Wissenstechnologie Iii 08 09

Wissenstechnologie WS 08/09

Michael Granitzer
IWM TU Graz & Know-Center
Know Center

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

The Semantic Web
h b
Stack (rep )
(rep.)
Semantics &
Ontologies

RDF S h
Schema (RDFS)
2
http://kmi.tugraz.at

WS 08/09 Wissenstechnologie @ kmi.tugraz.at

The Semantic Web
Stack (rep.)

Definition „Semantic Web“

The Semantic Web is an extension of the current Web in
which information is given well-defined meaning, better
enbaling computers and people to work in cooperations.

[Berners-Lee et al. 2001]

http://www.sciam.com/print_version.cfm?articleID=00048144-
10D2 1C70 84A9809EC588EF21
10D2-1C70-84A9809EC588EF21

3


The Semantic Web
Stack (rep.)

The Vision as Application Scenario

Plan a trip via the internet using your personal agent
Agent searches automatically for
Suitable flight
Suitable hotels
Alternative routes
Also, the software agent tells you why it made this decision!

4


The Semantic Web
Stack (rep.)

How to Express Semantics
A small example

John Lennon
Is A
Is Member Band
The B tl
Th Beatles

Is Member
Paul McCartney Founded in

Is born in Query: all bands from England

Ist in
Liverpool England ?All bands with English artists?

Inferenz & Reasoning: 5
English i P h i
E li h artists := Person who is an artist and born in England
i db i E l d


The Semantic Web
Stack (rep.)

Semantic Web Stack

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

6


The Semantic Web
Stack (rep.)

Semantic Web Stack

Unicode
URI

7


The Semantic Web
Stack (rep.)

Semantic Web Stack

XML
XML Schema
Namespaces

8


The Semantic Web
Stack (rep.)

Drawbacks of XML

9


The Semantic Web
Stack (rep.)

Drawbacks of XML

No semantic/meaning of tags

Tree-like structure makes it hard to combine decentral
stored information

<Person> <lecture>
<name> x</name> <name> x</name>
/
<lecture> <Person>
… …
</lecture> </Person>
/
</Person> </lecture>
10


The Semantic Web
Stack (rep.)

Semantic Web Stack

RDF

11


The Semantic Web
Stack (rep.)

Goal of RDF

Description of (Web) resource via metadata
Historically focused on web sites
E t d d t „general“ resources
Extended to l“

For
Classification of resources
Classification of relationships between resources
Unambigious description

12


The Semantic Web
Stack (rep.)

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”
13
aul_McCartney


The Semantic Web

RDF – Serialisation Stack (rep.)

Turtle Example - Extended

# Define some namespaces
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix dc: <http://purl.org/dc/elements/1.1/> .
@prefix ex: <http://example org/terms/> .
<http://example.org/terms/>

<http://www.example.org/index.html>
dc:creator <http://www.example.org/staffid/85740> .
# write all statements in short form
<http://www.example.org/staffid/85740>
ex:name quot;John Smithquot;;
ex:age quot;27quot; .

14


The Semantic Web
Stack (rep.)

RDF Extended Concepts

Blank Nodes
Container & Collections
Reification
Syntactical abbreviations, no extension of expressiveness

But how to define meaning?

15


Semantics & Ontologies
Ontologies & Semantics
What is an Ontology?

Greek: „The study of being“
The being
Branch of Philosophy
W can narrow it d
We down t th d fi iti
to the definition of concepts i
f t in
the world and their relationship

16


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‘ 17


How to describe concepts?

Intensional Description: Conditions and properties of a
concept
Natural World: textual summary
y
Logics:

– NNecessary and sufficient conditions
d ffi i di i
– constraints on things
Extensional Description: List of all objects belonging to a
p j g g
concept

18


Example: Mammal

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

Extension
•Elephant
•Lion
•Monkey
Monkey
•....
19



Ontologie (Gruber)
Definition in Computer Science

explicit specification of a conceptualization
conceptualization is an abstract, simplified view of
p , p
the world that we wish to represent for some purpose
Definitions associate the names of entities in the
universe of discourse with human readable text
human-readable
describing what the names mean, and formal axioms
that constrain the interpretation and well-formed use
of these terms
terms.
Formally, an ontology is the statement of a logical
theory

20



Ontologie (Gruber)

Ontologies are often equated with taxonomic
hierarchies of classes, but class definitions, and the
subsumption relation, but ontologies need not be
limited to these forms. … To specify a
forms
conceptualization one needs to state axioms that
do constrain the possible interpretations for the
d fi d terms.
defined t

21



Ontologie (Guarino)
Language vs. Conceptualization

An ontology is a logical theory accounting for the
gy g y g
intended meaning of a formal vocabulary, i.e. its
ontological commitment to a particular conceptualization
of the world. The intended models of a logical language
using such a vocabulary are constrained by its ontological
commitment. An ontology indirectly reflects this
commitment (and the underlying conceptualization) by
h d d d l
approximating these intended models.
an ontology is language-dependent
a conceptualization is language-independent

22



Ontologie (Sowa)
Formalization level of Ontologies

An informal ontology may be specified by a
catalog of types that are either undefined or
defined
d fi d only b statements in a natural l
l by t t t i t l language.
A formal ontology is specified by a collection of
names for concept and relation types organized
in a partial ordering by the type-subtype relation.

23



Ontologie (Obrst)

With respect to definitions of ontologies, I hope to send a portion
of a briefing I made at the Army Knowledge Management
Conference in Ft. Lauderdale late Aug/early Sept of 2004, that
takes you through the ontology spectrum, from taxonomy (weak
spectrum
and strong) to thesaurus (a strong term taxonomy) to
conceptual model (weak ontology) to logical theory (strong
ontology).
The first is unstandardized the second and third each has a
unstandardized,
set of standards associated with them, the third and fourth
have multiple representation languages supporting them,
and the last has some logic behind the representation language,
typically ranging from a description logic (OWL) to first-order
first order
logic (KIF, Common Logic) to a higher order logic.
A logical theory is a formal ontology. The others range from
informal to semi-formal. Other informal ontologies can be
document.
natural language sentences in a document The key point
about formal ontologies (logical theories) is that they are
machine-interpretable, i.e., semantically interpretable by
machine. The others are not, are only interpretable by 24
human beings, though they may be machine-readable and
machine readable
machine-processable. http://kmi.tugraz.at



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

25



Components of an Ontology

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

26


Semantics & Communication Semantics & Ontologies

Why do we need Ontologies in the Web?

Java based C# based
Exchange Semantics
Intelligent Agent on the basis of an Intelligent Agent
agreed Ontology

Q: Is Paul McCartney member of a Rock Band?

27



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

28


Example

Topic Vocabulary: Elephant, Mammal, Animal
Schema:
isSubClassOf defines an transitiv IS-A relationship
IS A
Define that: isSubClassOf(Elephant, Mammal)==true
Define that: isSubClassOf(Mammal, Animal)==true
isSubClassOf(Elephant,Animal)==true

Independent of implementation and applyable to
abritrary vocabularies:
isSubClassOf(A, B)
isSubClassOf(B, C)
isSubClassOf(A,C)==true
29


Example

„Rules
Similar „Rules“ exist in natural language
Fact 1: „An elephant is a mammal“
„Mammals like for example elephants“
Fact 2: „A mammal is an animal“
Based on our formal knowledge we conclude that an
g
„elephant is an animal“.
Note: Exploitable in Ontology Learning from Text

30



Ontology Spectrum (McGuinness)
..or how much semantic expresses

Thesauri
“narrower Formal Frames Selected
t
term”” i
is-a (properties) Logical
Catalog/
relation Constraints
ID (disjointness,
inverse, …)

Informal Formal General
Terms/ is-a instance Value Logical
glossary Restrs. constraints

http://ontolog.cim3.net/file/work/OntologySummit2007/workshop/McGuinness_NIST-interop-ontology-summit_20070423.ppt

Originally from AAAI 1999- Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty;
– updated by McGuinness.
31
Description in: www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html


RDF Schema (RDFS)

Semantic Web Stack

RDF Schema

32


RDF Schema
(RDFS)

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/

33


RDF Schema
(RDFS)

RDF Schema & Object-Orientierted
Languages
j p
RDFS uses object-oriented Concepts:
Classes
Properties of the classes
But not classes have properties (e.g. Java)
Properties are assigned to classes:
Easier to extend vocabulary
Easier to assign properties to classes
Take care on uniqueness of Properties
q p

34


RDF Schema
(RDFS)

RDF Schema
Notation

<http://www.w3.org/2000/01/rdf schema#>.
@prefix rdfs <http://www w3 org/2000/01/rdf-schema#>
@prefix rdf <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
For the following slides we define this namespace

35


RDF Schema
(RDFS)

RDF Schema
Classes

rdfs:Resource Class of all resources
rdfs:Literal Class of literals (Strings)
rdf:XMLLiteral Class of XML Literals
rdfs:Class Class of classes
rdf:Property Class of properties
rdfs:Datatype Class of datatypes (e g integer etc.)
(e.g. etc )
rdf:Statement Class of RDF Statements
rdfs:Container Class of containers

36


RDF Schema
(RDFS)

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
…

37


RDF Schema
(RDFS)

RDF Schema
Instances,
Instances Classes

Typing: Individuals are assigned to classes (multiple
assignments possible)

rdfs:Class

rdf:type

#MyBMW
#Car
rdf:type rdfs:subClassOf

rdfs:Resource

Note: Sometimes it is domain dependent what an instance is
and what not (modelling aspect) 38


RDF Schema
(RDFS)

RDF Schema
Hierarchies

rdf:subClassOf allows to define hierarchies among
classes

#Means of #Electric vehicle
Transportation

rdfs:subClassOf

#MyBMW
#Car #Train
rdf:type

#BMW
rdfs:subClassOf
39


RDF Schema
(RDFS)

RDF Schema
Hierarchies

Rdf:subPropertyOf allows to define hierarchies among
properties
ex:has

– ex: hasFour
– ex:hasTwo

<#BMW> <#BMW>
ex:hasFour <#Tires> . ex:has <#Tires> .

40


RDF Schema
(RDFS)

RDF Schema
Domain & Range

rdf:Domain and rdf:Range allow to specify which
classes of subjects (==domain) and which classes of
object (
bj t (==range) a property can connect
) t t
<ex:has> rdf:domain <#Car>
<ex:has>rdf:Range <rdf:Resource>

41


RDF Schema
Example

42


RDFS Semantics

RDFS Semantics

Model theoretic
Model-theoretic semantics (subfield of formal semantics)
Entailment: Given a graph the graph is transformed according
to the rules of RDFS
Implicit knowledge (i.e. not explicitly modelled)

#Means of #Means of
Transportation Transportation

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

rdfs:subClassOf rdf:type
df rdfs:subClassOf
df bCl Of

#BMW #BMW
43


RDFS Semantics RDFS Semantics

Deductive Rules/Entailment

The RDF Semantics Document defines a list of 44 Entailment
Rules:
s1 K sn
if s1 K sn are valid statements, add statement s
lid dd
s
“do that recursively until the graph does not change
do change”
“this can be done in polynomial time for a specific graph”
We have means for how statements should be
interpreted
We
W can express “meaning” of URI’s using RDFS
“ i ” f URI’ i
http://www.w3.org/TR/rdf-mt/ 44



Entailment Example

u, x,
u x v …. URI‘s or Blank Nodes
URI s

u rdfs : subtype rdfs : Class.
u rdfs : subClassOf rdfs : Re source.
rdfs:subtype
rdfs:Class

#Car rdfs:subClassOf
rdfs:Resource

#Means of
u rdfs : subClassOf v. v rdfs : subClassOf x. Transportation

u rdfs : subClassOf x. rdfs:subClassOf

#Car

45
rdfs:subClassOf

#BMW



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
46
No Counting: “An Elephant has 4 legs”
An legs


Summary

Classes, Instances,
Ontology = Classes Instances Properties and
Relationships
RDFS as terminological vocabulary over RDF
g y
RDF Schema (RDFS):
First step in increasing semantics
No negation and restricted logic capabilities

47


Points you should take away from this
lecture

• What are Ontologies in Computer Science?
• What adds RDFS to the semantic expressiveness of RDF
• Wh i RDFS not enough?
Why is t h?

48


That‘s it for today…

Thanks for your attention

Questions/comments?

mgranitzer@tugraz.at
i @

49


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
50


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