Semantic Modelling using Semantic Web Technology

Semantic Modelling WorkshopSemantic Web Technology
RinkeHoekstrahoekstra@few.vu.nl
Semantic Web Rubik's Cube by dullhunk at flickr under a cc-license. Thanks!

Overview
Semantic Web: background
Ideology
Semantic Web and Linked Data
Knowledge Representation and Ontology
Quick overview
RDF and RDFS
OWL 2 DL
SKOS
SPARQL
Resources
Wrap Up
Tutorial information

Background Information
The Web as a Knowledge Base

The Semantic Web Ideology
Identity is everything
Partial solutions are great too!
Layer cake/Web Stack
2/22/10
5
OWL

Key Aspects
World Wide Web Consortium
Globally unique identifiers
URI and IRI
Straightforward data integration
Interdependent languages
Resource Description Framework (RDF)
RDF Schema (RDFS)
Web Ontology Language (OWL), and OWL 2
SPARQL Query Language for RDF (SPARQL)
Semantic Web Rule Language (SWRL)
Rule Interchange Format (RIF)
Simple Knowledge Organization System (SKOS)

Semantic Web or Linked Data?
Initially
`Metadata’ for web pages
Since ~2006
`Web of Data’
Semantic web as data source in its own right
Linked Data
A ‘Databaseesque’ Web
RDF Triple stores
Common schema and identification mechanism
A single query language
2/22/10
7

Linked Open Data
2/22/10
8

2/22/10
9
November 2009: 13.1 Billion triples, 142 Million links

But… not just Web
History
Semantic Networks and Frame Systems (‘70-ies)
Formal Knowledge Representation (KL-One)
Description Logics (DL)
Model Theoretic Semantics
Logic programming
Strongly based in methodology
Knowledge sharing and reuse
Ontologies
Formal semantics

Why Ontology?
Knowledge bases that mix procedural and declarative knowledge are extremely hard to reuse
Ontologies capture the `domain theory’ of a KBS: that what a KBS knows about
Procedures capture what a KBS does with that knowledge
Problem Solving Methods
Slight problem:
Rules look like procedures, but can also capture declarative knowledge

Why Formal Semantics?
Standard inferences, dependable reasoning
Reusable KBS components should guarantee:
Soundnessall answers given should be correct
Completenessthe system should give all answers
Timelinessthe system should answer within reasonable time
Consistencythe knowledge in a KB should be provably correct

WARNING
Reasoners on the Semantic Web adopt the Open World Assumption as opposed to the Closed World Assumption of many other languages
This means that:
If a reasoner cannot infer that a conclusion holds, it stays silent, and will not report that it does not hold.
This is contrary to the negation as failure (NAF) feature of many rule languages.
Why?
NAF hinders reusability on the Web because conclusions may change depending on new information.

Ingredients
Ontology (TBox)
Classesconcepts in the domain (≈ DB tables)
Propertiesrelations that hold between individuals, or between an individual and a literal value (≈ DB columns)
Axioms (only in OWL)restrictions on relations that may hold between instances of a certain class.
Assertions (ABox)
Individualsinstances of classes in the ontology (≈ DB records)
Property assertionsrelations that hold between instances (≈ DB record entries)
Rules

Architecture

Very Quick Overview
Examples

Multiple Syntaxes
RDF
RDF/XMLVerbose, does not make an exact ‘fit’ with RDF data model
TurtleHuman readable
RDFaEmbedded in XHTML as attributes
TriXSupports ‘named graphs’
OWL
All RDF syntaxes, though RDF/XML is normative
OWL XMLXSLT-able
Functional SyntaxMapping to Structural Specification (UML MOF)
Manchester SyntaxHuman readable, used by most editors (Protégé, TopBraid)

2/22/10
18
URI’sand Namespaces
URI: Universal Resource Identifier
... Just an identifier
http://www.leibnizcenter.org/people#joost
URL: Universal Resource Location
URN: Universal Resource Name
urn:leibnizcenter:people:joost
Namespace
A ‘space’ in which all locally defined names are unique, e.g.:
http://www.hcs.science.uva.nl/staff#joost
Basis for `trust’

RDF Schema
RDF is triple-based<subject,predicate,object>
Resources
rdf:Resource
rdfs:Class
rdf:Property
rdfs:Literal
Properties
rdf:type
rdfs:subClassOf
rdfs:subPropertyOf
rdfs:domain
rdfs:range
rdfs:comment
rdfs:label
RDFS Reasoning
Traverse subclass hierarchy
Infer class membership based on domain and range

RDFS Example
@prefix rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>.
@prefix rdfs:<http://www.w3.org/TR/rdf-schema/>.
@prefixr:<http://www.overheid.nl/regering#>.
@prefixk:<http://www.overheid.nl/kabinet#>.
@prefix :<http://www.overheid.nl/personen#>.
r:Premieraowl:Class;
rdfs:subClassOfr:Minister.
r:is_premier_vanaowl:ObjectProperty;
rdfs:domainr:Premier;
rdfs:ranger:Regering.
:balkenendear:Premier;
r:name ”Jan Peter Balkenende”^^xsd:string;
r:is_premier_van k:balkenende_4 ;
k:balkenende_4 ar:Regering.
2/22/10
20

OWL 2 DL Reasoning
Consistency and coherency checking
Are all axioms and assertions consistent?
Classification
Determine subclass relations between classes
Infer disjointness and equivalence of classes
Realization
Determine class membership for individuals
Infer new property relations with other individuals

OWL 2 DL (1)
owl:Thing and owl:Nothing
Class axioms
Intersection, union, disjointness, equivalence:Minister disjointWith:Kamerlid
someValuesFrom (existential):Omnivore subClassOf:Animal and (:eats some :Vegetable)
allValuesFrom (universal):Herbivore subClassOf:Animal and (:eats only :Vegetable)
hasValue:CowsCalledBettyequivalentTo:Cow and (:name has “Betty”)
Self:Narcissist equivalentTo:likes Self

OWL 2 DL (2)
Class axioms (cont’d)
(Qualified) Cardinality:Premier equivalentTo:is_premier_vanmin 1 :Kabinet:KabinetsubClassOf:heeft_premiermax 1 :Premier
Property axioms
Transitive, chains
Inverse
Functional, inverse functional
Reflexive, irreflexive
Symmetric, asymmetric
Disjoint, equivalent
Property types
Object Property vs. Datatype Property

OWL 2 Profiles
Subsets of OWL 2 syntax that have desirable computational properties
OWL 2 QL
Optimized for ontologies with many instances
Query answering
OWL 2 EL
Optimized for ontologies with many classes
OWL 2 RL
Implementable using rule-based technology

Vocabularies
RDFS and OWL 2 DL semantics often too much
Simple method for describing taxonomies
Simple Knowledge Organization System
Lifting existing KOS’s to the Semantic Web
Every skos:Concept is an OWL individual
Lightweight semantic relations: broader, narrower, and related.
Lightweight mapping relations between skos:ConceptSchemes.
JURIX 2009

Querying: SPARQL
RDF Repositories exposed via SPARQL Endpoints
Query types
SELECT … WHERE …
CONSTRUCT … WHERE … ( similar to rules!)
DELETE … WHERE …
Example
PREFIXr: <http://www.overheid.nl/regering#>
PREFIXk: <http://www.overheid.nl/kabinet#>
SELECT ?name
WHERE
{ ?xr:is_premier_van k:balkenende_4.
?xr:name?name }
?xbinds with <http://www.overheid.nl/personen#balkenende>
?name binds with“Jan Peter Balkenende”^^xsd:string
2/22/10
27

Resources: Documentation
W3C Semantic Web portalhttp://www.w3.org/standards/semanticweb/
Start with
RDF Primerhttp://www.w3.org/TR/rdf-primer/
OWL2 Document Overview & Primerhttp://www.w3.org/TR/owl-overview/http://www.w3.org/TR/owl-primer/
SPARQLhttp://www.w3.org/TR/rdf-sparql-query/
SKOS Primerhttp://www.w3.org/TR/skos-primer/
Rule Interchange Formathttp://www.w3.org/2005/rules/wiki/RIF_Working_Group

Resources: Tools
Editors
TopBraid Composer (RDF+OWL)
Protégé 4 (OWL Only)
Reasoners
Pellet, Fact++, OWLIM, Racer, HermiT, CEL
RDF Repositories
OpenRDF Sesame, 4Store/5Store, Virtuoso, Mulgara
RDB to RDF bridges
D2RQ

Wrap Up: Benefits
Single `database schema’ eases query writing
Global identifiers facilitate data integration
Layered approach eases extensibility
Formal semantics ensure dependability

Wrap Up: Tutorial Information
2 Hour session
TopBraid Composer Standard (trial license)
What we’ll do:
Understanding an ontology & using a reasoner
Data integration using SPARQL
Simple OWL class definitions
Advanced OWL class definitions (extra)

http://www.leibnizcenter.org	70
http://www.rinkehoekstra.nl	68
http://www.slideshare.net	19
http://translate.googleusercontent.com	1

Semantic Modelling using Semantic Web Technology

by Rinke Hoekstra on Feb 23, 2010

Accessibility

Categories

Tags

Upload Details

Usage Rights

4 Embeds 158

Statistics

Semantic Modelling using Semantic Web Technology — Presentation Transcript