Ontology Engineering SSSC2009
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Transcript of Ontology Engineering SSSC2009
Elena Simperl @SSSC2009, Berkeley, CA.
F d l f l iFundamentals of ontologiesDefinitions, features, classifications, applications, modelling principlesmodelling principles
Ontology engineeringMethodologies methods and tools to build Methodologies, methods and tools to build, manage and use ontologies
*Thanks to Tobias Bürger, Asuncion Gomez Perez and MartinHepp for providing valuable contents to this lecture
A t l d fi th b i t d l ti An ontology defines the basic terms and relations comprising the vocabulary of a topic area, as well as the rules for combining terms and relations to define
t i t th b lextensions to the vocabularyNeches, R.; Fikes, R.; Finin, T.; Gruber, T.; Patil, R.; Senator, T.; Swartout, W.R. Enabling
Technology for Knowledge Sharing. AI Magazine. Winter 1991. 36‐56
An ontology is an explicit specification of a conceptualizationGruber, T. A translation Approach to portable ontology specifications. Knowledge Acquisition.
Vol 5 1993 199‐220Vol. 5. 1993. 199‐220
A t l i hi hi ll t t d t f t f An ontology is a hierarchically structured set of terms for describing a domain that can be used as a skeletal foundation for a knowledge base
B Swartout R Patil k Knight T Russ Toward DistributedUse of Large ScaleOntologiesB. Swartout; R. Patil; k. Knight; T. Russ. Toward DistributedUse of Large‐ScaleOntologiesOntological Engineering. AAAI‐97 Spring SymposiumSeries. 1997. 138‐148
An ontology provides the means for describing explicitly the conceptualization behind the knowledge represented in a conceptualization behind the knowledge represented in a knowledge baseA. Bernaras;I. Laresgoiti; J. Correra. Building and ReusingOntologies for Electrical Network Applications ECAI96. 12th European conference onArtificial Intelligence. Ed. John Wiley
& S Ltd 8& Sons, Ltd. 298‐302
“An ontology is a formal, explicit specification of a shared conceptualization”
Consensual
Machine-readable
Consensual Knowledge
Abstract model and simplified view of some
Concepts, propertiesrelations, functions,
Studer, Benjamins, Fensel. Knowledge Engineering: Principles and Methods. Data and Knowledge Engineering. 25 (1998) 161-197
simplified view of some phenomenon in the world that we want to represent
constraints, axioms, are explicitly defined
Studer, Benjamins, Fensel. Knowledge Engineering: Principles and Methods. Data and Knowledge Engineering. 25 (1998) 161 197
SUMOSUMO
Modelled knowledge about a specific domainModelled knowledge about a specific domain
DefinesA common vocabularyA common vocabularyThe meaning of termsHow terms are interrelated
Consists of Conceptualization and implementationConceptualization and implementation
ContainsOntological primitivesOntological primitives
C i d i iConcepts are organized in taxonomiesRelations • R: C1 x C2 x ... x Cn-1 x Cn
Functions• F: C1 x C2 x ... x Cn-1 --> Cn
Instances• Elements
Axioms• Sentences which are always true
Issue of the conceptualizationIssue of the conceptualizationUpper‐level/Top‐levelCoreDomainDomainTaskApplicationRepresentationp
Degree of formalityHighly informal: in natural languageS i i f l i i d d d f f l Semi‐informal: in a restricted and structured form of natural languageSemi‐formal: in an artificial and formally defined languageRigorously formal: in a language with formal semantics theorems Rigorously formal: in a language with formal semantics, theorems and proofs of such properties as soundness and completeness
Thessauri General
Catalog/ID
Thessauri “narrower term”
relationFormal
is-aFrames
(properties)
General Logical
constraints
T / I f l Formal V l DisjointnessTerms/ glossary
Informal is-a
Formal instance
Value Restrs.
Disjointness, Inverse, part-Of
...
Lassila O, McGuiness D. The Role of Frame-Based Representation on the Semantic Web. Technical Report. Knowledge Systems Laboratory. Stanford University. KSL-01-02. 2001.
Application Domain Application Domain RE Ontology Task Ontology
Domain Ontology Domain Task Ontology
EUSA Core Ontology Task Ontology
Top-Level Ontology
BILI
Core Ontology Task Ontology
Representation Ontology
General/Common OntologyITY
O t l i b b ilt i i l ith i Ontologies can be built using various languages with various degrees of formality
Natural languageUMLUMLEROWL/RDFSWSMLWSMLFOL...
Th f li d th l li it th ki d f k l d th t The formalism and the language limit the kind of knowledge that can be representedA domain model is not necessarily a formal ontology only because it is written in OWLit is written in OWL
(defconcept Travel"A journey from place to place"
:is-primitive(:and
(defrelation Pays:is (:function (?room ?Discount)( (Price ?room) (/(*(Price ?room) ?Discount) 100)))(:and
(:all arrivalDate Date)(:exactly 1 arrivalDate)(:all departureDate Date)(:exactly 1
departureDate)(:all companyName String)
(- (Price ?room) (/( (Price ?room) ?Discount) 100))):domains (Room Number):range Number)
(:all singleFare Number)(:at-most singleFare 1))) (defrelation connects"A road connects two different cities"
:arity 3:domains (Location Location)
R dS ti(tellm (AA7462 AA7462-08-Feb-2002) :range RoadSection:predicate ((?city1 ?city2 ?road) (:not (part-of ?city1 ?city2))(:not (part-of ?city2 ?city1))
(tellm (AA7462 AA7462-08-Feb-2002)(singleFare AA7462-08-Feb-2002 300)(departureDate AA7462-08-Feb-2002 Feb8-2002)(arrivalPlace AA7462-08-Feb-2002 Seattle))
( (p y y ))(:or (:and (start ?road ?city1)(end ?road ?city2))
(:and (start ?road ?city2)(end ?road ?city1)))))
K l d iKnowledge representationOntology models domain knowledge
Semantic annotationSemantic annotationOntology is used as a vocabulary, classification or indexing schema for a collection of itemsindexing schema for a collection of items
Semantic searchOntology is used as a query vocabulary or for gy q y yquery rewriting purposes
ConfigurationOntology defines correct configuration templates
Ontology‐based SearchNeutral Authoring
Ontologies provide the structure for the navigation of the results, support browsing and classification.
Bases for application development as core data model for all applications.
Typical use case in AI
O t l i
Ontologies allow for term disambiguation and query rewriting.
Typical use case in AI.
OntologiesSpecification of software systems and automation of code generation.
Global view on information.
Organization and management of information
MDA.
SOA.
sources and their interrelation.
Consistency checking.
Ontology‐based SpecificationCommon Access to Information
Source: Jasper & Uschold, 1999.
fQuery formulation.Query rewriting.
dAugmented query processing.
h kSemantic matchmaking.Navigation and browsing.
lVizualization.
WatsonWatsonhttp://watson.kmi.open.ac.uk/Overview.html
Swooglehttp://swoogle.umbc.edu/
Protégé Ontologiesg ghttp://protegewiki.stanford.edu/index.php/Protege_Ontology_Library#OWL_ontologies
OBO Foundation Ontologieshttp://www.obofoundry.org/
Open Ontology Repositoryhttp://ontolog.cim3.net/cgi‐bin/wiki.pl?OpenOntologyRepository
Manchester Ontology Libraryhttp://owl.cs.manchester.ac.uk/repository/
Ontology Yellow Pageshttp://wg sti2 org/semtech onto/index php/The Ontology Yellow Pageshttp://wg.sti2.org/semtech‐onto/index.php/The_Ontology_Yellow_Pages
AIM@SHAPEhttp://dsw.aimatshape.net/tutorials/ont‐intro.jsp
VoCampsphttp://vocamp.org/wiki/Main_Page
Project management: t lli l i lit t
Domain analysismotivating scenarios, competency questions, existing solutions
Kno
Project management: controlling, planing, quality assurance etc.
Conceptualizationconceptualization of the model, integration and extension of existing solutions
owledge a
Evaluat
Docum
en
Implementationimplementation of the formal model in a representation language
cquisition
tion
ntation
Usage/Maintenanceadaptation of the ontology according to new requirements
Management SupportDevelopment oriented
Pre-development
SchedulingKnowledge acquisition
Environment study Feasibility studyg
Evaluation IntegrationDevelopment
Environment study Feasibility study
Control Documentation
Specification Conceptualization
Merging
Quality
Formalization Implementation
Post-development
Qualityassurance
Configurationmanagement
Maintenance Use Alignment
Historical Background
Enterprise Ontology[U h ld & Ki ]
CommonKADS[Schreiber et al., 1999]
[Uschold & King, 1995]DILIGENT
[Tempich 2006]IDEF5[Benjamin et al. 1994]
H l l &J hi
[Tempich, 2006]
OTK Holsapple&Joshi[Holsapple & Joshi, 2002]
METHONTOLOGY
OTK[Sure, 2003]
CO4[Euzenat, 1995]
METHONTOLOGY[Gomez‐Perez, 1996]
T l i d hTwo or more people interact and exchangeknowledge in order to build a common, shared ontology in pursuit of a shared shared ontology in pursuit of a shared, collective, bounded goal.Interaction may be indirect but required Interaction may be indirect but required. Argumentation as a common interaction means.Simple contributions not enough Simple contributions not enough. Bounded goal: beginning and end.Collaborators may have individual goals.Collaborators may have individual goals.
1 Emergence of ideas In the first phase new concept ideas are collected in an 1. Emergence of ideas. In the first phase, new concept ideas are collected in an ad‐hoc fashion. This is done using simple tags.
2. Consolidation in communities. The concept symbols generated in the first phase are re‐used and adapted by the user community. The phase aims at p p y y pextracting concepts from the available tags leading to a common terminology.
3. Formalization. This phase adds taxonomic and ad‐hoc relations to the common terminology yielding lightweight but formal ontologies.
4. Axiomatization. The final step in the methodology addresses knowledge workers, i.e. ontology engineers, to add axiom leading to a heavy‐weight ontology.
[Braun, 2007]
T i i f l h Tagging is a very successful approach to organize all sorts of content on the Web.
Approaches to derive formal ontologies from tag clouds are emerging.
There are several tools available for building ontologies using semantic wikis.g g
Serious games to engineer ontologies and annotate contentannotate content.
http://vocamp.org/wiki/Main_Page