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![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](https://image.slidesharecdn.com/ontologiesfmi042010-12816871992725-phpapp02/75/Ontologies-Fmi-042010-26-2048.jpg)
Uploaded byMariana Damova, Ph.D
Ontologies Fmi 042010
The document defines ontologies as explicit descriptions of a domain that define concepts, properties, attributes, and constraints. It discusses the history of categorization in philosophy and the development of knowledge models like semantic nets and conceptual graphs. The document outlines different methods for building ontologies and different types of ontologies. It also discusses ontology tools like Protege and TopBraid Composer and how ontologies are used on the semantic web through languages like OWL.
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Ontologies Fmi 042010
- 1. Ontologies Mariana Damova, PhD April, 2010
- 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 ofElea, 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 representationsof 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 withdictionaries • 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 • Taxonomieson 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
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- 26. Ontology • More complex Aformal 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 inthe 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 canbe 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 BuildingOntologies • From scratch – conceptual analysis • Ontology acquisition • Building on existing ontologies
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- 36. Modeling of anorganization
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- 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
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- 47. TopBraid Composer -Diagram
- 48. TopBraid Composer -Graph
- 49. TopBraid Composer -Layout
- 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 WebOntology 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 completelanguage 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
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- 57. LDSR – reason-ableview 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