Semantic Web and its Logical

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Semantic Web and its Logical
Foundations

Serguei Krivov,

Ecoinformatics Collaboratory

Gund Institute for Ecological Economics, UVM

Overview


Semantic Web



Semantic Web Languages and Tools



Description Logics (DL)


Formalism of
Web Ontology Languages



OWL

latest Web Ontology Language


Why Semantic Web?


Most information on the Web is designed for
human consumption, and even if it was derived
from a database with well defined meanings for
its columns, that the structure of the data is not
evident to a robot browsing the web.



Leaving aside the artificial intelligence problem
of training machines to behave like people, the
Semantic Web approach instead develops
languages for expressing information in a
machine processable form.

The Semantic Web Vision


+
Web made possible through established
standards


TCP/IP
for transporting bits down a wire


HTTP & HTML
for transporting and rendering hyperlinked text

+
Applications
able to exploit this common infrastructure

Result is the WWW as we know it

+
1st generation
web mostly handwritten HTML pages

+
2nd generation
(current) web often machine generated/active

+ Both intended for direct human processing/interaction

+ In
next generation
web,
resources
should be more accessible to
automated processes

To be achieved via
semantic markup

Metadata
annotations that describe content/function

+ Coincides with Tim Berners
-
Lee’s vision of a
Semantic Web


Ian Horroks, Logical Foundations for the Semantic Web


What is Semantic Web?


Semantic Web is an initiative of World Wide Web consortium
(
http://www.w3.org/2001/sw/
)



Semantic Web is a set of Languages and Tools for machine processing of
information stored in WWW



You can think of it as being an efficient way of representing data on the
World Wide Web, or as a globally linked Knowledge Base

.


Semantic Web is about efficient Knowledge Representation mechanism for
WWW. (AI)



Semantic Web is about efficient Reasoning Systems requered for
integration of distributed data .


Ontologies


+
Semantic markup must be
meaningful
to automated processes

+ Ontologies will play a key role


Source of
precisely defined
terms (vocabulary) Can be
shared
across applications (and humans)


+ Ontology typically consists of:


Hierarchical
description of important
concepts
in domain


Descriptions of
properties
of instances of each concept

+ Degree of formality can be quite variable

+ Increased formality and regularity facilitates machine understanding


+ Ontologies can be used, e.g.:


To facilitate agent
-
agent communication in
e
-
commerce


In semantic based
search


To provide richer
service descriptions
that can be more flexibly
interpreted by intelligent agents


Ian Horroks, Logical Foundations for the Semantic Web

RDF

Ressource Definition Framework

<?xml version="1.0"?>

<
Class

rdf:ID
="
Resource
"


xmlns:rdf="http://www.w3.org/1999/02/22
-
rdf
-
syntax
-
ns#"


xmlns="
uri
">


<
property
>
value
</
property
>


<
property
>
value
</
property
>


...

</
Class
>


[ressource] [property] [ressource]



[Hamlet] [Author] [W. Shakespeare ]

RDF Usage


Add ”annotations” for web
-
pages ?


Add ”annotations” for web
-
services ?


Instead of building a menu for a web
-
site,
declare the content in RDF, and let the user
-
agent build the menu dynamically ?


Describe all images on your website ?


Market the web.service your web.site
provides ?


RDF is used as a syntax for more
expressive languages: DAML+OIL,
OWL

*.jpg














RDF enhanced Website

”Semantic Web In A Box”


A Semantic Web in A Box Architecture

RDF Repository

Search

View

Update

Manage

Internet

Agents

*.gif

*.asp

*.html

*.jsp

From Jens Jacob Anderson’s Semantic Web Tutorial

Companies ,Tools, and Resources


Ontoprise :


OntoEdit, OntoBrocker



see:
http://www.ontoprise.de/products/index_html_en


Unicorn


http://www.unicorn.com/


KAON :



http://kaon.semanticweb.org/


Protégé
-
Free Ontology Editor


http://protege.stanford.edu/


Semantic Web Tools Tutorial

http://www.daml.org/2003/05/swmu
-
tools
-
tutorial/Overview.html



First Semantic Web Website:


http://owl.mindswap.org/

Web Languages

+
Web languages already extended to facilitate
content description



XML Schema (XMLS)



RDF and RDF Schema (RDFS)

+ RDFS recognisable as an
ontology language



Classes and properties



Range and domain of properties



Sub/super
-
classes (and properties)

+ But RDFS not a suitable foundation for Semantic Web



Too weak
to describe resources in sufficient detail


+ Requirements for web ontology language:



Compatible
with existing Web standards (XML, RDF, RDFS)



Easy to understand
and use (based on familiar KR idioms)



Formally specified
and of “adequate” expressive power

possible to provide
automated reasoning
support


Ian Horroks, Logical Foundations for the Semantic Web

Formalism for Ontology Languages: Description Logics

extracts from Franconi’s course

DL
-
examples

DL definition of “Happy Father”




(Example from Ian Horrocks, U Manchester, UK)

A Few Fundamental Definitions

Example:

KB={



A&B,



(C or (not D)),



D

}

The following is true:

KB |= A

KB |= C


Decidability:

A formal system is decidable if it has
inference procedure
i

that always terminates with
definite answer (either KB|
-
A or not KB|
-
A)

Why DL are used as formalism of Semantic Web ?


FOL

sound, complete, but not decidable



Proposition Logic
-

sound, complete, decidable,
but has low expressive power



DL
-

has sound, complete, decidable inference
procedure; has reasonable expressive power



Alternatives to DL
-

decidable fragments of FOL
-

Horn logic (prolog), F
-
Logic

OWL
-
Web Ontology Language

Extracts from:

Ian Horroks, Logical Foundations for the Semantic Web


+ Three species of OWL



OWL full is union of OWL syntax and RDF



OWL DL restricted to FOL fragment ( DAML+OIL)

OWL
Lite is

“easier to implement” subset of OWL DL


+ Semantic layering



OWL DL OWL full
within DL fragment



DL semantics officially
definitive


+ OWL DL based on SHIQ
Description Logic


+ Benefits from many years of DL research



Well defined
semantics



Formal properties
well understood (complexity, decidability)

Known
reasoning algorithms



Implemented systems
(highly optimised)