Wissenstechnologie Iv 08 09

Wissenstechnologie WS 08/09

Michael Granitzer
IWM TU Graz & Know-Center
Know Center

Lecture 4: OWL Inference
Lect e 4 OWL, Infe ence and
Upper Ontologies
http://kmi.tugraz.at
http://kmi tugraz at http://www.know-center.at
http://www know center at
This work is licensed under the Creative Commons Attribution 2.0 Austria License.
To view a copy of this license, visit http://creativecommons.org/licenses/by/2.0/at/.

Today

RDF Schema (RDFS)

Web Ontology Language (OWL)

OWL & Logics

Example Ontologies
2

WS 08/09 Wissenstechnologie @ kmi.tugraz.at

Semantic Web Stack

a.k.a. SW Layer Cake
y
a.k.a. SW Tower

3


Semantic Web Stack

RDF

4


RDF Statements (Triples)
A small example

http://en.wikipedia.org/wiki/John_Lennon
htt // iki di / iki/J h L http://dbpedia.org/property/associatedActs
http://dbpedia org/property/associatedActs

http://en.wikipedia.org/wiki/The_Beatles

http://en.wikipedia.org/wiki/Paul_McCartney
http://dbpedia.org/property/associatedActs
rdfs:label

„Paul McCartney“

Subject
j Predicate Object
j
http://en.wikipedia.org/wiki/J http://dbpedia.org/property/a http://en.wikipedia.org/wiki/T
ohn_Lennon ssociatedActs he_Beatles

http://en.wikipedia.org/wiki/P http://dbpedia.org/property/a http://en.wikipedia.org/wiki/T
aul_McCartney ssociatedActs he_Beatles

http://en.wikipedia.org/wiki/P Rdfs:label “Paul McCartney”
5
aul_McCartney


Ontologies
What are Concepts in our purpose?

Semiotic Triangle [Ogden & Richards 1923]

Concept

Refers to
Symbolizes

Term / Word
Thing
/URI
Stands for
St d f
‚Apache‘ 6


Ontologies & Semantics
Example: Mammal

Intension
•isA(Vertebrate Animal)
•has(Sweat glands)
•withFunction(Milk)
•withFunction(hair)
•....

Extension
•Elephant
•Lion
•Monkey
Monkey
•....
7


Summary of Definitions

A Ontology is a model (of the world)
t l
A ontology d ib
describes a particular (k
ti l (knowledge) d
l d ) domain
i
A ontologie defines words/terms/signs for describing
Concepts
A ontologie puts concepts into relation to each other
A ontologie uses axioms to put constraints on particular
concepts

8


Components of an Ontology

Classes general things of a domain
Instances special things of a domain
R l ti
Relations between thi
b t things
Properties of things

9


Semantics & Communication

Language must allow to express the semantics in an
implementation/algorithmic independent way
Usually done via a Vocabulary
Topic oriented vocabulary (e.g. Friend of a friend)
Schema Knowledge/Terminological Knowledge
g g g

– Special vocabulary to make statements over topic oriented
vocabulary (i.e. the termonologie used in a domain)
– A general set of rules independent of the domain
– Defines the expressiveness of a language

10


Semantic Web Stack

RDF Schema

11


RDF Schema (RDFS)
http://www.w3.org/2000/01/rdf-schema#
http://www w3 org/2000/01/rdf-schema#

Allows to express terminological knowledge over RDF
Application of RDFS
Defines a new vocabulary for giving meaning
independent of program logic
Allows to define „lightweight“ Ontologies and basic
g g g
Reasoning capabilities

http://www.w3.org/TR/rdf-schema/

12


RDF Schema
Classes

rdfs:Resource Class of all resources
rdfs:Literal Class of literals (Strings)
rdfs:Class Class of classes
rdf:Property Class of properties
rdf:Statement Class of RDF Statements
…

13


RDF Schema
Properties

rdf:type Subject is an instance of a class
rdfs:subClassOf Subject is a subclass of a class
rdfs:subPropertyOf Subject is a sub property of a property
rdfs:domain A possible class for a subject of a property
rdfs:range A possible class for an object of a property
rdfs:label human readable label of an resource
rdfs:comment human readable comment of an resource
…

14


RDFS Semantics

Model based semantics:
each triple is a sentence
A sentence is tr true, if the triple exists
Entailment: Given a graph the graph is transformed according to the
rules of RDFS
Implicit knowledge (i e not explicitly modelled)
(i.e.

#Means of #Means of
Transportation Transportation

rdfs:subClassOf rdf:type rdfs:subClassOf
#MyBMW
#Car #MyBMW #Car
rdf:type

rdfs:subClassOf rdf:type 15
rdfs:subClassOf

#BMW #BMW


RDFS Semantics
Drawback/Restriction of RDF

Open world assumption: false statements must be
specified
Closed world assumption: if a statement is missing, it is
p g,
assumed to be false
No negation in RDFS possible
• ex:michael rdf:type ex:nonsmoker
• ex:michael rdf:type ex:smoker
Does not lead to a contradiction!
No l
N rules over individuals e.g. ex:Humans = All
i di id l H
ex:Women and All ex:Men
16
No Counting: “An Elephant has 4 legs”
An legs


Semantic Web Stack
Web Ontology Language (OWL)

OWL

17


Historical Development

Standardised since 2004

18


DARPA Agent Markup Language
(DAML)

DARPA,
Funded by DARPA start 2001
DARPA: Defense Advanced Research
Projects Agency
j g y
Markup Language for semantic nets
DAML-ONT:
DAML ONT: RDFS extension for Ontologies
Focus is on the Web

19


Ontology Inference Layer (OIL)

European Project with focus on inference
capabilities
Different kinds of standard
Excluding Reification Core OIL is compatible to
RDFS

20


History DAML+OIL

1999
DARPA Agent Markup Language (DAML) in USA
Ontology Inference Layer (OIL) in EU
2000
Combining both DAML+OIL
2001
DAML+OIL handed in to W3C for standardisastion
Base for Web Ontology Language (OWL)

21


Development of OWL

W3C founded 2001 The Ontology (WebONT) Working
Group
Using DAML+OIL for language specification
g g g p
Feb. 2004 the W3C has published the OWL Web Ontology
Language Recommendations
Simply speaking: They added an additional vocabulary to
RDF(S)
http://w3.org/2001/sw/WebOnt
htt // 3 /2001/ /W bO t

22


OWL - WOL

Web Language
The language started out as the quot;Web Ontology Languagequot;
but the Working Group disliked the acronym quot;WOL.quot; We
decided to call it OWL. The Working Group became more
comfortable with this decision when one of the members
pointed out the following justification for this decision from
the noted ontologist A.A. Milne who, in his influential book
quot;Wi i th P hquot; stated of th wise character OWL
quot;Winnie the Poohquot; t t d f the i h t OWL:
quot;He could spell his own name WOL, and he could spell
Tuesday so that you knew it wasn't Wednesday quot;
wasn t Wednesday...
http://www.w3.org/2003/08/owlfaq

23


OWL - WOL

Owl

Winnie the Pooh

Piglet 24


OWL
The second story
y
http://lists.w3.org/Archives/Public/www-webont-wg/2001Dec/0169.html

Jim Hendler wrote:
> ... Dieter is right about that as well) I prefer the three letter WOL to the longer
SWOL. How about OWL as a variation. The words would be the same (Ontology
Web Language) but it has several advantages: (1) it has just one obvious
pronunciation which is easy on the ear; (2) it opens up great
i ti hi h i th t
opportunities for logos; (3) owls are associated with wisdom; (4) it has
an interesting back story. OWL has probably been used for many computer
languages and projects (see below), but I don't think that is a show stopper.

• But the Background is: quot;One World Language“ short OWL in the mid 70‘s
developed at MIT

25


OWL - Specifications

OWL besteht aus 3 Untersprachen
OWL Lite
OWL DL
OWL Full

26


OWL - Specification

The following set of relations hold.
Their inverses do not:
Every legal OWL Lite ontology
i a legal OWL DL ontology.
is l l t l
Every legal OWL DL ontology
is a legal OWL Full ontology
ontology.
Every valid OWL Lite conclusion
is a valid OWL DL conclusion.
Every valid OWL DL conclusion
is a valid OWL Full conclusion.
http://www.w3.org/TR/owl-guide/
27


OWL Syntax and Semantic
Namespace & Header

In addition to rdfs and rdf:
<rdf:RDF … xmlns:owl = „http://www.w3.org/2002/07/owl#“>
<owl:Ontology rdf:about=„“>
<rdfs:comment>my best ontology</rdfs:comment>
<owl:versinoInfo>v0.5</owl:verisonInfo>
….
</owl:Ontology>

Combines Elements of OWL and RFDS Namespace

Import of other ontologies possible
<owl:imports rdf:resource=uri> 28


Classes,
Classes Individuals and Roles

(i.e.
Classes similar to RDFS (i e subclass of rdfs:Class)
owl:Class

Individuals are similar to instances in RDFS
Definition via the property rdf:type

<rdf:Description rdf:about=„KlausTochtermann“>
f p f „
<rdf:type rdf:resource=„Professor“/>
</rdf:Description>

Abbrevated Notation in XML: <Class rdf:about=URI>

<Professor rdf:about=„KlausTochtermann“/>

29


Roles (properties in RDF)

owl:DataTypeProperty (rdf:Domain ~ rdf:Literal|rdf:DataType|xsd:xxx)
<owl:DatatypeProperty rdf:about=„Name“>
<rdfs:domain rdf:resource=„Professor“/>
<rdfs:range rdf:resource= xsd:String“/>
rdf:resource=„xsd:String“/>
</owl:DatatypeProperty>

owl:ObjectProperty ( df D
l Obj tP t (rdf:Domain ~ owl:Thing)
i l Thi )
<owl:ObjectProperty rdf:about=„lecturing“>
<rdfs:domain rdf:resource=„Professor“/>
<rdfs:range rdf:resource=„Lecture“/>
</owl:ObjectProperty>

owl:annotationProperty
Just for commenting on resources
30


Simple Properties between Classes

rdfs:subClassOf Similar to RDFS
All classes are sublcasses from owl:Thing
All classes have the sub class owl:Nothing
owl:disjointWith No individual is contained in both classes

<owlClass rdf:about=„Human“/>
/
<owlClass rdf:about=„Animal“>
<owl:disjointWith rdf:resource=„Human“/>
</owlClass>

owl:equivalentClass
Two classes are semantically equal

31


Properties between Individuals

Owl:sameAs two individuals are the same
<Professor rdf:about=„KlausTochtermann“/>
<owl:sameAs rdf:resource=„ProfessorTochtermann“>
</Professor>

owl:differentFrom two individuals are different
owl:AllDifferent Abrevation for a set of individuals
owl:distinctMembers

<owl:AllDifferent>
<owl:distinctMembers rdf:parseType=„Collection“>
<Person rdf:about=„MichaelGranitzer“>
<Person rdf:about=„MarkusStrohmaier“>
<Person rdf:about KlausTochtermann“>
rdf:about=„KlausTochtermann“>
</olw:distinctMembers>

32
</owl:AllDifferent>



Properties between Individuals

owl:oneOf classes, i.e.
closed classes i e class with a fixed
number of members
<owl:Class rdf:about=„IWMLecturers“>
<owl:oneOf rdf:parseType=„Collection“>
<Person rdf:about=„MichaelGranitzer“>
<Person rdf:about=„MarkusStrohmaier“>
<Person rdf:about=„KlausTochtermann“>
rdf:about „KlausTochtermann >
</olw:oneOf>
</owl:Class>

33


Logical Constructors for Classes

Logical construtors on „simple classes allow to construct new
simple“
complex classes
Human =Women U Men
owl:unionOf <owl:Class rdf:about=„Women“/>
logical OR <owl:Class rdf:about=„Men“>
<owl:complementOf rdf:resource=„Women“>
owl:complementOf </owl:Class>
logical Not
<owl:Class rdf:about=„Human“/>
<owl:unionOf rdf:parseType=„Collection“>
owl:intersectionOf <owl:Class rdf:about=„Men“>
<owl:Class rdf:about=„Women“>
logical AND </owl:unionOf>
</owl:Class>

34


Logical Constructors for Classes

Complex class construtors via role restrictions
Defines a class as set of object for which the role has a value of
a specific class
owl:someValuesFrom
owl:allValuesFrom
Owl:hasValue

Cardinality of roles
owl:maxCardinaltiy
owl:minCardinality
owl:cardinality
35


Relationships between Roles/Role Properties

Relationships between roles
owl:subPropertyOf Hierarchy for properties
owl:inverseOf inverse role
Properties of roles
Symmetry role(A,B) = role(B,A)
<MichaelGranitzer, worksTogetherWith,MarkusStrohmaier>

Transitivity role(A,B) && role(B,C) role (A,C)
<Transistor, isPartOf, Chip> && <Chip, isPartOf,Laptop>
<Transisotr,isPartOf,Laptop>

Functional role(A,B) && role (A,C) <B,sameAs,A>
<MichaelGranitzer, isLecturerOf, Wissenstechnologie>
<GranitzerMichael, isLecturerOf, Wissenstechnologie>

Inverse Functional role(B,A) && role (C,A) <B,sameAs,A> 36


http://www.w3.org/TR/2004/REC-owl-
semantics-20040210/

37


OWL Full

Highest possible expressiveness using OWL
Constraint: Must be valid RDF
D id bilit i not guaranteed
Decidability is t t d
No distinction between roles, classes and instances
An instance may be a class of another instance (Meta-
modelling)

– <Car rdf:about=„BMW“>
<BMW rdf:about=„MyBMW“>

38


OWL DL

p g
DL….Description Logics
Guranteed to be deciable
Contains all elements of OWL but only some elements of RDFS
(mainly rdfs:class and rdf:Property)
Separation of classes, roles and instances
Restrictions on specific roles for classes and instances

Completeness (all implications can be calcualted)
Decidability (all calcualtions can be done in finite time)
With maximum expressiveness

39


OWL Lite

Simplest form of OWL
Restriction on class constructors
R t i ti di lit
Restrictions on cardinality
Predefined class names and role restrictions in specific
situations

Hardly used in practice

40


Editors for OWL

Protégé:
http://protege.stanford.edu/
Altova SemanticWorks (comercial):
( )
http://www.altova.com/products_semanticworks.html
SWOOP:
htt //
http://www.mindswap.org/2004/SWOOP/
i d /2004/SWOOP/
TopBraid Composer™ (comercial):
http://www topbraidcomposer com/
http://www.topbraidcomposer.com/

41


OWL Inference and Reasoning

OWL DL uses Description Logics (Beschreibungslogik)
DL is a subset of First Order
B
Benefits f
fit from L i
Logic
Well known Logic, studied over years
Known runtime complexibility
Existing algorithms for reasoning

42


OWL Inference and Reasoning
Important Properties

Expressive Power (Aussdrucksstärke)
What statements can be made over the model?
C
Computability (B
t bilit (Berechenbarkeit)
h b k it)
Can the evaluation algorithm be calculated in finite
time?
Decideability (Entscheidbarkeit)
Given a logical systems, is there an computable
algorithm to evaluate a given formula? (e.g. decide
whether it is true or false)
)
Tradeoff: Expressive Power vs. Decideability
43
Open vs Closed World Assumption
vs.


Logic Families

Propositonal Logic

( warm ∨ hot ) → cowFeelsWell
Predicate Logic: Formulas contain variables and quantifiers
First Order Logic

– D
Description L i
i ti Logic

Second Order Logic
Many-sorted logic
…
Temporal Logic
44


Propositonal Logic

Elements
El
Atoms: P, Q, R, …
Constants: T
C t t True, F l
False
Junctors: ∧,∨, ¬, →, ↔
Klammern: (, )
(

Example

( warm ∨ hot ) → cowFeelsWell

45


First Order Logic

Elemente
Constants: a, b, John, Animal, Mammal …
Variables: x, y, z, …
, ,
Extension to
Functions: f, g,
Mapping from constants to constants
propositional Logic
like
Predicate: P(x), Q(y),
P di t P( ) Q( )
Mapping von variables to constants ( warm ∨ hot ) → cowFeelsWell
Quantoren: ∀ , ∃
Brackets: (, )

Example

(∀x)isCow( x) → isCow(mother ( x)) 46


Description Logics

Knowledge representation via
Classes
I di id l
Individuals
Roles (Properties)
Subset of First Order Logic
Family having different languages depending on the
expressiveness

47


Description Logic

TBox (terminological box)
Statements over concepts
Class models and class roles
ABox (assertional box)
Statements over Individuals
Assignment of Individuals to classes and filling the roles
OWL DL: TBox and ABox are disjunct
OWL-DL:
E.g. no Class can be an individual
E.g.
E g no roles can be individuals

48


Description Logics
Family Member ALC

ALC – Attributive Language with Complement
Class, Role and Individual
A i
Assignment of I di id l t classes
t f Individuals to l
Equivalence, disjunction and conjunction of classes
owl:Thing, owl:Nothing
owl:intersectionOF, owl:complementOf
owl:allValuesFrom, owl:somealuesFrom
rdfs:range,
rdfs:range rdfs:domain

49


Description Logics
Family Member SHOIN(D)

SHOIN OWL DL
SHOIN– Standard OWL-DL Logic
S: ALC including transitivity of roles
H: b t df
H sub property, rdfs:subPropertyOf
bP t Of
O: owl:oneOf (closed classes)
I: owl:inverseOf (inverse roles)
N: Restrictions on numbers
D: Allows datatypes (owl:DataType)

50


Description Logics
Family Member SHIF(D)

SHIF – OWL Lite
S: ALC including transitivity of roles
H: b t df
H sub property, rdfs:subPropertyOf
bP t Of
I: owl:inverseOf (inverse roles)
F: Functional Roles

51


OWL –DL Reasoning

Application Areas
Taxonomy classification: Computes an inferred class
hierarchy from the asserted definitions
Consistency checking: Detects classes that cannot have any
instances
Instance classification: Finds all classes that a given
individual belongs to
State of the Art
State-of-the-Art are so called tableaux algorithms for reasoning
Worst case time compelxity is exponential, for practical
problems usually faster
http://www.cs.man.ac.uk/~ezolin/dl/
52


DL Resources

OWL Reasoning Examples
http://owl.man.ac.uk/2003/why/latest/
Description Logic
p g
The Description Logic Handbook: Theory,
Implementation, and Applications. F. Baader et al.,
Cambridge University Press, 2003. ISBN 0521781760
Press 2003
http://dl.kr.org/

53


DL (OWL) Reasoner

Racer (commercial):
http://www.racer-systems.com/
FaCT++:
http://owl.man.ac.uk/factplusplus/
Pellet:
htt // ll t
http://pellet.owldl.com/
ldl /

54


A Short Protege Demo
Do you know mad Cows?

http://protege.cim3.net/cgi-bin/wiki.pl?ProtegeOWLDLReasoning 55


Ontology Types and Existing
Ressources

Upper Level Ontologies
Aka Top-Level Ontology, Foundation Ontology
M d l of common objects
Model f bj t
Common Sense Knowledge/ General models of the
World
Domain Ontologies
Model for a specific domain (i.e. Genes, Biomedical
Engineering etc.)
Focused also on th application use case
F d l the li ti

56


Upper Level Ontologies

Formal Upper Level Ontologies
Suggested Upper Merged Ontology (SUMO)
DOLCE
(Open)Cyc
Basic Formal Ontology (BFO)
…
Informal Upper Level Ontologies
DublinCore
WordNet
57


SUMO
Suggested Upper Merged Ontology (SUMO)

1600.p1
From IEEE Working Group 1600 p1
Largest free, formal ontology available, with 20,000
terms and 70,000 axioms when all domain ontologies are
, g
combined. (http://www.ontologyportal.org/)
Mapping to Word Net
Demo

58


WordNet
http://wordnet.princeton.edu/
http://wordnet princeton edu/

Lexical Ontology for (English) Language
Classes: Nouns, Verbs, Adjective, Adverbs
G
Grouped i t S
d into Synsets
t
Relations between Synsets: hypernym, hyponym,
holonym, meronym, troponym…
holonym meronym troponym
220,000 Words; 128,000 Synsets
Limitations
No pronouncation and irregulary verbs
No domain specific vocabulary
59


Cyc

Largest project to capture human knowledge
Formalized representation of a vast quantity of
fundamental human knowledge g
Started 1986, Cycorp spin off 1994
Properitery System using predicate logic and LISP similar
syntax
Structured in micro theories and assertions
Open Source Version available as OpenCyc
http://www.opencyc.org
htt //

60


Cyc
http://www.cyc.com/cyc/technology/whatiscyc_di
r/whatdoescycknow

What Cyc „knows ….
knows“

61


Summary

OWL Syntax adds means to express complex classes and
logics over RFDS
OWL-DL,OWL-Lite, OWL-Full
, ,
Formal Logical Theories for Reasoning
Description Logic for OWL
Abox, Tbox
Upper Ontologies vs. Domain Ontologies
SUMO, WordNet, OpenCyc
Linking Open Data
62


Points you should take away from this
lecture

• What OWL adds to RDFS?
• Types of OWL and Reasoning capabilities?
• Use existing Ontologies/Upper Level Ontologies
• What is Linking Open Data?

Next Week:
• Ontology Modelling
Rules of Thumb for modeling ontologies
• Ontology Alignment & Matching

• Semantic Web Frameworks:
Jena/Sesame with Examples 63


That‘s it for today…

Thanks for your attention

Questions/comments?

mgranitzer@tugraz.at
i @

64


License

This work is licensed under the Creative Commons
Attribution 2.0 Austria License.
To view a copy of this license, visit
http://creativecommons org/licenses/by/2 0/at/
http://creativecommons.org/licenses/by/2.0/at/.

Contributors:
Mathias Lux
Peter Scheir
Klaus Tochtermann
Michael Granitzer
65


Wissenstechnologie Iv 08 09

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