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
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
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
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
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
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
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)
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
