Semantic Web Technologies

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Semantic Web Technologies

Pierre Senellart

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Outline

Introduction

The Semantic Web Ontologies and Reasoning Components of an Ontology

3 Ontology Languages for the Web RDF

RDFS OWL

Querying Data through Ontologies Reference Material

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Outline

Introduction

3 Ontology Languages for the Web Querying Data through Ontologies Reference Material

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Outline

Introduction

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The Semantic Web

A Web in which the resources are semantically described

annotations give information about a page, explain an expression in a page, etc.

More precisely, a resource is anything that can be referred to by a URI

a web page, identified by a URL

a fragment of an XML document, identified by an element node of the document,

a web service,

a thing, an object, a concept, a property, etc.

Semantic annotations: logical assertions that relate resources to some terms in associated ontologies

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Outline

Introduction

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Ontologies

Formal descriptions providing humanusers a shared understanding of a given domain

A controlled vocabulary

Formally defined so that it can also be processed bymachines Logical semantics that enables reasoning

Reasoning is the key for different important tasks of Web data management, in particular:

to answer queries (over possibly distributed data)

to relate objects in different data sources enabling their integration to detect inconsistencies or redundancies

to refine queries with too many answers, or to relax queries with no answer

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Where Do Ontologies Come From?

Manually craftedto represent the knowledge of a specific domain (e.g., life sciences)

Exported fromclassical Web databases

Through information extractionfrom the Web, Wikipedia, etc.

(e.g., DBpedia, YAGO)

Privateto a company or public

Some ontologies focus on instances, others on aschema (see further)

Value of the Semantic Web: bits of ontologies can be re-usedin another, and ontologies can be mapped through anowl:sameAs link

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As of September 2011 Music

Brainz (zitgist)

P20

Turismo de Zaragoza

yovisto

Yahoo!

Geo Planet

YAGO World Fact- book

ViajeroEl Tourism

WordNet (W3C) WordNet (VUA)

VIVO UF VIVO Indiana

VIVO Cornell

VIAF

URI Burner

Sussex Reading Lists

Plymouth Reading Lists

UniRef UniProt UMBEL

UK Post- codes legislation data.gov.uk

Uberblic

UB Mann- heim

TWC LOGD

Twarql transport data.gov.

uk

Traffic Scotland

theses.

fr Thesau-

rus W

totl.net Tele- graphis

TCM GeneDIT Taxon

Concept

Open Library (Talis) tags2con

delicious

t4gm info

Swedish Open Cultural Heritage Surge

Radio

Sudoc

STW RAMEAU

SH

statistics data.gov.

uk

Andrews St.

Resource Lists

ECS South- ampton EPrints SSW

Thesaur us

Smart Link

Slideshare 2RDF

semantic web.org Semantic

Semantic XBRL

SW Dog Food Source Code Ecosystem Linked Data

US SEC (rdfabout)

Sears Scotland

Geo- graphy Scotland Pupils &

Exams

Scholaro- meter

WordNet (RKB Explorer)

Wiki

UN/

LOCODE Ulm

ECS (RKB Explorer)

Roma

RISKS RESEX

RAE2001 Pisa OS

OAI

NSF New-castle

LAAS KISTI JISC

IRIT

IEEE IBM

Eurécom ERA

ePrints dotAC

DEPLOY DBLP

Explorer)(RKB Crime

Reports UK

Course- ware CORDIS

Explorer)(RKB

CiteSeer

Budapest

ACM

riese

Revyu research

data.gov.

Ren. uk Energy Genera- tors

reference data.gov.

uk

Recht- spraak.

nl

ohlohRDF

Last.FM (rdfize)

RDF Book Mashup

Rådata nå!

PSH

Product Types Ontology Product

DB

PBAC Poké-

pédia patents

data.go v.uk Ox

Points

Ord- nance Survey

Openly Local

Open Library

Open Cyc

Open Corpo- rates

Open Calais OpenEI

Open Election Data Project

Open Data Thesau- rus

Ontos News Portal

OGOLOD Janus

AMP Ocean Drilling Codices

New York Times

NVD ntnusc Resource NTU

Lists

Norwe- gian MeSH NDL

subjects

ndlna Experi-my

ment

Italian Museums

medu- cator

MARC Codes List Man- chester Reading Lists Lotico

Weather Stations London

Gazette

LOIUS

Linked Open Colors

lobid Resources

lobid Organi- sations LEM

Linked MDB

LinkedL CCN

Linked GeoData

LinkedCT Linked

User Feedback LOV

Linked Open Numbers LODE

Eurostat (Ontology Central) Linked

EDGAR (Ontology Central)

Linked Crunch- base

lingvoj Lichfield

Spen- ding

LIBRIS

Lexvo

LCSH

DBLP (L3S)

Linked Sensor Data (Kno.e.sis)

Klapp- stuhl- club

Good- win Family

National Radio- activity JP

Jamendo (DBtune)

Italian public schools ISTAT

Immi- gration

iServe

IdRef Sudoc

NSZL Catalog Hellenic

PD Hellenic

FBD

Piedmont Accomo- dations GovTrack GovWILD

Google wrapperArt gnoss

GESIS

GeoWord Net

Geo Species NamesGeo

Geo Linked

Data

GEMET GTAA

STITCH SIDER

Project Guten- berg

MediCare Euro-

stat (FUB)

EURES

Drug Bank

Disea- some

DBLP (FU Berlin) Daily

Med CORDIS

(FUB)

Freebase flickr wrappr

Fishes of Texas

Finnish Munici- palities

ChEMBL FanHubz

Event Media EUTC

Produc- tions

Eurostat

Europeana

EUNIS EU

Insti- tutions

ESD stan- dards

EARTh

Enipedia Popula-

tion (En- AKTing) NHS (En- AKTing) Mortality

(En- AKTing) Energy

(En- AKTing)

Crime (En- AKTing)

CO2 Emission

(En- AKTing) EEA

SISVU educatio

n.data.g ov.uk

ECS South- ampton

ECCO- TCP GND Didactal

ia

DDC Deutsche

Bio- graphie

data dcs Music

Brainz (DBTune) Magna-

tune John Peel (DBTune)

Classical Tune)(DB

Audio Scrobbler (DBTune)

Last.FM artists (DBTune) DB Tropes

Portu- guese DBpedia

dbpedia lite

Greek DBpedia

DBpedia

data- open- ac-uk

SMC Journals

Pokedex

Airports NASA (Data Incu- bator)

Music Brainz (Data Incubator) Moseley

Folk

Metoffice Weather Forecasts

Discogs (Data Incubator)

Climbing data.gov.uk

intervals

Data Gov.ie

data bnf.fr

Cornetto reegle

Chronic- ling America

Chem2 Bio2RDF

Calames business

data.gov.

uk

Bricklink

Brazilian Poli- ticians

BNB

UniSTS

UniPath way UniParc

Taxono my

UniProt (Bio2RDF)

SGD

Reactome

PubMed Pub

Chem PRO-

SITE ProDom

Pfam PDB

OMIM

MGI

KEGG Reaction KEGG

Pathway KEGG Glycan KEGG Enzyme KEGG Drug

KEGG Com- pound InterPro

Homolo Gene HGNC

Gene Ontology

GeneID Affy-

metrix

bible ontology BibBase

FTS

BBC Wildlife Finder BBC Program

mes BBC

Music

Alpine Ski Austria

LOCAH

Amster- Museumdam AGROV

OC AEMET

US Census (rdfabout)

Media Geographic Publications

Government Cross-domain Life sciences User-generated content

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Outline

Introduction

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Classes and class hierarchy

Backbone of the ontology

AcademicStaff is a Class(A class will be interpreted as a set of objects)

AcademicStaff isaStaff (isa is interpreted as set inclusion)

FacultyComponent

Course

MathCourse

Probabilities Algebra Logic CSCourse

DB AI Java Student

UndergraduateStudent MasterStudent

PhDStudent Department

PhysicsDept MathsDept CSDept Staff

AcademicStaff

Lecturer Researcher Professor AdministrativeStaff

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Relations

Declaration of relationswith their signature

(Relations will be interpreted as binary relations between objects) TeachesIn(AcademicStaff,Course)

if one states that “X TeachesInY”, then X belongs to AcademicStaffandY toCourse

TeachesTo(AcademicStaff,Student) Leads(Staff,Department)

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Instances

Classes haveinstances

Dupondis an instance of the classProfessor corresponds to the fact: Professor(Dupond)

Relations also have instances

(Dupond,CS101) is an instance of the relationTeachesIn corresponds to the fact: TeachesIn(Dupond,CS101)

The instance statements can be seen as (and stored in) adatabase

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Ontology = schema + instance

Schema (TBox)

The set of class and relation names

Thesignaturesof relations and alsoconstraints The constraints are used for two purposes

– checking data consistency (like dependencies in databases) – inferring new facts

Instance (ABox) The set of facts

The set of base facts together with the inferred facts should satisfy the constraints

Ontology(i.e., Knowledge Base) = Schema + Instance

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Outline

Introduction

RDFS OWL

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3 ontology languages for the Web

RDF: a very simple ontology language RDFS: Schema for RDF

Can be used to define richer ontologies OWL: a much richer ontology language

We next present them rapidly

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Outline

Introduction

RDFS OWL

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Namespaces

A URImost often takes the form of a URL:

http://live.dbpedia.org/page/%C3%89lectricit%C3%A9_de_France http://sw.opencyc.org/2012/05/10/concept/en/GameOfChance http://www.w3.org/People/Berners-Lee/card#i

http:

//www4.wiwiss.fu-berlin.de/dblp/resource/record/conf/www/2006

Some of these URIs may be actual URLs(point to a browsable resource), some may just be abstract

For simplicity, possibility of definingnamespace prefixes, e.g., dbpedia = http://live.dbpedia.org/page/ along with a default prefix(e.g., mapped to

http://sw.opencyc.org/2012/05/10/concept/en/):

dbpedia:%C3%89lectricit%C3%A9_de_France :GameOfChance

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RDF: Resource Description Framework

RDF facts are triplets

Each triplet is of the form: hSubject Predicate Objecti The subject is a URI, referencing an entity

The predicate is a URI, referencing a relation

The object is either a URI, referencing anentity, or aliteral

h:Dupond:Leads:CSDepti

h:Dupond:HasName“Paul Dupond” i h:Dupond:TeachesIn:UE111i h:Dupond:TeachesTo:Pierrei h:Pierre:EnrolledIn:CSDepti h:Pierre:RegisteredTo:UE111i h:UE111:OfferedBy:CSDepti

The linked data cloud contains dozens of billions of RDF triples

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RDF graph

A set of RDF facts defines

a set of relations between objects

anRDF graph where the nodes are objects:

:TeachesIn

:Dupond :Pierre

:InfoDept

UE111 :TeachesTo

:EnrolledIn

:RegisteredTo

:OfferedBy :Leads

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RDF semantics

A tripleths P oi is interpreted in first-order logic (FOL) as a fact P(s;o)

Example:

Leads(Dupond,CSDept) TeachesIn(Dupond,UE111) TeachesTo(Dupond,Pierre) EnrolledIn(Pierre,CSDept) RegisteredTo(Pierre,UE111) OfferedBy(UE111,CSDept)

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RDF Serialization

Several serialization formats for RDF data, see alternate formats of http://live.dbpedia.org/page/%C3%89lectricit%C3%A9_de_France:

RDF/XML, structured XML representation, allowing for nesting N3 orTurtle, more compact, readable syntax, with some syntaxic sugar (Turtle is a subset of N3)

N-Triples, a simple text-based format

RDFato integrate RDF annotations into HTML

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Outline

Introduction

RDFS OWL

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RDFS: RDF Schema

Not detailed here: the schema in RDF is super simplistic An RDF Schemadefines the schema of a richer ontology

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RDF Schema

Do net get confused: RDFS can use RDF as syntax, i.e., RDFS statements can be themselves expressed as RDF triplets using some specificproperties andobjects used as RDFS keywords with a particular meaning.

Declaration of classes and subclass relationships hStaffrdf:typerdfs:Classi

hJavardfs:subClassOfCSCoursei

Declaration of instances (beyond the pure schema) hDupondrdf:type AcademicStaffi

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RDF Schema - continued

Declaration of relations (properties in RDFS terminology) hRegisteredTordf:type rdfs:Propertyi

Declaration of subproperty relationships

hLateRegisteredTordfs:subPropertyOfRegisteredToi Declaration of domain and range restrictions for predicates

hTeachesInrdfs:domainAcademicStaffi hTeachesInrdfs:rangeCoursei

TeachesIn(AcademicStaff,Course)

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RDFS logical semantics

RDF and RDFS statements FOL translation DL notation

hi rdf:type Ci C(i) i :C orC(i)

hi P ji P(i;j) i P j orP(i;j)

hC rdfs:subClassOf Di 8X(C(X) )D(X)) C vD hP rdfs:subPropertyOf Ri 8X8Y(P(X;Y) )R(X;Y)) PvR hP rdfs:domain Ci 8X8Y(P(X;Y) )C(X)) 9P vC hP rdfs:range Di 8X8Y(P(X;Y) )D(Y)) 9P vD DL: Description logics, a specialized logical formalism

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Outline

Introduction

RDFS OWL

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OWL: Web Ontology Language

OWL extends RDFS with the possibility to express additional constraints

Main OWL constructs

Disjointness between classes

Constraints of functionality and symmetry on predicates Intentional class definitions

Class union and intersection

Inspired by description logics

Several profiles: OWL Full, OWL DL, OWL Lite, OWL 2 EL, OWL 2 QL, OWL 2 RL. Different profiles include different features, and have different tractability

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OWL constructs

Disjointness between classes:

OWL notation FOL translation DL notation hC owl:disjointWith Di 8X(C(X) ) :D(X)) Cv :D

Constraints of functionality and symmetry on predicates:

OWL notation FOL translation DL notation

h P rdf:type

owl:FunctionalPropertyi 8X8Y8Z (funct P) (P(X;Y) ^P(X;Z) )Y=

Z)

or9Pv (1P)

hPrdf:type 8X8Y8Z (funct P )

owl:InverseFunctionalPropertyi (P(X;Y) ^P(Z;Y) )X= Z)

or 9P v (

1P ) hPowl:inverseOfQi 8X8Y(P(X;Y) ,

Q(Y;X))

PQ hPrdf:type owl:SymmetricProperty

i 8X8Y(P(X;Y) )

P(Y;X))

PvP

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Definition of intentional classes in OWL

Goal: allow expressing complex constraints such as:

departments can be lead only by professors

only professors or lecturers may teach to undergraduate students.

The keyword owl:Restrictionis used in association with a blank node class, and some specific restriction properties:

owl:someValuesFrom owl:allValuesFrom owl:minCardinality owl:maxCardinality

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OWL Semantics

OWL notation FOL translation DL notation

_a owl:onProperty P

_a owl:allValuesFrom C 8Y(P(X;Y) )C(Y)) 8P:C _a owl:onProperty P

_a owl:someValuesFrom C 9Y(P(X;Y) ^C(Y)) 9P:C _a owl:onProperty P

_a owl:minCardinalityn 9Y1: : : 9Yn(P(X;Y1) ^ : : : ^

P(X;Yn) ^^Vi;j2[1::n];i6=j(Yi6=Yj)) (n P) _a owl:maxCardinalityn 8Y1: : : 8Yn8Yn+1

(P(X;Y1) ^ : : : ^ P(X;Yn) ^

P(X;Yn+1) (n P) )^Wi;j2[1::n+1];i6=j(Yi=Yj))

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Unnamed new classes by example

Departments can be lead only by professors

Define the set of objects that are lead by professors _a rdfs:subClassOf owl:Restriction _a owl:onProperty Leads

_a owl:allValuesFrom Professor

Now specify that all departments are lead by professors Department rdfs:subClassOf _a

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Union and Intersection of Classes by example

Only professors or lecturers may teach to undergraduate students

_a rdfs:subClassOf owl:Restriction _a owl:onProperty TeachesTo _a owl:someValuesFrom Undergrad

_b owl:unionOf (Professor,Lecturer) _a rdfs:subClassOf _b

This corresponds to an inclusion axiom in Description Logic:

9 TeachesTo.UndergraduateStudentvProfessortLecturer owl:equivalentClass corresponds to double inclusion:

MathStudent Studentu 9 RegisteredTo.MathCourse

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Outline

Introduction

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Querying using RDFS

RDFS statements can be used to infer new triples Example

Base factResponsibleOf(durand;ue111)

Use the statementhResponsibleOf rdfs:domainProfessori i.e., the logical rule: ResponsibleOf(X;Y) )Professor(X) With substitution {X/durand, Y/ue111}

Infer factProfessor(durand)

Use the statementhProfessor rdfs:subClassOfAcademicStaffi i.e., the ruleProfessor(X) )AcademicStaff(X)

With substitution {X/durand}

Infer factAcademicStaff(durand) etc.

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The saturation algorithm

Keep infering new facts until a fixpoint is reached Note: Only polynomially many facts can be added ptime

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Querying using DL

RDFS simpler and very used but limited

Query answering is unfeasible for all of OWL (even OWL-DL). . . but restrictions exist that have more reasonable complexity (OWL-Lite, OWL 2 QL, OWL 2 EL). OWL-Full is even undecidable!

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SPARQL: query language for RDF data

Graph patternlanguage

Get all URIs, name, emails of persons with all three pieces of information from a FOAF dataset:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT * WHERE {

?person foaf:name ?name .

?person foaf:mbox ?emails . }

The SPARQL processor may or may not use reasoning w.r.t. the schema

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Outline

Introduction

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Where can Semantic Content be Found?

In the linked data, through Web-available RDF data:

dumpsof an entire ontology, in one of the RDF serialization formats (RDF/XML, Turtle, N-Triples)

crawlableRDF content, with small fragments pointing to other fragments

aSPARQL endpoint

HTML annotated withRDFa,

cf.http://www.w3.org/TR/rdfa-syntax/

Other popular semantic content embedded in Web pages:

microformats (hCard, vCard, etc.), microdata

(cf. http://schema.org/). Not directly the spirit of the Semantic Web, but heavily used.

RDF content used internally in a company

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Systems

RDF stores (triplestores) with relational or native backend, open-source or commercial, see

http://en.wikipedia.org/wiki/Triplestore. Apache Jenais a popular open-source Java store.

SPARQL engines, usually on top of a triplestore.

http://en.wikipedia.org/wiki/SPARQL Semantic browsers, to navigate RDF content,

http://en.wikipedia.org/wiki/Linked_data#Browsers A semantic Web search engine,http://sig.ma/

Tool to viewsemantic data in Web pages:

http://www.google.com/webmasters/tools/richsnippets

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To go further. . .

The specifications on http://www.w3.org/

A gentle introduction to the Semantic Web:

A Semantic Web Primer, G. Antoniou, F. van Harmelen, MIT Press, 2008

A practical approach:

Semantic Web for the Working Ontologist: Modeling in RDF, RDFS and OWL, Dean Allemang, James A. Hendler,

Morgan-Kaufman, 2008 Contents of this lecture from:

Web data management, S. Abiteboul, I. Manolescu, P. Rigaux, M.-C. Rousset, P. Senellart, Cambridge University Press, 2012.

Also available at http://webdam.inria.fr/Jorge/