Ontologies

Mariana Damova, PhD

      April, 2010
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
Ontologies
                 What Is An Ontology

• An ontology is an explicit description of a
  domain:
 –   concepts
 –   properties and attributes of concepts
 –   constraints on properties and attributes
 –   Individuals (often, but not always)

• An ontology defines
 – a common vocabulary
 – a shared understanding
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
Philosophy
•   What   exists?
•   What   is?
•   What   am I?
•   What   is describing this to me?
Philosophy
Greek etymology
Parmenides of Elea, ancient Greek
  philosopher (early 5th century BCE)

For never shall this prevail,
that things that are not are

  Parmenides made the ontological argument
  against nothingness, essentially denying
  the possible existence of a void.
Philosophy
• Jacob Lorhard, German
  philosopher (1561 - 1609)
• 1607 - First occurrence of the word
  Ontology (lat. Ontologia) and the
  first published ontology
Lorhard‘s Ontology
•   Translation from: Peter Øhrstøm, Sara L. Uckelman; Henrik
    Schärfe –
•   Historical and conceptual foundations of diagrammatical ontology
Ontologies and CS
• Tom Gruber, 1992
• An ontology is a specification of a
  conceptualization.

•   An ontology defines
•    Concepts
•    Relationships
•   Any other distinctions that are relevant
    for modeling a domain
Ontologies and CS
• To share common understanding of the
  structure of information among people
  or software agents
• To enable reuse of domain knowledge
• To make domain assumptions explicit
• To separate domain knowledge from
  the operational knowledge
• To analyze domain knowledge
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
Knowledge Models
Structured representations of knowledge using symbols to
represent pieces of knowledge and relationships between
them.

Different types of KM have different degrees of formality and
levels of expressivity.

A KM can include:
Symbolic character-based languages, such as logic
Diagrammatic representations, such as networks and ladders
Tabular representations, such as matrices
Structured text, such as hypertext
Knowledge Models - Design

• Knowledge identification
   - What?
• Knowledge specification
   - How?
• Knowledge refinement
   - Validation
Knowledge Models - Types

• Ladders: hierarchical (tree-like)
  diagrams
• Tables and Grids: tabular
  representations
• Network Diagrams: shows nodes
  connected by arrows
    The most complex type of KM
    Examples include semantic nets
  and conceptual graphs
Ladder Model Example – British Royal Family
Tabular Model Example – Stock Markets
Network Diagrams – Semantic Nets



• Nodes in the graph represent concepts
• Arcs represent binary relationships between concepts
• Any characteristic that links two concepts: isA, hasColour, hasAge,
LivesIn, etc.




  Note the difference between this structure and the ladders.
Network Diagrams – Conceptual Graphs

•   Combination between the existential graphs and Semantic nets
•   A conceptual graph consists of:
•   Concept nodes – represented as rectangular boxes
•   Relations nodes – represented as ovals
•   One way connections between the nodes – represented as arrows
•   Less intuitive then the Semantic Nets




                       Nemo the fish lives in water
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
Knowledge Organization



• Thesaurus
• Taxonomies
• Ontologies
Thesaurus

• Similar with dictionaries
• Provides synonyms and antonyms
  for words, and not definitions
   E.g., WordNet
Taxonomies


• Hierarchical structures
• Subtype-supertype relationships, also
  called parent-child relationships
• Example: Whale is Mammal; Mammal is
  an Animal (not all Animals are Mammal,
  not all mammals are Whales)
Taxonomy Examples

• Taxonomies on the Web
– Yahoo! Categories

• Catalogs for on-line shopping
– Amazon.com product catalog

• Domain-specific standard terminology
– Unified Medical Language System (UMLS)
– UNSPSC - terminology for products and
services
Yahoo
Amazon
Ontology

• More complex
A formal definition of ontologies is provided in [Brewster and
Wilks, 2009]

          O = (C,T,R,A,I,V,≤c, ≤t, σR, σA, IC, IT, IR, IA)

• Whereby:

C – Concepts V – Values
T – Types      ≤ – Partial Order on C and T
R – Relations σ – Functions
A – Attributes        I – Partial Instantiation Functions
I – Instances
Knowledge Organization




Differences in the degree of logical rigor, formality and the
potential for reasoning over the data structure
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
How Ontologies can be used


                               Declare
                                            Databases
                              structure
           Ontologies
                                            Knowledge
                                              bases
     Provide
      domain
    description


                               Domain-
Software                     independent
                  Problem-
 agents                      applications
                   solving
                  methods
Types of Ontologies

• Upper Ontology – model of the common
  objects that are applicable across a wide
  range of domain ontologies

• Domain Ontology – an ontology developed
  for a specific domain; conforms to an upper
  ontology

• Application Ontology – an ontology created
  for a specific application; may conform to a
  domain ontology
Types of Ontologies - Examples

Upper Ontologies:
• Dublin Core
• OpenCyc/ResearchCyc
• SUMO
• DOLCE
• PROTON


•   Domain Ontologies:
•   E-business : Rosetta-Net
•   Medical: UMLS
•   Engineering: EngMath
Methods for Building Ontologies
• From scratch – conceptual analysis
• Ontology acquisition
• Building on existing ontologies
Conceptual Schema
Sample Class Hierarchy
Sample Property Hierarchy
Modeling of an organization
DBPedia




http://mappings.dbpedia.org/server/ontology/classes
DBPedia
Proton Ontology
Person in DBPedia
Person in Proton
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
Protege
Protege
Class and Properties
Instances
TopBraid Composer - Diagram
TopBraid Composer - Graph
TopBraid Composer - Layout
Outline
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web
OWL: Summary
The Web Ontology Language (OWL) was developed to provide
  for more expressive ontologies based on a decidable formal
  logic.

Three flavours of OWL have been specified: OWL Full for full
expressiveness without guarantees of decidability, OWL DL
  for a compromise expressiveness within the decidable
  fragment of Description Logic and OWL Lite as a subset of
  DL.

OWL provides for additional constructs not present in RDFS to
  define classes and properties. As a result, OWL is well
  suited to consistency checking and classification tasks.
OWL Lite
The complete language OWL Full has two sublanguages:
       • OWL DL (Description Language)
            • supports reasoning applications
            • has restrictions on OWL Full constructs
            • restrictions make reasoning systems decidable
       • OWL Lite
            • supports only a subset of OWL Full constructs
            • provides a minimal set of features allowing the
              development of ontologies without the encoding
              of complex semantic relationships
OWL Lite - Classes
OWL classes define basic concepts.


A Simple Named Class is defined as follows:
–    <owl:Class rdf:ID=„classname“/>
     Ex. <owl:Class rdf:ID=„Restaurant“/>


Predefined OWL Classes (Extreme classes)
–    Thing class (owl:Thing)
            the most general class
            every individual is member of this class
–    Nothing class (owl:Nothing)
            empty class with no member individuals
OWL Lite - Properties
There are four disjoint type of properties in OWL.
        • Datatype properties (owl:DatatypeProperty)
        • Object properties (owl:ObjectProperty)
        • Annotationproperties (owl:AnnotationProperty)
        • Ontology properties (owl:OntologyProperty)
OWL Lite – Classes and Properties
Linking Open Data
LDSR – reason-able view to LOD


http://ldsr.ontotext.com
http://linkedlifedata.com
Summary
•   Definition of ontologies
•   History of the science of categorization
•   Knowledge models
•   Knowledge organization
•   Use and Building of ontologies
•   Ontology tools
•   Ontologies on the Web

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Ontologies Fmi 042010

  • 2. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 3. Ontologies What Is An Ontology • An ontology is an explicit description of a domain: – concepts – properties and attributes of concepts – constraints on properties and attributes – Individuals (often, but not always) • An ontology defines – a common vocabulary – a shared understanding
  • 4. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 5. Philosophy • What exists? • What is? • What am I? • What is describing this to me?
  • 6. Philosophy Greek etymology Parmenides of Elea, ancient Greek philosopher (early 5th century BCE) For never shall this prevail, that things that are not are Parmenides made the ontological argument against nothingness, essentially denying the possible existence of a void.
  • 7. Philosophy • Jacob Lorhard, German philosopher (1561 - 1609) • 1607 - First occurrence of the word Ontology (lat. Ontologia) and the first published ontology
  • 8. Lorhard‘s Ontology • Translation from: Peter Øhrstøm, Sara L. Uckelman; Henrik Schärfe – • Historical and conceptual foundations of diagrammatical ontology
  • 9. Ontologies and CS • Tom Gruber, 1992 • An ontology is a specification of a conceptualization. • An ontology defines • Concepts • Relationships • Any other distinctions that are relevant for modeling a domain
  • 10. Ontologies and CS • To share common understanding of the structure of information among people or software agents • To enable reuse of domain knowledge • To make domain assumptions explicit • To separate domain knowledge from the operational knowledge • To analyze domain knowledge
  • 11. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 12. Knowledge Models Structured representations of knowledge using symbols to represent pieces of knowledge and relationships between them. Different types of KM have different degrees of formality and levels of expressivity. A KM can include: Symbolic character-based languages, such as logic Diagrammatic representations, such as networks and ladders Tabular representations, such as matrices Structured text, such as hypertext
  • 13. Knowledge Models - Design • Knowledge identification - What? • Knowledge specification - How? • Knowledge refinement - Validation
  • 14. Knowledge Models - Types • Ladders: hierarchical (tree-like) diagrams • Tables and Grids: tabular representations • Network Diagrams: shows nodes connected by arrows The most complex type of KM Examples include semantic nets and conceptual graphs
  • 15. Ladder Model Example – British Royal Family
  • 16. Tabular Model Example – Stock Markets
  • 17. Network Diagrams – Semantic Nets • Nodes in the graph represent concepts • Arcs represent binary relationships between concepts • Any characteristic that links two concepts: isA, hasColour, hasAge, LivesIn, etc. Note the difference between this structure and the ladders.
  • 18. Network Diagrams – Conceptual Graphs • Combination between the existential graphs and Semantic nets • A conceptual graph consists of: • Concept nodes – represented as rectangular boxes • Relations nodes – represented as ovals • One way connections between the nodes – represented as arrows • Less intuitive then the Semantic Nets Nemo the fish lives in water
  • 19. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 20. Knowledge Organization • Thesaurus • Taxonomies • Ontologies
  • 21. Thesaurus • Similar with dictionaries • Provides synonyms and antonyms for words, and not definitions E.g., WordNet
  • 22. Taxonomies • Hierarchical structures • Subtype-supertype relationships, also called parent-child relationships • Example: Whale is Mammal; Mammal is an Animal (not all Animals are Mammal, not all mammals are Whales)
  • 23. Taxonomy Examples • Taxonomies on the Web – Yahoo! Categories • Catalogs for on-line shopping – Amazon.com product catalog • Domain-specific standard terminology – Unified Medical Language System (UMLS) – UNSPSC - terminology for products and services
  • 24. Yahoo
  • 26. Ontology • More complex A formal definition of ontologies is provided in [Brewster and Wilks, 2009] O = (C,T,R,A,I,V,≤c, ≤t, σR, σA, IC, IT, IR, IA) • Whereby: C – Concepts V – Values T – Types ≤ – Partial Order on C and T R – Relations σ – Functions A – Attributes I – Partial Instantiation Functions I – Instances
  • 27. Knowledge Organization Differences in the degree of logical rigor, formality and the potential for reasoning over the data structure
  • 28. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 29. How Ontologies can be used Declare Databases structure Ontologies Knowledge bases Provide domain description Domain- Software independent Problem- agents applications solving methods
  • 30. Types of Ontologies • Upper Ontology – model of the common objects that are applicable across a wide range of domain ontologies • Domain Ontology – an ontology developed for a specific domain; conforms to an upper ontology • Application Ontology – an ontology created for a specific application; may conform to a domain ontology
  • 31. Types of Ontologies - Examples Upper Ontologies: • Dublin Core • OpenCyc/ResearchCyc • SUMO • DOLCE • PROTON • Domain Ontologies: • E-business : Rosetta-Net • Medical: UMLS • Engineering: EngMath
  • 32. Methods for Building Ontologies • From scratch – conceptual analysis • Ontology acquisition • Building on existing ontologies
  • 36. Modeling of an organization
  • 42. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 50. Outline • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web
  • 51. OWL: Summary The Web Ontology Language (OWL) was developed to provide for more expressive ontologies based on a decidable formal logic. Three flavours of OWL have been specified: OWL Full for full expressiveness without guarantees of decidability, OWL DL for a compromise expressiveness within the decidable fragment of Description Logic and OWL Lite as a subset of DL. OWL provides for additional constructs not present in RDFS to define classes and properties. As a result, OWL is well suited to consistency checking and classification tasks.
  • 52. OWL Lite The complete language OWL Full has two sublanguages: • OWL DL (Description Language) • supports reasoning applications • has restrictions on OWL Full constructs • restrictions make reasoning systems decidable • OWL Lite • supports only a subset of OWL Full constructs • provides a minimal set of features allowing the development of ontologies without the encoding of complex semantic relationships
  • 53. OWL Lite - Classes OWL classes define basic concepts. A Simple Named Class is defined as follows: – <owl:Class rdf:ID=„classname“/> Ex. <owl:Class rdf:ID=„Restaurant“/> Predefined OWL Classes (Extreme classes) – Thing class (owl:Thing) the most general class every individual is member of this class – Nothing class (owl:Nothing) empty class with no member individuals
  • 54. OWL Lite - Properties There are four disjoint type of properties in OWL. • Datatype properties (owl:DatatypeProperty) • Object properties (owl:ObjectProperty) • Annotationproperties (owl:AnnotationProperty) • Ontology properties (owl:OntologyProperty)
  • 55. OWL Lite – Classes and Properties
  • 57. LDSR – reason-able view to LOD http://ldsr.ontotext.com http://linkedlifedata.com
  • 58. Summary • Definition of ontologies • History of the science of categorization • Knowledge models • Knowledge organization • Use and Building of ontologies • Ontology tools • Ontologies on the Web