Ontologies: methods, languages, and applications

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Ontologies methods, languages, and applications

• OLGA NABUCO
• CenPRA Brazil
• LAAS-CNRS - France

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Outline

• Definitions
• Methodologies some advices
• Languages representation and possibilities
• Tools editors, reasoners
• Application semantic web services

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Objectives

• Share knowledge permitting its reuse, encoding,
  and capturing.
• Share a common understanding allowing exchanges
  of labeled information for e-science, e-commerce,
  and other electronically-enabled interaction
• Analyzing domain knowledge problem-solving
  methods, domain-independent applications.
• Ontological analysis clarifies the structure of
  knowledge

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Knowledge representation

• Frame representation systems by thinking of think
  
• A frame is a data-structure for representing a
  stereotyped situation, like being in a certain
  kind of living room, or going to a child's
  birthday party. Attached to each frame are
  several kinds of information. Some of this
  information is about how to use the frame. Some
  is about what one can expect to happen next. Some
  is about what to do if these expectations are not
  confirmed.
• We can think of a frame as a network of nodes and
  relations. The "top levels" of a frame are fixed,
  and represent things that are always true about
  the supposed situation. The lower levels have
  many terminals"slots" that must be filled by
  specific instances or data. Each terminal can
  specify conditions its assignments must meet.
• Collections of related frames are linked together
  into frame-systems.
• (from Minskys frame concept)

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Definitions - The classics

• An explicit specification of a conceptualization
  (Gruber, 93)
• And conceptualization is an abstract, simplified
  view of the world that we wish to represent for
  some purpose.

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Ontology by frame description

• Frame is the class described by concepts
• Slots describing roles or properties
• Facets describing role restrictions
• Instances constitute the knowledge base

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Ontologies methodologies for construction
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Criteria by Gruber

• Clarity - Objective, formal, complete necessary
  and sufficient conditions
• Coherence axioms should be logically consistent
  as also the natural language documentation
• Extendibility the conceptual foundation
  antecipates tasks it should be extended and
  specialized
• Minimal encoding bias not encoding dependent
• Minimal ontological commitment allows
  specialization and instantiation.

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Ontology by Noy McGuiness

• Determine the domain and scope of the ontology
  (competency questions)
• Consider reusing existing ontologies
• Enumerate important terms in the ontology
• Define the classes and the class hierarchy
• Define the properties of classes slots
• Define the facets of the slots
• Create instances.

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The early vision knowledge sharing
(Neches at al., 91)
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Ontology of a problem-solver
B. Chandrasekaran, J. R. Josephson and V. Richard
Benjamins
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Ontology languages

• XML -
• RDF
• OWL

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XML eXtensible Markup Language

• You can formalise a tag set written in XML by
  creating a config file for it, known as a
  Document Type Definition, or more recently, a
  Schema.
• e.g.
• Summary Metadata Dublin Core and its
  derivatives.
• Rich Metadata Encoded Archival Description.
• XML can also format and transform itself with XML
  stylesheets XSL/XLSt.

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RDF

• Resources
• A resource is a thing you talk about (can
  reference)
• Resources have URIs
• RDF definitions are itself Resources (linkage)
• Properties
• slots, defines relationship to other resources or
  atomic values
• Statements
• Resource has Property with Value
• (Values can be resources or atomic XML data)
• Similar to Frame Systems

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• RDF just defines the datamodel
• Need for definition of vocabularies for the
  datamodel - an Ontology Language!
• RDF schemas are Web resources (and have URIs) and
  can be described using RDF

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• RDF just defines the datamodel
• Need for definition of vocabularies for the
  datamodel - an Ontology Language!
• RDF schemas are Web resources (and have URIs)
  and can be described using RDF

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RDF Schema
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OWL Web Ontology Language

• Shared ontologies
• interoperability requires agreements
• Ontology evolution
• Capacity to accommodate new terminology,
  revision, etc
• Ontology interoperability
• Different representations should be allowed
• Inconsistency detection
• Balance of expressivity and scalability
• Able of expressing a wide variety of knowledge as
  also providing means to reason
• Ease of use
• Low learning barrier
• Compatibility with other standards
• Internationalization
• Multilingual ontologies
• OWL stems from a family of logics, called
  description logics

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OWL Web Ontology Language

• XML provides a surface syntax for structured
  documents, but imposes no semantic constraints on
  the meaning of these documents.
• XML Schema is a language for restricting the
  structure of XML documents and also extends XML
  with datatypes.
• RDF is a datamodel for objects ("resources") and
  relations between them, provides a simple
  semantics for this datamodel, and these
  datamodels can be represented in an XML syntax.
• RDF Schema is a vocabulary for describing
  properties and classes of RDF resources, with a
  semantics for generalization-hierarchies of such
  properties and classes.
• OWL adds more vocabulary for describing
  properties and classes among others, relations
  between classes (e.g. disjointness), cardinality
  (e.g. "exactly one"), equality, richer typing of
  properties, characteristics of properties (e.g.
  symmetry), and enumerated classes.

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OWL Layers
Supports maximum expressiveness and sintatic
freedom
Supports maximum expressiveness computational
completeness, and decidability
Supports classification hierarchies and simple
constraints
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Tools

• Protégé http//protege.stanford.edu
• Swoop http//www.mindswap.org/2004/SWOOP
• Racer

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Semantic web and ontologies
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Semantic Web

• The Semantic Web is an extension of the current
  Web in which information is given well-defined
  meaning, better enabling computers and people to
  work in cooperation. Tim Bernes-Lee
• For the Web to become a truly machine-readable
  resource, the information it contains must be
  structured in a logical, comprehensible and
  transparent fashion.

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Semantic web layer
D
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Semantic web languages

• RDF, RDFS and OWL are ready for prime time
• Designs are stable, implementations maturing
• Major Research investment translating into
  application development and commercial spinoffs
• Adobe 6.0 embraces RDF
• IBM releases tools, data and partnering
• HP extending Jena to OWL
• OWL Engines by Ontoprise GmbH, Network Inference,
  Racer GmbH
• Proprietary OWL ontologies for vertical markets
• c.f. pharmacology, HMO/health care, ... Soft
  drinks

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Semantic web services
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OWL-S Semantic Markup for Web Services

• Automatic Web service discovery enables
  declarative advertisements of service properties
  and capabilities
• Automatic Web service invocation in conjunction
  with domain ontologies specified in OWL, provides
  standard means of specifying declaratively APIs
  for Web services that enable this kind of
  automated Web service execution.
• Automatic Web service composition and
  interoperation provides declarative
  specifications of the prerequisites and
  consequences of application of individual
  services, and a language for describing service
  compositions and data flow interactions.

http//www.ai.sri.com/daml/services/owl-s/1.2/over
view/
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OWL-S Semantic Markup for Web Services
Composition
What does the service provide for prospective
clients? The answer to this question is given in
the "profile," which is used to advertise the
service. To capture this perspective, each
instance of the class Service presents a
ServiceProfile. How is it used? The answer to
this question is given in the "process model."
This perspective is captured by the ServiceModel
class. Instances of the class Service use the
property describedBy to refer to the service's
ServiceModel. How does one interact with it?
The answer to this question is given in the
"grounding." A grounding provides the needed
details about transport protocols. Instances of
the class Service have a supports property
referring to a ServiceGrounding.
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OWL-S Semantic Markup for Web Services Profile
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OWL-S Semantic Markup for Web Services Process
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OWL-S Semantic Markup for Web Services Grounding
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QoS as Semantic Description

• Objective include QoS information in any phase
  of the web service life cycle as a semantic one.
• Refining the search process using QoS criteria
• Atomating QoS negotiation
• Measurement of QoS
• QoS aware dynamic deployment
• Use ontologiesRules as semantic annotation or
  markup language to distingueshed information

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Annottations and Markup

• At least two possibilities are candidate
• OWL-S semantic markup for web services
• SAWRL semantic annotations for WSDL

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Semantic Annotations for WSDL
Semantic Annotations for WSDL (SAWSDL) defines
how to add semantic annotations to various parts
of a WSDL document such as input and output
message structures, interfaces and operations.
For example, it defines a way to annotate WSDL
interfaces and operations with categorization
information that can be used to publish a Web
service in a registry. The annotations on schema
types can be used during Web service discovery
and composition.
http//www.w3.org/2002/ws/sawsdl/spec/
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Semmantic Annotations for WSDL

• an extension attribute, named modelReference, to
  specify the association between a WSDL components
  and a concept in some semantic model. It is used
  to to annotate XSD complex type definitions,
  simple type definitions, element declarations,
  and attribute declarations as well as WSDL
  interfaces, operations, and faults.
• two extension attributes, named
  liftingSchemaMapping and loweringSchemaMapping,
  that are added to XML Schema element
  declarations, complex type definitions and simple
  type definitions for specifying mappings between
  semantic data and XML. The mappings can be used
  during service invocation.

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QoS Upper by Maximilien and Singh
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QoS Middle by Maximilien and Singh
E. Michael Maximilien and Munindar P. Singh. A
framework and ontology for dynamic web services
selection. In IEEE Internet Computing, 84-93,
September-October 2004.
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RosettaNets ontology Message excerpt
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Some examples of ontologies

• General purpose ontologies
• DOLCE, http//www.loa-cnr.it/DOLCE.html
• The Upper Cyc Ontology, http//www.cyc.com/cyc-2-1
  /index.html
• IEEE Standard Upper Ontology, http//suo.ieee.org/
  
• Domain and application-specific ontologies
• GALEN, http//www.openclinical.org/prj_galen.html
• Foundational Model of Anatomy, http//sig.biostr.w
  ashington.edu/projects/fm/AboutFM.html
• RETSINA Calendering Agent, http//ilrt.org/discove
  ry/2001/06/schemas/ical-full/hybrid.rdf
• Dublin Core, http//dublincore.org/
• Semantic Desktop Ontologies
• Semantics-Aware instant Messaging SAM Ontology,
• http//www.uni-koblenz.de/FB4/Institutes/IFI/AGSta
  ab/Research/sam
• Haystack, http//haystack.lcs.mit.edu/
• Gnowsis, http//www.gnowsis.org/
• Piggybank, http//simile.mit.edu/piggy-bank/
• Web Services Ontologies
• Core ontology of services http//cos.ontoware.org
• Web Service Modeling ontology http//www.wsmo.org
• OWL-S, http//www.daml.org/services/owl-s/1.0/

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Web Service Diagnosability, Monitoring and
Diagnosis IST-516933

• Operational framework for self-healing service
  execution of conversationally complex Web
  Services
• Monitoring service execution
• Fault detection
• Diagnosis
• Recovery/repair
• A methodology and tools for service design that
  guarantee effective and efficient diagnosability
  / repairability during execution

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Partners
Dept. AI Vrije Univ. Amsterdam (NL)
Dept. Informatica Univ Torino (I)
IRISA Univ Rennes (F)
Dept. CS and manufacturing Univ Klagenfurt (A)
LRI Univ. Paris Sud (F)
Workflow Research group Univ Vienna (A)
LAAS - CNRS Univ. Toulouse (F)
Dept. Electronics and Information Polit. Milan
(I)
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Rule Language Extensions (to OWL)

• First Order extension (e.g., SWRL) Horrocks et
  al, JWS, 2005
• Horn clauses where predicates are OWL classes and
  properties
• Resulting language is undecidable
• Reasoning support currently only via FOL theorem
  provers (Hoolet)
• Hybrid language extensions being investigated
• Restricting language interaction maintains
  decidability
• DL extended with Answer Set Programming Eiter et
  al, KR-04
• DL extended with Datalog rules Motik et al,
  ISWC-04 Rosati, JWS, 2005
• LP/F-logic rule language
• Claimed interoperability with OWL via DLP
  subset de Bruijn et al, WWW-05

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References

• Gruber, 93 - http//ksl.stanford.edu/KSL_Abstracts
  /KSL-93-04.html
• Minsky, 74 -http//web.media.mit.edu/minsky/pape
  rs/Frames/frames.html
• http//www.museumscomputergroup.org.uk/meetings/1_
  2005_docs/A-Beginner's-guide-to-the-Semantic-Web.p
  pt
• Neches et al, 1991 http//www.isi.edu/isd/KRSharin
  g/vision/AIMag.html
• http//www.cse.ohio-state.edu/chandra/Ontology-of
  -Tasks-Methods.PDF