaluation


Back to the Web: FolksonomiesBack to the Web: Folksonomies

Tags are popular, easy to use annotations

But they are not structured…

No computable semantics…


Finding tagged imagesFinding tagged images

FlowerRose

Lilac

LilacFlower

TulipFlowersCutFlower

Tulip


FlowerRose

Lilac

LilacFlower


Tulip

Finding tagged images –Finding tagged images –

FLOWERFLOWER


What if …What if …

Rose Tulip

Flower

Lilac

…folksonomies were semantically richer


FlowerRose

Lilac

LilacFlower


Tulip

Finding tagged images –Finding tagged images –FLOWER (II)FLOWER (II)

Rose Tulip

Flower

Lilac


Learning Relations Between TagsLearning Relations Between Tags

Tags

{camera, digital slr, photograph} {damage, flooding, hurricane, katrina, Louisiana} Clusters

Digital SLR

cameraphotographtakenWith

Ontologies

NLP/ClusteringNLP/Clustering

Find and combine Online ontologies +modularizaton

+matching+modularizaton

+matching


ExamplesExamples


Read more…Read more…

NeOnhttp://www.neon-project.org/web

Next Generation Semantic Web ApplicationsE. Motta and M. Sabou. Next Generation Semantic Web Applications. AWC 2006. E. Motta and M. Sabou. Language Technologies and the Evolution of the Semantic Web. LREC 2006.E, Motta. Knowledge Publishing and Access on the Semantic Web: A Socio-Technological Analysis. IEEE

Intelligent Systems, Vol.21, 3, (88-90).

WastonM. d’Aquin, M. Sabou, M. Dzbor, C. Baldassarre, L. Gridinoc, S. Angeletou, and E. Motta. WATSON: A

Gateway for the Semantic Web. Accepted for the poster session of ESWC 2007.http://watson.kmi.open.ac.uk/http://watson.kmi.open.ac.uk/blog

Ontology ModularizationM. d’Aquin, M. Sabou, and E. Motta. Modularization: a Key for the Dynamic Selection of Relevant

Knowledge Components. ISWC 2006 workshop on Modular Ontologies (WoMO 2006).

Ontology MatchingM. Sabou, M. d’Aquin and E. Motta. Using the Semantic Web as Background Knowledge in Ontology

Mapping. ISWC 2006 workshop on Ontology Mapping (OM 2006).

Linking folksonomies to ontologiesL.Specia and E. Motta. Integrating Folksonomies with the Semantic Web. Accepted for ESWC 2007.


Thank you!

Lifecycle Support for Networked Ontologies And related research in KMi Mathieu dAquin and Marta...

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