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Introduction to the
               Semantic Web
                Oscar Corcho (ocorcho@fi.upm.es)
                Universidad Politécnica de Madrid

               Universidad del Valle, Cali, Colombia
                       September 7th 2010

Acknowledgements: Asunción Gómez-Pérez, Jesús Barrasa,
Angel López Cima, Oscar Muñoz, Jose Angel Ramos Gargantilla,
María del Carmen Suárez de Figueroa, Boris Villazón, Mariano
Fernández López, Luis Vilches, Carlos Ruíz Moreno

     Work distributed under the license Creative Commons Attribution-
                      Noncommercial-Share Alike 3.0
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
Health and Safety Notice




Classification
       Disclaimer: This is not the only way that applications can be classified or
       grouped. In fact, many other possibilities exist for the classification of
       Semantic Web application.
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
The beginning: Web 1.0

WWW
HTTP
 URI
From Web1.0 to Web2.0

                          More than
                          30M pages


 More than
1000M users




                        New requirements start arising
                        • Cooperation
          WWW
                        • Dynamicity
      HTTP, HTML, URI   • Decentralised change
                        • Heterogeneity
                        • Multimedia content
Web2.0 basic sites and services
Web1.0 vs Web2.0




• Cooperation
• Dynamicity
• Decentralised change
• Heterogeneity
• Multimedia content
Web Applications

• Who doesn‟t know what is a Web application?
• Let‟s define it
   • A web application is an application that is accessed over a
     network such as the Internet or an intranet.
   • The term may also mean a computer software application that is…
      • … hosted in a browser-controlled environment (e.g. a Java
         applet)
      • … or coded in a browser-supported language (such as
         JavaScript, combined with a browser-rendered markup
         language like HTML)
      • … and reliant on a common web browser to render the
         application executable.
• Some comments
   • Too many technology-related terms in the definition
   • No mentions to the evolution of user-generated content (Web1.0 
     Web2.0), although it is already well understood.
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
(Syntactic) Web Limitations

                       Resource
               href         href                   href

    Resource          Resource      Resource              Resource

               href        href      href
     href             Resource

                           href     href
                href
    Resource          Resource      Resource


                             href           href

                                    Resource




•   A place where computers do the
    presentation (easy) and people do
    the linking and interpreting (hard).
•   Why not get computers to do more
    of the hard work?
Hard Work using the Syntactic Web…

Find images of Oscar Corcho

           …Marta Millán (Universidad del Valle)…
What’s the Problem?

• Typical web page
  markup consists of:
   • Rendering information
     (e.g., font size and
     colour)
   • Hyper-links to related
     content
• Semantic content is
  accessible to humans
  but not (easily) to
  computers…
Information we can see…
Universidad del Valle
Organización Universitaria
Alumnos
Investigación
Deporte
Eventos y actividades… (en la universidad/fuera…?)

Noticias

Tipos de personas a los que va dirigido
Alumnos
Profesores
Personal de Administración y Servicios

…
Information a machine can see…




WWW2002
The eleventh inteqnational woqld wide webcon
Sheqaton waikiki hotel
Honolulu, hawaii, USA
7-11 may 2002
1 location 5 days leaqn inteqact
Registeqed paqticipants coming fqom
austqalia, canada, chile denmaqk, fqance,
geqmany, ghana, hong kong, india, iqeland,
italy, japan, malta, new zealand, the
netheqlands, noqway, singapoqe, switzeqland,
the united kingdom, the united states,
vietnam, zaiqe
Registeq now
On the 7th May Honolulu will pqovide the
backdqop of the eleventh inteqnational woqld
wide web confeqence. This pqestigious event 
Speakeqs confiqmed
Tim beqneqs-lee
Tim is the well known inventoq of the Web,…
Solution: XML markup with “meaningful”
                                     tags?




<name>WWW2002
The eleventh inteqnational woqld wide webcon</name>
<date>7-11 may 2002</date>
<location>Sheqaton waikiki hotel
Honolulu, hawaii, USA</location>
<introduction>Registeq now
On the 7th May Honolulu will pqovide the
backdqop of the eleventh inteqnational woqld
wide web confeqence. This pqestigious event 
Speakeqs confiqmed</introduction>
<speaker>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the Web,</bio>
</speaker>
<speaker>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the Web,</bio>
</speaker>
<registration>Registeqed paqticipants coming fqom
austqalia, canada, chile denmaqk, fqance,
geqmany, ghana, hong kong, india, iqeland,
italy, japan, malta, new zealand, the
netheqlands, noqway, singapoqe, switzeqland, the
united kingdom, the united states, vietnam,
zaiqe<registration>
But What About…?




<conf>WWW2002
The eleventh inteqnational woqld wide webcon</conf>
<date>7-11 may 2002</date>
<place>Sheqaton waikiki hotel
Honolulu, hawaii, USA</place>
<introduction>Registeq now
On the 7th May Honolulu will pqovide the
backdqop of the eleventh inteqnational woqld
wide web confeqence. This pqestigious event 
Speakeqs confiqmed</introduction>
<speaker>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the Web,</bio>
</speaker>
<speaker>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the Web,</bio>
</speaker>
<registration>Registeqed paqticipants coming fqom
austqalia, canada, chile denmaqk, fqance,
geqmany, ghana, hong kong, india, iqeland,
italy, japan, malta, new zealand, the
netheqlands, noqway, singapoqe, switzeqland, the
united kingdom, the united states, vietnam,
zaiqe<registration>
Still the Machine only sees…




<conf>WWW2002
The eleventh inteqnational woqld wide webcon<conf>
<date>7-11 may 2002</date>
<place>Sheqaton waikiki hotel
Honolulu, hawaii, USA<place>
<intqoduction>Registeq now
On the 7th May Honolulu will pqovide the
backdqop of the eleventh inteqnational woqld
wide web confeqence. This pqestigious event 
Speakeqs confiqmed</intqoduction>
<speakeq>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the
Web,</bio>
</speakeq>
<speakeq>Tim beqneqs-lee
 <bio>Tim is the well known inventoq of the
Web,</bio>
</speakeq>
<qegistqation>Registeqed paqticipants coming fqom
austqalia, canada, chile denmaqk, fqance,
geqmany, ghana, hong kong, india, iqeland,
italy, japan, malta, new zealand, the
netheqlands, noqway, singapoqe, switzeqland, the
united kingdom, the united states, vietnam,
What is the Semantic Web?
• An extension of the current
  Web…
   • … where information and services
     are given well-defined and
     explicitly represented meaning, …
   • … so that it can be shared and
     used by humans and machines, ...
   • ... better enabling them to work in
     cooperation


• How?
   • Promoting information exchange
     by tagging web content with
     machine processable descriptions
     of its meaning.
   • And technologies and
     infrastructure to do this
Need to Add “Semantics”

• Agreement on the meaning of annotations
    •   Shared understanding of a domain of interest
    •   Formal and machine manipulable model of a domain of interest


• An ontology is an engineering artifact, which provides:
    •   A vocabulary of terms
    •   A set of explicit assumptions regarding the intended meaning of the
        vocabulary.
          • Almost always including concepts and their classification
          • Almost always including properties between concepts


• Besides...
    •   The meaning (semantics) of such terms is formally specified
    •   New terms can be formed by combining existing ones
    •   Can also specify relationships between terms in multiple ontologies
Types of ontologies




                           Thesauri                                         General
                       “narrower term”                        Frames         Logical
                                                Formal
                           relation                         (properties)   constraints
     Catalog/ID                                  is-a



                   Terms/            Informal             Formal       Value        Disjointness,
                  glossary              is-a             instance     Restrs.    Inverse, part-Of ...




 Lassila O, McGuiness D (2001) The Role of Frame-Based Representation on the
  Semantic Web. Technical Report. Knowledge Systems Laboratory. Stanford University.
  KSL-01-02
A catalog

Consoles and Accessories (1150)
    Amiga (12)
    Amstrad (28)
    Atari (22)
     Commodore (13)
     Microsoft (31)
      Xbox (20)
                                  Catalog: finite list of terms. It can provide
      Xbox360 (11)
                                   an unambiguous interpretation of terms.
     Nintendo (338)
                                      (E.g. 1150 unambiguously denotes
      GameBoy (47)
                                         “consoles and accessories“.)
      GameBoy Advance (40)
      GameBoy Color (16)
      Gamecube (38)
      GameBoy Micro (2)
      Nintendo 64 (74)
                                  http://www.todocoleccion.net/catalogo.cfm
      SuperNintendo (51)
      Nintendo DS (52)
      Nintendo wii (16)
A glossary of terms

Action - Proceeding taken in a court of law. Synonymous
with case, suit lawsuit.

Adjudication - A judgment or decree

Adversary system - Basic U.S. trial system in which each
                                                                 Glossary: list of terms and meanings,
of the opposing parties has opportunity to state his
                                                                which are expressed as natural language
viewpoints before the court. Plaintiff argues for defendant's
                                                                              statements.
guilt (criminal) or liability (civil). Defense argues for
defendant's innocence (criminal) or against liability civil)

Affidavit - A written or printed declaration or statement       http://www.headinjury.com/lawglossary.htm
under oath

Affirm - The assertion of an appellate court that the
judgment of the lower court is correct and should stand.
Thesauri
Agricultural economics MT 6.35 Agriculture
FR Agroéconomie
SP Economía agraria
NT1 Agricultural credit
NT1 Agricultural development                         Thesaurus: list of terms that specifies
  NT2 Subsistence agriculture                        what terms are preferred, the relation
NT1 Agricultural markets                              narrower term, etc. (e.g. “agricultural
NT1 Agricultural planning                              credit“ is a narrower term [NT] than
NT1 Agricultural policy                                      “agricultural economics“)
  NT2 Agricultural prices
  NT2 Food security
NT1 Agricultural production
NT1 Agricultural statistics
  NT2 Food statistics
NT1 Land economics
  NT2 Agrarian structure                  http://www2.ulcc.ac.uk/unesco/
     NT3 Land reform
  NT2 Farm size
  NT2 Land reclamation
                              A searching system uses ”agroindustry” when the query
  NT2 Land tenure
                                            includes ”agrocultural industry”,
  NT2 Land value
RT Agricultural enterprises
RT Agroindustry                             Agricultural industry USE Agroindustry
RT Rural economy
Informal is-a




   Term hierarchies: they
  provide a general notion of
generalization and specialization.




      http://dir.yahoo.com/
Formal is-a

                                     Strict subclass hierarchies: if A is a subclass of B,
                                        then if an object is an instance of A necessarily
                                            implies that the object is instance of B.




                                    http://www.xml.com/pub/a/2005/01/26/formtax.html

…
<owl:Class rdf:ID="Transportation"/>
<owl:Class rdf:ID="AirVehicle">
         <rdfs:subClassOf rdf:resource="#Transportation"/>
</owl:Class>
<owl:Class rdf:about="#GroundVehicle">
         <rdfs:subClassOf rdf:resource="#Transportation"/>
</owl:Class>
<owl:Class rdf:about="#Automobile">
         <rdfs:subClassOf> <owl:Class rdf:ID="GroundVehicle"/>
         </rdfs:subClassOf>
</owl:Class>
<owl:Class rdf:ID="Truck">
         <rdfs:subClassOf> <owl:Class rdf:about="#GroundVehicle"/>
         </rdfs:subClassOf>
</owl:Class>
…
Logical constraints

                               Ontologies with general logical constraints:
                              they include constraints, explicit formal definitions,
                                                      etc.


     <!-- http://www.owl-ontologies.com/unnamed.owl#hasDeparturePlace -->
         <owl:ObjectProperty rdf:about="#hasDeparturePlace">
         <rdfs:domain rdf:resource="#travel"/>
         <rdfs:range rdf:resource="#place"/>
     </owl:ObjectProperty>

     <!-- http://www.owl-ontologies.com/unnamed.owl#hasArrivalPlace -->
         <owl:ObjectProperty rdf:about="#hasArrivalPlace">
         <rdfs:domain rdf:resource="#travel"/>
         <rdfs:range rdf:resource="#place"/>
     </owl:ObjectProperty>
                                                       TRAVEL


 Gómez-Pérez A, Fernández-López M, Corcho O (2003)       Has departure place                 Has arrival place
   Ontological engineering. Springer-Verlag, London

                                                                                         PLACE

                      travel (= 1 departurePlace.place)     (= 1 arrivalPlace.place)   ( hasTransportMean.string)
Ontology Languages
   • A large amount of work on Semantic Web has concentrated on
     the definition of a collection or “stack” of languages.
         •   Used to support the representation and use of metadata
         •   Basic machinery that we can use to represent the extra semantic
             information needed for the Semantic Web


                   SWRL

                    OWL

                    RDFS
RDF(S)
                     RDF

                     XML
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             29
RDF: Resource Description Framework

• W3C recommendation
• RDF is graphical formalism ( + XML syntax + semantics)
     • For representing metadata
     • For describing the semantics of information in a machine-
       accessible way
     • Resources are described in terms of properties and property
       values using RDF statements
     • Statements are represented as triples, consisting of a subject,
       predicate and object. [S, P, O]

                            “Oscar Corcho García”
        person:hasName

                         person:hasColleague
oeg:Oscar                                           oeg:Asun

                         person:hasColleague                      person:hasHomePage


                     oeg:Raul                          “http://www.fi.upm.es/”

                                                                                       30
URIs (Universal-Uniform Resource Identifer)


• Two types of identifiers can be used to identify Linked
  Data resources
   • Hash URIs or URIRefs (Unique Resource Identifiers
     References)
      • A URI and an optional Fragment Identifier separated
        from the URI by the hash symbol „#‟
      • http://www.ontology.org/people#Person
      • people:Person
   • Slash URIs or plain URIs can also be used, as in FOAF:
      • http://xmlns.com/foaf/0.1/Person




                                                              31
RDF Serialisations

• Normative
   • RDF/XML (www.w3.org/TR/rdf-syntax-grammar/)
• Alternative (for human consumption)
   •   N3 (http://www.w3.org/DesignIssues/Notation3.html)
   •   Turtle (http://www.dajobe.org/2004/01/turtle/)
   •   TriX (http://www.w3.org/2004/03/trix/)
   •   …




    Important: the RDF serializations allow different
   syntactic variants. E.g., the order of RDF statements
                      has no meaning


                                                                 32
RDF Serialisations. RDF/XML

<?xml version="1.0"?>
<rdf:RDF
  xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
  xmlns:person="http://www.ontologies.org/ontologies/people#"
  xmlns="http://www.oeg-upm.net/ontologies/people#"
  xml:base="http://www.oeg-upm.net/ontologies/people">

  <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasHomePage"/>
  <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasColleague"/>
  <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasName"/>

  <rdf:Description rdf:about="#Raul"/>
  <rdf:Description rdf:about="#Asun">
     <person:hasColleague rdf:resource="#Raul"/>
     <person:hasHomePage>http://www.fi.upm.es</person:hasHomePage>
  </rdf:Description>
  <rdf:Description rdf:about="#Oscar">
     <person:hasColleague rdf:resource="#Asun"/>
     <person:hasName>Oscar Corcho García</person:hasName>
  </rdf:Description>

</rdf:RDF>




                                                                                         33
RDF Serialisations. N3

@base <http://www.oeg-upm.net/ontologies/people >
@prefix person: <http://www.ontologies.org/ontologies/people#>
:Asun person:hasColleague :Raul ;
        person:hasHomePage “http://www.fi.upm.es/”.
:Oscar person:hasColleague :Asun ;
        person:hasName “Óscar Corcho García”.




                                                                 34
Exercise




• Objective
     • Get used to the different syntaxes of RDF
• Tasks
     • Take the text of an RDF file and create its corresponding graph
     • Take an RDF graph and create its corresponding RDF/XML and N3 files




                                                                                   35
Exercise 1.a. Create a graph from a file



• Open the file StickyNote_PureRDF.rdf

• Create the corresponding graph from it

• Compare your graph with those of your colleagues




                                                           36
Exercise 1.a. StickyNote_PureRDF.rdf




    37
Exercise 1.b. Create files from a graph


 • Transform the following graph into N3 syntax



                                        hasMeasurement
                                                                   Measurement8401
          includes     Sensor029

                                                      hasTemperature            atTime
Class01

            includes
                                                              29           2010-06-12T12:00:12


                                   Computer101
                                                           hasOwner
                                                                                            User10A

                                                                                      hasName

                                                                                             Pedro




                                                 38
Blank nodes: structured property values

• Most real-world data involves structures that are more
  complicated than sets of RDF triple statements

                                                           This intermediate URI does not
                         “Oscar Corcho García”                   need to have a name
        person:hasName

                    person:hasPostalAddress
oeg:Oscar


                             address:city                      address:hasStreetName

            city:BoadillaDelMonte                Campus de Montegancedo s/n


• In RDF/XML, it is an <rdf:Description> node with no
  rdf:about
• In N3, it is a resource identifier that starts with „_‟
    • E.g., “_:nodeX”

                                                                                       39
Typed literals


• So far, all values have been presented as strings
• XML Schema datatypes can be used to specify
  values (objects in some RDF triple statements)

                                 person:hasBirthDate
                    oeg:Oscar                          1976-02-02



• In RDF/XML, this is expressed as:
   •   <rdf:Description rdf:about=”#Oscar”>
         <person:hasBirthDate
             rdf:datatype="http://www.w3.org/2001/XMLSchema#date">1976-02-02
         </person:hasBirthDate>
       </rdf:Description>

• In N3, this is expressed as:
   •   oeg:Oscar person:hasBirthDate ”1976-02-02”^^xsd:date .


                                                                                40
RDF Containers

• There is often the need to describe groups of things
    • A book was created by several authors
    • A lesson is taught by several persons
    • etc.
• RDF provides a container vocabulary
    • rdf:Bag  A group of resources or literals, possibly including
      duplicate members, where the order of members is not
      significant
    • rdf:Seq  A group of resources or literals, possibly including
      duplicate members, where the order of members is significant
    • rdf:Alt  A group of resources or literals that are alternatives
      (typically for a single value of a property)

                    person:hasEmailAddress               rdf:type
 oeg:Oscar                                                             rdf:Seq

                                 rdf:_1                  rdf:_2


             “ocorcho@fi.upm.es”               “oscar.corcho@upm.es”

                                                                                 41
RDF Reification

• RDF statements about other RDF statements
   • “Raúl believes that Oscar‟s birthdate is on Feb 2nd, 1976 and that
     his e-mail address is ocorcho@fi.upm.es”


                   modal:believes
oeg:Raúl                                    oeg:Oscar

               person:hasEmailAddress                        person:hasBirthDate


           “ocorcho@fi.upm.es”                          02/02/1976



• RDF Reification
   • Allows expressing beliefs (and other modalities)
   • Allows expressing trust models, digital signatures, etc.
   • Allows expressing metadata about metadata


                                                                                   42
Main value of a structured value


• Sometimes one of the values of a structured value is
  the main one
   • The weight of an item is 2.4 kilograms
   • The most important value is 2.4, which is expressed with
     rdf:value


• Scarcely used

                    product:hasWeight
   product:Item1
                               rdf:value                    units:hasWeightUnit


                                 2.4                  units:kilogram



                                                                                  43
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             44
RDF inference. Graph matching techniques


• RDF inference is based on graph matching
  techniques
• Basically, the RDF inference process consists of the
  following steps:
   • Transform an RDF query into a template graph that has to
     be matched against the RDF graph
      • It contains constant and variable nodes, and constant
        and variable edges between nodes
   • Match against the RDF graph, taking into account constant
     nodes and edges
   • Provide a solution for variable nodes and edges




                                                                 45
RDF inference. Examples (I)

• Sample RDF graph
                             “Oscar Corcho García”
         person:hasName

                          person:hasColleague
 oeg:Oscar                                                   oeg:Asun

                          person:hasColleague                               person:hasHomePage


                      oeg:Raúl                                  “http://www.fi.upm.es/”


• Query: “Tell me who are the persons who have Asun as a
  colleague”
                                      person:hasColleague
              ?                                                         oeg:Asun

   • Result: oeg:Oscar and oeg:Raúl


                                                                                                 46
RDF inference. Examples (II)

• Query: “Tell me which are the relationships between
  Oscar and Asun”
                                               ?
             oeg:Oscar                                      oeg:Asun

   • Result: oeg:hasColleague

• Query: “Tell me the homepage of Oscar colleagues”
                         person:hasColleague
 oeg:Oscar

                                                               person:hasHomePage


                                                               ?


   • Result: “http://www.fi.upm.es/”


                                                                                    47
RDF inference. Entailment rules




                             48
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             49
RDFS: RDF Schema

• W3C Recommendation
• RDF Schema extends RDF to enable talking about classes of
  resources, and the properties to be used with them
   • Class definition: rdfs:Class, rdfs:subClassOf
   • Property definition: rdfs:subPropertyOf, rdfs:range, rdfs:domain
   • Other primitives: rdfs:comment, rdfs:label, rdfs:seeAlso,
     rdfs:isDefinedBy
• RDFS vocabulary adds constraints on models, e.g.:
   •   x,y,z type(x,y) and subClassOf(y,z)    type(x,z)



                                               ex:Animal


                                                      rdfs:subClassOf

                            rdf:type
       ex:Oscar                                ex:Person


                                                                        50
RDF(S) Serialisations. RDF/XML syntax

<?xml version="1.0"?>
<rdf:RDF
  xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
  xmlns:person="http://www.ontologies.org/ontologies/people#"
  xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
  xmlns="http://www.oeg-upm.net/ontologies/people#"
  xml:base="http://www.oeg-upm.net/ontologies/people">

 <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Professor">
   <rdfs:subClassOf>
     <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Person"/>
   </rdfs:subClassOf>
 </rdfs:Class>
 <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Lecturer">
   <rdfs:subClassOf rdf:resource="http://www.ontologies.org/ontologies/people#Person"/>
 </rdfs:Class>
 <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#PhD">
   <rdfs:subClassOf rdf:resource="http://www.ontologies.org/ontologies/people#Person"/>
 </rdfs:Class>
 …


                                                                                          51
RDF(S) Serialisations. RDF/XML syntax

…
 <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasHomePage"/>
 <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasColleague">
  <rdfs:domain rdf:resource=" http://www.ontologies.org/ontologies/people#Person"/>
  <rdfs:range rdf:resource=" http://www.ontologies.org/ontologies/people#Person"/>
 </rdf:Property>
 <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasName">
  <rdfs:domain rdf:resource="http://www.w3.org/2002/07/owl#Thing"/>
 </rdf:Property>

 <person:PhD rdf:ID="Raul"/>
 <person:Professor rdf:ID=“Asun">
    <person:hasColleague rdf:resource="#Raul"/>
    <person:hasHomePage>http://www.fi.upm.es</person:hasHomePage>
 </person:Professor>
 <person:Lecturer rdf:ID="Oscar">
    <person:hasColleague rdf:resource="#Asun"/>
    <person:hasName>Óscar Corcho García</person:hasName>
 </person:Lecturer>
</rdf:RDF>


                                                                                       52
RDF(S) Serialisations. N3


@base <http://www.oeg-upm.net/ontologies/people >
@prefix person: <http://www.ontologies.org/ontologies/people#>
person:hasColleague       a rdf:Property;
                          rdfs:domain person:Person;
                          rdfs:range person:Person.
person:Professor rdfs:subClassOf person:Person.
person:Lecturer rdfs:subClassOf person:Person.
person:PhD rdfs:subClassOf person:Person.
:Asun a person:Professor;
        person:hasColleague :Raul ;
        person:hasHomePage “http://www.fi.upm.es/”.
:Oscar a person:Lecturer;
        person:hasColleague :Asun ;
        person:hasName “Óscar Corcho García”.
:Raul   a person:PhD.
                                                             a is equivalent to rdf:type

                                                                                      53
RDF(S) Example
RDFS
               rdfs:Literal                               rdfs:Class

                                                                    rdf:Type
                      rdfs:range

                                                                                           rdfs:domain
rdf:Type                                                      Flight                                                    arrivalDate
                rdfs:domain                                                           rdfs:domain
                                   rdfs:domain                                               departureDate

  company-name                            singleFare                                                                          rdfs:range
                                                                                                               rdfs:range
                                                 rdfs:range                rdf:Type

                                      units:currencyQuantity                                rdf:Type
rdf:Type          rdf:Type                                                                                              time:Date

                                                                                               RDF

                                                                                                         rdf:Property
                                                                                                                                 rdf:Type
                                                  rdf:Type
                           company-name
                                                                                                                                       rdf:Type

           “Iberia”                                                                                      arrivalDate
                                                                          IB-4321
                                                       singleFare                               departureDate
                                                                                                                               10/11/2005
                                      500 euros
                                                                                                                                                  54
Exercise




•Objective
     • Get used to the different syntaxes of RDF(S)
•Tasks
     • Take the text of an RDF(S) file and create its corresponding graph
     • Take an RDF(S) graph and create its corresponding RDF/XML and N3 files




                                                                                      55
Exercise 2.a. Create a graph from a file


• Open the files StickyNote.rdf and StickyNote.rdfs

• Create the corresponding graph from them

• Compare your graph with those of your colleagues




                                                            56
Exercise 2.a. StickyNote.rdf




                          57
Exercise 2.a. StickyNote.rdfs




                           58
Exercise 2.b. Create files from a graph


   • Transform the following graph into N3 syntax


Room                         Object                           Measurement                   Person



                                          hasMeasurement
          includes     Sensor029

                                                 hasTemperature             atTime
Class01

            includes
                                                         29           2010-06-12T12:00:12


                                   Computer101
                                                           hasOwner
                                                                                            User10A

                                                                                     hasName

                                                                                             Pedro


                                                 59
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             60
RDF(S) inference. Entailment rules




                                61
RDF(S) inference. Additional inferences




                                     62
RDF(S) limitations

• RDFS too weak to describe resources in sufficient detail
   • No localised range and domain constraints
       • Can‟t say that the range of hasChild is person when applied to
         persons and elephant when applied to elephants
   • No existence/cardinality constraints
       • Can‟t say that all instances of person have a mother that is also a
         person, or that persons have exactly 2 parents
   • No boolean operators
       • Can‟t say or, not, etc.
   • No transitive, inverse or symmetrical properties
       • Can‟t say that isPartOf is a transitive property, that hasPart is the
         inverse of isPartOf or that touches is symmetrical
• Difficult to provide reasoning support
   • No “native” reasoners for non-standard semantics
   • May be possible to reason via FOL axiomatisation




                                                                                 63
Exercise




•Objective
     • Understand the features of RDF(S) for implementing ontologies, including its
       limitations
•Tasks
     • Given a scenario description, build a simple ontology in RDF Schema




                                                                                        64
Exercise 3. Domain description

•   Un lugar puede ser un lugar de interés.
•   Los lugares de interés pueden ser lugares turísticos o
    establecimientos, pero no las dos cosas a la vez.
•   Los lugares turísticos pueden ser palacios, iglesias, ermitas y
    catedrales.
•   Los establecimientos pueden ser hoteles, hostales o albergues.
•   Un lugar está situado en una localidad, la cual a su vez puede ser
    una villa, un pueblo o una ciudad.
•   Un lugar de interés tiene una dirección postal que incluye su calle y
    su número.
•   Las localidades tienen un número de habitantes.
•   Las localidades se encuentran situadas en provincias.

•   Covarrubias es un pueblo con 634 habitantes de la provincia de
    Burgos.
•   El restaurante “El Galo” está situado en Covarrubias, en la calle
    Mayor, número 5.
•   Una de las iglesias de Covarrubias está en la calle de Santo
    Tomás.

                                                                            65
Exercise 3. Sample resulting ontology




                                   66
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             67
Sample RDF APIs

• RDF libraries for different languages:
    • Java, Python, C, C++, C#, .Net, Javascript, Tcl/Tk, PHP, Lisp, Obj-C,
      Prolog, Perl, Ruby, Haskell
    • List in http://esw.w3.org/topic/SemanticWebTools

• Usually related to a RDF repository

• Multilanguage:
    • Redland RDF Application Framework (C, Perl, PHP, Python and Ruby):
      http://www.redland.opensource.ac.uk/
• Java:
    • Jena: http://jena.sourceforge.net/
    • Sesame: http://www.openrdf.org/
• PHP:
    • RAP - RDF API for PHP: http://www4.wiwiss.fu-berlin.de/bizer/rdfapi/
• Python:
    • RDFLib: http://rdflib.net/
    • Pyrple: http://infomesh.net/pyrple/


                                                                              68
Jena


• Java framework for building Semantic Web
  applications
• Open source software from HP Labs
• The Jena framework includes:
   •   A RDF API
   •   An OWL API
   •   Reading and writing RDF in RDF/XML, N3 and N-Triples
   •   In-memory and persistent storage
   •   A rule based inference engine
   •   SPARQL query engine




                                                                69
Sesame

• A framework for storage, querying and inferencing of RDF
  and RDF Schema
• A Java Library for handling RDF
• A Database Server for (remote) access to repositories of
  RDF data
• Highly expressive query and transformation languages
   • SeRQL, SPARQL
• Various backends
   • Native Store
   • RDBMS (MySQL, Oracle 10, DB2, PostgreSQL)
   • main memory
• Reasoning support
   • RDF Schema reasoner
   • OWL DLP (OWLIM)
   • domain reasoning (custom rule engine)


                                                             70
Jena example. Graph creation

                                 http://.../JohnSmith
                     vcard:FN                      vcard:N


                 John Smith
                                 vcard:Given            vcard:Family


                                    John                 Smith

// some definitions
String personURI = "http://somewhere/JohnSmith";
String givenName = "John";
String familyName = "Smith";
String fullName = givenName + " " + familyName;
// create an empty
Model Model model = ModelFactory.createDefaultModel();
// create the resource
// and add the properties cascading style
Resource johnSmith = model.createResource(personURI)
    .addProperty(VCARD.FN, fullName)
    .addProperty(VCARD.N, model.createResource()
    .addProperty(VCARD.Given, givenName)
    .addProperty(VCARD.Family, familyName));

                                                                           71
Jena example. Read and write
// create an empty model
Model model = ModelFactory.createDefaultModel();

// use the FileManager to find the input file
InputStream in = FileManager.get().open( inputFileName );
if (in == null) {
    throw new IllegalArgumentException("File not found");
}
                              <rdf:RDF
// read the RDF/XML file
model.read(in, "");               xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'
                                  xmlns:vcard='http://www.w3.org/2001/vcard-rdf/3.0#'
// write it to standard out   >
model.write(System.out);
                                  <rdf:Description rdf:nodeID="A0">
                                    <vcard:Family>Smith</vcard:Family>
                                    <vcard:Given>John</vcard:Given>
                                  </rdf:Description>
                                  <rdf:Description rdf:about='http://somewhere/JohnSmith/'>
                                    <vcard:FN>John Smith</vcard:FN>
                                    <vcard:N rdf:nodeID="A0"/>
                                  </rdf:Description>
                              ...
                              </rdf:RDF>

                                                                                              72
Some RDF editors




• IsaViz
   • http://www.w3.org/2001/11/IsaViz/
• Morla
   • http://www.morlardf.net/
• RDFAuthor
   • http://rdfweb.org/people/damian/RDFAuthor/
• RdfGravity
   • http://semweb.salzburgresearch.at/apps/rdf-gravity/
• Rhodonite
   • http://rhodonite.angelite.nl/




                                                                    73
Main References



• Brickley D, Guha RV (2004) RDF Vocabulary
  Description Language 1.0: RDF Schema. W3C
  Recommendation
      http://www.w3.org/TR/PR-rdf-schema/
• Lassila O, Swick R (1999) Resource Description
  Framework (RDF) Model and Syntax Specification.
  W3C Recommendation
      http://www.w3.org/TR/REC-rdf-syntax/
• RDF validator:
      http://www.w3.org/RDF/Validator/
• RDF resources:
      http://planetrdf.com/guide/

                                                     74
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             75
RDF(S) query languages

•   Languages developed to allow accessing datasets expressed in RDF(S)
    (and in some cases OWL)
             Application                             Application


                   SQL queries                                SPARQL, RQL, etc., queries



             Relational                               RDF(S)
                DB                                     OWL



•   Supported by the most important language APIs
     •   Jena (HP labs)
     •   Sesame (Aduna)
     •   Boca (IBM)
     •   ...
•   There are some differences wrt. languages like SQL, such as
     •   Combination of different sources
     •   Trust management
     •   Open World Assumption



                                            76
Query types

• Selection and extraction
    • “Select all the essays, together with their authors and their authors‟
      names”
    • “Select everything that is related to the book „Bellum Civille‟”
• Reduction: we specify what it should not be returned
    • “Select everything except for the ontological information and the book
      translators”
• Restructuring: the original structure is changed in the final result
    • “Invert the relationship „author‟ by „is author of‟”
• Aggregation
    • “Return all the essays together with the mean number of authors per
      essay”
• Combination and inferences
    • “Combine the information of a book called „La guerra civil‟ and whose
      author is Julius Caesar with the book whose identifier is „Bellum Civille‟”
    • “Select all the essays, together with its authors and author names”,
      including also the instances of the subclasses of Essay
    • “Obtain the relationship „coauthor‟ among persons who have written the
      same book”



                                         77
RDF(S) query language families

•   SquishQL Family             Triple            •   RQL Family                    Description
     •   SquishQL
                              database                 • RQL                         graphs
                                Query                                                 Query
                                                       • SeRQL
     •   rdfDB Query   Language
                              structure                                             semantics
                                                       • eRQL
     •   RDQL                                     •   Controlled natural language
     •   BRQL                                          • Metalog
     •   TriQL                                    •   Other
•   XPath, XSLT, XQuery               XML              •   Algae
     • XQuery for RDF              repository          •   iTQL
                                     Query             •   N3QL
     • XsRQL                         syntax
                                                       •   PerlRDF Query Language
     • TreeHugger and RDFTwig                          •   RDEVICE Deductive
     • RDFT, Nexus Query                                   Language
       Language                                        •   RDFQBE
     • RDFPath, Rpath and RXPath                       •   RDFQL
     • Versa                                           •   TRIPLE
                               SPARQL                  •   WQL
                             W3C Recommendation
                               15 January 2008

                                                                                              78
SPARQL

• SPARQL Protocol and RDF Query Language
• Supported by: Jena, Sesame, IBM Boca, etc.
• Features
   • It supports most of the aforementioned queries
   • It supports datatype reasoning (datatypes can be requested instead
     of actual values)
   • The domain vocabulary and the knowledge representation
     vocabulary are treated differently by the query interpreters
   • It allows making queries over properties with multiple values, over
     multiple properties of a resource and over reifications
   • Queries can contain optional statements
   • Some implementations support aggregation queries
• Limitations
   • Neither set operations nor existential or universal quantifiers can be
     included in the queries
   • It does not support recursive queries



                                                                              79
SPARQL is also a protocol

•   SPARQL is a Query Language …
    Find names and websites of contributors to PlanetRDF:
    PREFIX foaf: <http://xmlns.com/foaf/0.1/>
    SELECT ?name ?website
    FROM <http://planetrdf.com/bloggers.rdf>
    WHERE {
         ?person foaf:weblog ?website .
         ?person foaf:name ?name .
         ?website a foaf:Document }

•   ... and a Protocol
    http://.../qps?query-lang=http://www.w3.org/TR/rdf-sparql-query/
    &graph-id=http://planetrdf.com/bloggers.rdf&query=PREFIXfoaf:
    <http://xmlns.com/foaf/0.1/...

•   Services running SPARQL queries over a set of graphs
•   A transport protocol for invoking the service
•   Based on ideas from earlier protocol work such as Joseki
•   Describing the service with Web Service technologies



                                                                        80
SPARQL Endpoints
• SPARQL protocol services
   • Enables users (human or other) to query a knowledge base using
     SPARQL
   • Results are typically returned in one or more machine-processable
     formats
• List of SPARQL Endpoints
   • http://esw.w3.org/topic/SparqlEndpoints
• Programmatic access using libraries:
   • ARC, RAP, Jena, Sesame, Javascript SPARQL, PySPARQL, etc.
• Examples:

   Project                        Endpoint
   DBpedia                        http://dbpedia.org/sparql
   BBC Programmes and Music http://bbc.openlinksw.com/sparql/
   data.gov                       http://semantic.data.gov/sparql
   data.gov.uk                    http://data.gov.uk/sparql
   Musicbrainz                    http://dbtune.org/musicbrainz/sparql



                                                                         81
A simple SPARQL query
    Data:

    @prefix dc: <http://purl.org/dc/elements/1.1/> .
    @prefix : <http://example.org/book/> .
    :book1 dc:title "SPARQL Tutorial" .

    Query:
SELECT ?title
WHERE
{
  <http://example.org/book/book1> <http://purl.org/dc/elements/1.1/title> ?title .
}
    Query result:      title
                       "SPARQL Tutorial"


•      A pattern is matched against the RDF data
•      Each way a pattern can be matched yields a solution
•      The sequence of solutions is filtered by: Project, distinct, order, limit/offset
•      One of the result forms is applied: SELECT, CONSTRUCT, DESCRIBE, ASK


                                                                                          82
Graph patterns


• Basic Graph Patterns, where a set of triple patterns
  must match
• Group Graph Pattern, where a set of graph patterns
  must all match
• Optional Graph patterns, where additional patterns
  may extend the solution
• Alternative Graph Pattern, where two or more
  possible patterns are tried
• Patterns on Named Graphs, where patterns are
  matched against named graphs




                                                         83
Multiple matches


@prefix foaf:     <http://xmlns.com/foaf/0.1/> .

_:a   foaf:name     "Johnny Lee Outlaw" .
_:a   foaf:mbox     <mailto:jlow@example.com> .
_:b   foaf:name     "Peter Goodguy" .
_:b   foaf:mbox     <mailto:peter@example.org> .
_:c   foaf:mbox     <mailto:carol@example.org> .


PREFIX   foaf:   <http://xmlns.com/foaf/0.1/>
SELECT   ?name ?mbox
WHERE
  { ?x   foaf:name ?name .
    ?x   foaf:mbox ?mbox }


      name                           mbox
      "Johnny Lee Outlaw"            <mailto:jlow@example.com>
      "Peter Goodguy"                <mailto:peter@example.org>


                                                                   84
Matching RDF literals


@prefix   dt:    <http://example.org/datatype#> .
@prefix   ns:    <http://example.org/ns#> .
@prefix   :      <http://example.org/ns#> .
@prefix   xsd:   <http://www.w3.org/2001/XMLSchema#> .

:x   ns:p        "cat"@en .
:y   ns:p        "42"^^xsd:integer .
:z   ns:p        "abc"^^dt:specialDatatype .

SELECT ?v WHERE { ?v ?p "cat" }                v

                                               v
SELECT ?v WHERE { ?v ?p "cat"@en }
                                               <http://example.org/ns#x>

                                               v
SELECT ?v WHERE { ?v ?p 42 }
                                               <http://example.org/ns#y>

SELECT ?v WHERE { ?v ?p "abc"^^<http://example.org/datatype#specialDatatype> }

                                               v
                                               <http://example.org/ns#z>


                                                                                 85
Blank node labels in query results



@prefix foaf:     <http://xmlns.com/foaf/0.1/> .

_:a   foaf:name     "Alice" .
_:b   foaf:name     "Bob" .



PREFIX foaf:    <http://xmlns.com/foaf/0.1/>
SELECT ?x ?name
WHERE { ?x foaf:name ?name }



           x           name             x          name
           _:c         "Alice"     =    _:r        "Alice"
           _:d         "Bob"            _:s        "Bob"



                                                                   86
Group graph pattern


PREFIX foaf:    <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE { { ?x foaf:name ?name . }
         { ?x foaf:mbox ?mbox . }
       }



SELECT ?x
WHERE {}




PREFIX foaf:    <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE { { ?x foaf:name ?name . }
         { ?x foaf:mbox ?mbox . FILTER regex(?name, "Smith")}
       }



                                                                87
Optional graph patterns

@prefix foaf:      <http://xmlns.com/foaf/0.1/> .
@prefix rdf:       <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

_:a   rdf:type      foaf:Person .
_:a   foaf:name     "Alice" .
_:a   foaf:mbox     <mailto:alice@example.com> .
_:a   foaf:mbox     <mailto:alice@work.example> .

_:b   rdf:type      foaf:Person .
_:b   foaf:name     "Bob" .


PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox
WHERE { ?x foaf:name ?name .
         OPTIONAL { ?x foaf:mbox ?mbox }
       }



       name                                 mbox
       "Alice"                              <mailto:alice@example.com>
       "Alice"                              <mailto:alice@work.example>
       “Bob"


                                                                              88
Multiple optional graph patterns

@prefix foaf:          <http://xmlns.com/foaf/0.1/> .

_:a   foaf:name         "Alice" .
_:a   foaf:homepage     <http://work.example.org/alice/> .

_:b   foaf:name         "Bob" .
_:b   foaf:mbox         <mailto:bob@work.example> .



PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?mbox ?hpage
WHERE { ?x foaf:name ?name .
         OPTIONAL { ?x foaf:mbox ?mbox } .
         OPTIONAL { ?x foaf:homepage ?hpage }
       }




       name           mbox                            hpage
       "Alice"                                        <http://work.example.org/alice/>
       “Bob"          <mailto:bob@work.example>




                                                                                         89
Alternative graph patterns

  @prefix dc10:    <http://purl.org/dc/elements/1.0/> .
  @prefix dc11:    <http://purl.org/dc/elements/1.1/> .

  _:a    dc10:title     "SPARQL Query Language Tutorial" .
  _:a    dc10:creator   "Alice" .
  _:b    dc11:title     "SPARQL Protocol Tutorial" .
  _:b    dc11:creator   "Bob" .
  _:c    dc10:title     "SPARQL" .
  _:c    dc11:title     "SPARQL (updated)" .

PREFIX   dc10: <http://purl.org/dc/elements/1.0/>                         title
PREFIX   dc11: <http://purl.org/dc/elements/1.1/>                         "SPARQL Protocol Tutorial"
SELECT   ?title
                                                                          "SPARQL"
WHERE    { { ?book dc10:title ?title } UNION
           { ?book dc11:title ?title } }                                  "SPARQL (updated)"
                                                                          "SPARQL Query Language Tutorial"

SELECT ?x ?y                                   x                                          y
WHERE { { ?book dc10:title ?x } UNION
                                                                                          "SPARQL (updated)"
         { ?book dc11:title ?y } }
                                                                                          "SPARQL Protocol Tutorial"
                                               "SPARQL"
                                               "SPARQL Query Language Tutorial"
SELECT ?title ?author
WHERE                                                         author              title
  { { ?book dc10:title ?title . ?book dc10:creator ?author }
                                                              "Alice"             "SPARQL Protocol Tutorial"
    UNION
    { ?book dc11:title ?title . ?book dc11:creator ?author }} “Bob”               "SPARQL Query Language Tutorial"




                                                                                                                       90
Patterns on named graphs

# Named   graph: http://example.org/foaf/aliceFoaf
@prefix   foaf:<http://.../foaf/0.1/> .
@prefix   rdf:<http://.../1999/02/22-rdf-syntax-ns#> .
@prefix   rdfs:<http://.../2000/01/rdf-schema#> .

_:a   foaf:name      "Alice" .
_:a   foaf:mbox      <mailto:alice@work.example> .
_:a   foaf:knows     _:b .

_:b   foaf:name      "Bob" .
_:b   foaf:mbox      <mailto:bob@work.example> .
_:b   foaf:nick      "Bobby" .
_:b   rdfs:seeAlso   <http://example.org/foaf/bobFoaf> .

<http://example.org/foaf/bobFoaf>
     rdf:type      foaf:PersonalProfileDocument .

# Named   graph: http://example.org/foaf/bobFoaf
@prefix   foaf:<http://.../foaf/0.1/> .
@prefix   rdf:<http://.../1999/02/22-rdf-syntax-ns#> .
@prefix   rdfs:<http://.../2000/01/rdf-schema#> .

_:z   foaf:mbox      <mailto:bob@work.example> .
_:z   rdfs:seeAlso   <http://example.org/foaf/bobFoaf> .
_:z   foaf:nick      "Robert" .

<http://example.org/foaf/bobFoaf>
     rdf:type      foaf:PersonalProfileDocument .



                                                                                 91
Patterns on named graphs II

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

SELECT ?src ?bobNick
FROM NAMED <http://example.org/foaf/aliceFoaf>       src                                   bobNick
FROM NAMED <http://example.org/foaf/bobFoaf>         <http://example.org/foaf/aliceFoaf>   "Bobby"
WHERE
  {                                                  <http://example.org/foaf/bobFoaf>     "Robert"
    GRAPH ?src
    { ?x foaf:mbox <mailto:bob@work.example> .
      ?x foaf:nick ?bobNick
    }
  }


PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX data: <http://example.org/foaf/>

SELECT ?nick
FROM NAMED <http://example.org/foaf/aliceFoaf>
                                                                     nick
FROM NAMED <http://example.org/foaf/bobFoaf>
WHERE                                                                "Robert"
  {
      GRAPH data:bobFoaf {
          ?x foaf:mbox <mailto:bob@work.example> .
          ?x foaf:nick ?nick }
  }




                                                                                                      92
Restricting values

@prefix dc:    <http://purl.org/dc/elements/1.1/> .
@prefix :      <http://example.org/book/> .
@prefix ns:    <http://example.org/ns#> .

:book1   dc:title   "SPARQL Tutorial" .
:book1   ns:price   42 .
:book2   dc:title   "The Semantic Web" .
:book2   ns:price   23 .

PREFIX   dc: <http://purl.org/dc/elements/1.1/>
SELECT   ?title                                       title
WHERE    { ?x dc:title ?title
           FILTER regex(?title, "^SPARQL")            "SPARQL Tutorial"
         }


PREFIX   dc: <http://purl.org/dc/elements/1.1/>
SELECT   ?title                                       title
WHERE    { ?x dc:title ?title
           FILTER regex(?title, "web", "i" )          "The Semantic Web"
         }

PREFIX   dc: <http://purl.org/dc/elements/1.1/>
PREFIX   ns: <http://example.org/ns#>                 title                price
SELECT   ?title ?price
WHERE    { ?x ns:price ?price .                       "The Semantic Web"   23
           FILTER (?price < 30.5)
           ?x dc:title ?title . }



                                                                                   93
Value tests


• Based on XQuery 1.0 and XPath 2.0 Function and
  Operators
• XSD boolean, string, integer, decimal, float, double,
  dateTime
• Notation <, >, =, <=, >= and != for value comparison
  Apply to any type
• BOUND, isURI, isBLANK, isLITERAL
• REGEX, LANG, DATATYPE, STR (lexical form)
• Function call for casting and extensions functions




                            94
Solution sequences and modifiers


•   Order modifier: put the solutions in     SELECT ?name
    order                                    WHERE { ?x foaf:name ?name ; :empId ?emp }
                                             ORDER BY ?name DESC(?emp)
•   Projection modifier: choose certain      SELECT ?name
    variables                                WHERE
                                              { ?x foaf:name ?name }
•   Distinct modifier: ensure solutions
    in the sequence are unique               SELECT DISTINCT ?name
                                             WHERE { ?x foaf:name ?name }
•   Reduced modifier: permit
    elimination of some non-unique           SELECT REDUCED ?name
    solutions                                WHERE { ?x foaf:name ?name }

•   Limit modifier: restrict the number of
    solutions                                SELECT ?name
                                             WHERE { ?x foaf:name ?name }
                                             LIMIT 20
•   Offset modifier: control where the
    solutions start from in the overall      SELECT ?name WHERE { ?x foaf:name ?name }
    sequence of solutions                    ORDER BY ?name
                                             LIMIT   5
                                             OFFSET 10



                                                                                     95
SPARQL query forms

• SELECT
  • Returns all, or a subset of, the variables bound in a query
    pattern match
• CONSTRUCT
  • Returns an RDF graph constructed by substituting variables
    in a set of triple templates
• ASK
  • Returns a boolean indicating whether a query pattern
    matches or not
• DESCRIBE
  • Returns an RDF graph that describes the resources found




                                                                  96
SPARQL query forms: SELECT

@prefix     foaf:   <http://xmlns.com/foaf/0.1/> .

_:a    foaf:name      "Alice" .
_:a    foaf:knows     _:b .
_:a    foaf:knows     _:c .

_:b    foaf:name      "Bob" .

_:c    foaf:name      "Clare" .
_:c    foaf:nick      "CT" .

PREFIX foaf:    <http://xmlns.com/foaf/0.1/>
SELECT ?nameX ?nameY ?nickY
WHERE
  { ?x foaf:knows ?y ;
       foaf:name ?nameX .
    ?y foaf:name ?nameY .
    OPTIONAL { ?y foaf:nick ?nickY }
  }

  nameX                         nameY                nickY
  "Alice"                       "Bob"
  "Alice"                       "Clare"              "CT"


                                                                     97
SPARQL query forms: CONSTRUCT

@prefix         foaf:   <http://xmlns.com/foaf/0.1/> .

_:a       foaf:name        "Alice" .
_:a       foaf:mbox        <mailto:alice@example.org> .




PREFIX foaf:            <http://xmlns.com/foaf/0.1/>
PREFIX vcard:           <http://www.w3.org/2001/vcard-rdf/3.0#>

CONSTRUCT         { <http://example.org/person#Alice> vcard:FN ?name }

WHERE             { ?x foaf:name ?name }



Query result:

@prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0#> .

<http://example.org/person#Alice> vcard:FN "Alice" .




                                                                         98
SPARQL query forms: ASK

@prefix foaf:          <http://xmlns.com/foaf/0.1/> .

_:a    foaf:name        "Alice" .
_:a    foaf:homepage    <http://work.example.org/alice/> .

_:b    foaf:name        "Bob" .
_:b    foaf:mbox        <mailto:bob@work.example> .




PREFIX foaf:   <http://xmlns.com/foaf/0.1/>
ASK { ?x foaf:name "Alice" }




Query result:

yes




                                                                      99
SPARQL query forms: DESCRIBE


PREFIX ent: <http://org.example.com/employees#>
DESCRIBE ?x WHERE { ?x ent:employeeId "1234" }




Query result:

@prefix    foaf:    <http://xmlns.com/foaf/0.1/> .
@prefix    vcard:   <http://www.w3.org/2001/vcard-rdf/3.0> .
@prefix    exOrg:   <http://org.example.com/employees#> .
@prefix    rdf:     <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix    owl:     <http://www.w3.org/2002/07/owl#>

_:a        exOrg:employeeId      "1234" ;

           foaf:mbox_sha1sum     "ABCD1234" ;
           vcard:N
            [ vcard:Family         "Smith" ;
              vcard:Given          "John" ] .

foaf:mbox_sha1sum     rdf:type    owl:InverseFunctionalProperty .



                                                                      100
Main References



• Prud‟hommeaux E, Seaborne A (2008) SPARQL
  Query Language for RDF. W3C Recommendation
      http://www.w3.org/TR/rdf-sparql-query/
• SPARQL validator:
      http://www.sparql.org/validator.html
• SPARQL implementations:
      http://esw.w3.org/topic/SparqlImplementations
• SPARQL Endpoints
      http://esw.w3.org/topic/SparqlEndpoints
• SPARQL in Dbpedia
      http://dbpedia.org/sparql
                                                       101
Index


• Resource Description Framework (RDF)
   • RDF primitives
   • Reasoning with RDF
• RDF Schema
   • RDF Schema primitives
   • Reasoning with RDFS
• RDF(S) Management APIs
• SPARQL
• OWL




                             102
OWL Basics (on top of RDF and RDFS)

• Set of constructors for concept expressions
   • Booleans: and/or/not
      • A Session is a TheoreticalSession or a HandsonSession
      • Slides are not the same as Code
   • Quantification: some/all
      • Sessions must have some EducationalMaterial
      • Sessions can only have Presenters that have developed Grid
        applications or Grid middleware


• Axioms for expressing constraints
   • Necessary and Sufficient conditions on classes
      • A Session that hasEducationalMaterial Code is a
         HandsonSession.
   • Disjointness
      • TheoreticalSessions are disjoint with HandsonSessions
   • Property characteristics: transitivity, inverse
OWL Ontology Example. BioPAX ontology

• http://www.biopax.org/release/biopax-level2.owl
Description Logics

• A family of logic based Knowledge Representation formalisms
   • Descendants of semantic networks and KL-ONE
   • Describe domain in terms of concepts (classes), roles (relationships)
     and individuals
      • Specific languages characterised by the constructors and axioms
         used to assert knowledge about classes, roles and individuals.
      • Example: ALC (the least expressive language in DL that is
         propositionally closed)
           • Constructors: boolean (and, or, not)
           • Role restrictions

• Distinguished by:
   • Model theoretic semantics
      • Decidable fragments of FOL
      • Closely related to Propositional Modal & Dynamic Logics
   • Provision of inference services
      • Sound and complete decision procedures for key problems
      • Implemented systems (highly optimised)
Structure of DL Ontologies

• A DL ontology can be divided into two parts:
   • Tbox (Terminological KB): a set of axioms that describe the
     structure of a domain :
      • Doctor Person
      • Person Man Woman
      • HappyFather Man       hasDescendant.(Doctor
         hasDescendant.Doctor)
   • Abox (Assertional KB): a set of axioms that describe a
     specific situation :
      • John HappyFather
      • hasDescendant (John, Mary)
Most common constructors in class definitions

•   Intersection: C1 ... Cn            Human Male
•   Union: C1 ... Cn                   Doctor Lawyer
•   Negation: C                           Male
•   Nominals: {x1} ... {xn}            {john} ... {mary}
•   Universal restriction: P.C           hasChild.Doctor
•   Existential restriction: P.C         hasChild.Lawyer
•   Maximum cardinality: nP.C            3hasChild.Doctor
•   Minimum cardinality: nP.C            1hasChild.Male
•   Specific Value: P.{x}                hasColleague.{Matthew}

• Nesting of constructors can be arbitrarily complex
    • Person     hasChild.(Doctor   hasChild.Doctor)
• Lots of redundancy
    • A B is equivalent to ( A    B)
    • P.C is equivalent to   P. C
OWL (1.0 and 1.1)

February 2004

Web Ontology Language

Built on top of RDF(S)

Three layers:
- OWL Lite
   - A small subset of primitives
   - Easier for frame-based tools to transition to
- OWL DL
   - Description logic
   - Decidable reasoning
- OWL Full
   - RDF extension, allows metaclasses


Several syntaxes:
- Abstract syntax
- Manchester syntax
- RDF/XML
OWL 2 (I). New features

• October 2009

• New features
   • Syntactic sugar
      • Disjoint union of classes
   • New expressivity
      • Keys
      • Property chains
      • Richer datatypes, data ranges
      • Qualified cardinality restrictions
      • Asymmetric, reflexive, and disjoint properties
      • Enhanced annotation capabilities


• New syntax
   • OWL2 Manchester syntax
OWL 2 (II). Three new profiles

•   OWL2 EL
    •   Ontologies that define very large numbers of classes and/or properties,
    •   Ontology consistency, class expression subsumption, and instance
        checking can be decided in polynomial time.
•   OWL2 QL
    •   Sound and complete query answering is in LOGSPACE (more precisely, in
        AC0) with respect to the size of the data (assertions),
    •   Provides many of the main features necessary to express conceptual
        models (UML class diagrams and ER diagrams).
    •   It contains the intersection of RDFS and OWL 2 DL.
•   OWL2 RL
    •   Inspired by Description Logic Programs and pD*.
    •   Syntactic subset of OWL 2 which is amenable to implementation using rule-
        based technologies, and presenting a partial axiomatization of the OWL 2
        RDF-Based Semantics in the form of first-order implications that can be
        used as the basis for such an implementation.
    •   Scalable reasoning without sacrificing too much expressive power.
    •   Designed for
          • OWL applications trading the full expressivity of the language for
            efficiency,
          • RDF(S) applications that need some added expressivity from OWL 2.
OWL: Most common constructors

Intersection:              C1 ... Cn            intersectionOf                         Human Male
Union:                     C1 ... Cn            unionOf                                Doctor Lawyer
Negation:                     C                 complementOf                             Male
Nominals:                  {x1} ... {xn}        oneOf                                  {john} ... {mary}
Universal restriction:        P.C               allValuesFrom                            hasChild.Doctor
Existential restriction:     P.C                someValuesFrom                           hasChild.Lawyer
Maximum cardinality:         nP[.C]             maxCardinality (qualified or not)        3hasChild[.Doctor]
Minimum cardinality:         nP[.C]             minCardinality (qualified or not)        1hasChild[.Male]
Exact cardinality:         =nP[.C]              exactCardinality (qualified or not)    =1hasMother[.Female]
Specific Value:              P.{x}              hasValue                                 hasColleague.{Matthew}
Local reflexivity:         --                   hasSelf                   Narcisist   Person hasSelf(loves)

Keys                       --                   hasKey                    hasKey(Person, passportNumber, country)

Subclass                   C1 C2                subClassOf                             Human Animal Biped
Equivalence                C1 C2                equivalentClass                        Man Human Male
Disjointness               C1 C2                disjointWith, AllDisjointClasses       Male Female
DisjointUnion              C C1 ... Cn and
                           Ci Cj   forall i≠j   disjointUnionOf           Person DisjointUnionOf (Man, Woman)

Metaclasses and annotations on axioms are also valid in OWL2, and declarations of classes have to provided.
Full list available in reference specs and in the Quick Reference Guide: http://www.w3.org/2007/OWL/refcard
OWL: Most common constructors

Subproperty             P1      P2             subPropertyOf                     hasDaughter hasChild
Equivalence             P1      P2             equivalentProperty                cost price
DisjointProperties      P1      ... Pn         disjointObjectProperties          hasDaughter hasSon
Inverse                 P1      P2-            inverseOf                         hasChild hasParent-
Transitive              P+      P              TransitiveProperty                ancestor+ ancestor
Functional                      1P             FunctionalProperty                T    1hasMother
InverseFunctional               1P-            InverseFunctionalProperty         T    1hasPassportID-
Reflexive                                      ReflexiveProperty
Irreflexive                                    IrreflexiveProperty
Asymmetric                                     AsymmetricProperty
Property chains         P      P1 o ... o Pn   propertyChainAxiom                hasUncle   hasFather o hasBroth

Equivalence             {x1}     {x2}          sameIndividualAs                  {oeg:OscarCorcho} {img:Oscar}
Different               {x1}       {x2}        differentFrom, AllDifferent       {john}  {peter}

NegativePropertyAssertion                      NegativeDataPropertyAssertion      {hasAge john 35}
                                               NegativeObjectPropertyAssertion    {hasChild john peter}

Besides, top and bottom object and datatype properties exist
Basic Inference Tasks

• Subsumption – check knowledge is correct (captures intuitions)
    • Does C subsume D w.r.t. ontology O? (in every model I of O, CI          DI )
• Equivalence – check knowledge is minimally redundant (no
  unintended synonyms)
    • Is C equivalent to D w.r.t. O? (in every model I of O, CI = DI )
• Consistency – check knowledge is meaningful (classes can have
  instances)
    • Is C satisfiable w.r.t. O? (there exists some model I of O s.t. CI       )
• Instantiation and querying
    • Is x an instance of C w.r.t. O? (in every model I of O, xI CI )
    • Is (x,y) an instance of R w.r.t. O? (in every model I of O, (xI,yI)   RI )

• All reducible to KB satisfiability or concept satisfiability w.r.t. a KB
• Can be decided using highly optimised tableaux reasoners
Reasoning Tasks. Classification
Main References

 W3C OWL Working Group (2009) OWL2 Web Ontology Language Document Overview.
   http://www.w3.org/TR/2009/REC-owl2-overview-20091027/
 Dean M, Schreiber G (2004) OWL Web Ontology Language Reference. W3C Recommendation.
   http://www.w3.org/TR/owl-ref/



Gómez-Pérez, A.; Fernández-López, M.; Corcho, O. Ontological Engineering. Springer Verlag. 2003

               Capítulo 4: Ontology languages



 Baader F, McGuinness D, Nardi D, Patel-Schneider P (2003)
 The Description Logic Handbook: Theory, implementation and applications.
 Cambridge University Press, Cambridge, United Kingdom


   Jena web site:              http://jena.sourceforge.net/
   Jena API:                   http://jena.sourceforge.net/tutorial/RDF_API/
   Jena tutorials:             http://www.ibm.com/developerworks/xml/library/j-jena/index.html
                               http://www.xml.com/pub/a/2001/05/23/jena.html

   Pellet:                     http://clarkparsia.com/pellet
   RACER:                      http://www.racer-systems.com/
   FaCT++:                     http://owl.man.ac.uk/factplusplus/
   HermIT:                     http://hermit-reasoner.com/
Ontology Languages
   • A large amount of work on Semantic Web has concentrated on
     the definition of a collection or “stack” of languages.
         •   Used to support the representation and use of metadata
         •   Basic machinery that we can use to represent the extra semantic
             information needed for the Semantic Web


                   SWRL




                                                                 Inference
                    OWL



                                                   Integration
                                                   Integration
                    RDFS
RDF(S)
                                      Annotation



                     RDF                                                     Reasoning over the information we have
                                                                             Could be light-weight (taxonomy)
                     XML                                                     Could be heavy-weight (logic-style)

                                                                                 Integrating information sources

                                                                      Associating metadata to resources (bindings)
The evolution of the Semantic Web
pre-Semantic Web            Semantic Web 1.0           Semantic Web 3.0




                                             Semantic Web
                                               Challenge
                                2004                          2008
  No standardised formats       RDFS, OWL            • Cooperation          Dynamicity
        e.g., (KA)2                                  • Decentralised change
                                                     • Heterogeneity        Multimedia
[Semantic | Web]+ Applications (I)

• No definition in Wikipedia… ;-(




• Why [Semantic | Web]+ application?
[Semantic | Web]+ Applications (II)

• Why [Semantic | Web]+ application?
   • Most of them are focused on the use of semantics
      • In fact, probably it would be better to use
        Semantic [Web]* application
   • However, many of them are not so Web-oriented
      • E.g., very common in data integration approaches
• http://www.readwriteweb.com/archives/10_semantic_
  apps_to_watch.php
   • A key element [of a Semantic Web App] is that the apps all
     try to determine the meaning of text and other data, and
     then create connections for users. Besides, data
     portability and connectibility are keys to these new
     semantic apps - i.e. using the Web as platform.
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
What is the Web of Linked Data?
• An extension of the current
  Web…
   • … where informationdata services
                            and
     are given well-defined and explicitly
     represented meaning, …
   • … so that it can be shared and used
     by humans and machines, ...
   • ... better enabling them to work in
     cooperation


• How?
   • Promoting information exchange by
     tagging web content with machine
     processable descriptions of its
     meaning.
   • And technologies and infrastructure
     to do this
   • And clear principles on how to
     publish data
What is a Linked Data application

• Again, no definition yet




    • Linked Data is a term used to describe a recommended best
      practice for exposing, sharing, and connecting pieces of data,
      information, and knowledge on the Semantic Web using URIs and
      RDF.
    • So every element from the definition of SW application applies
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
The Web
Semantic Webs
Ontologies




 Metadata    <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>
             <RDF triple>   <RDF triple>   <RDF triple>



The web
The Web of Data
The Web of Data
Ontologies




    Alignments     <RDF triple>   <RDF triple>   <RDF triple>
  Onto. - Schema                  <RDF triple>
                   <RDF triple>                  <RDF triple>   Metadata
   Data Sources    <RDF triple>   <RDF triple>   <RDF triple>
                   <RDF triple>   <RDF triple>   <RDF triple>
                   <RDF triple>   <RDF triple>   <RDF triple>
                   <RDF triple>   <RDF triple>   <RDF triple>
                   <RDF triple>   <RDF triple>   <RDF triple>



Resources
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
Annotation-focused applications: key characteristics

• Available at all stages (pre-Semantic Web, SW1.0
  and SW3.0), although predominantly in the early
  ones
• Single (usually small) ontologies, many of them built
  manually
• Centralised ontologies
• Instances stored in a centralised manner, together
  with the ontologies, or in separate files/DBs
• Low heterogeneity and relatively small scale
• Homogeneous quality in data
Annotation in the pre-Semantic Web

• (KA)2
Semantic Web Portals
                                                      Semantic Driven


                                                      Permission-based


                                                      User Oriented
      Portal Administrators
     Ontologies and Software


                     O2
           O1
                          Oi
                Oj
                                               Extranet Users




Agents                    External resources
Extranet view
Content Edition
Semantic-based Visualisation




                  Workpackage

                           has associated

                      Deliverable
    is generated by            has Q.A. partner

                  Organization
Extranet View (RDF lives behind)
Overview

• Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the
  Web of Linked Data and all its applications
   • The Web (1.0 and 2.0)
       • Web applications
   • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0)
       • Semantic Web Applications Or [Semantic | Web]+ Applications
   • The Web of Linked Data
       • Linked Data Applications
• Semantic-based Applications
   • preSemanticWeb Applications
       • Annotation
   • Semantic Web 1.0 Applications
       • Annotation, Data Integration and Decision Support Systems
   • Semantic Web 3.0 Applications
       • (Collaborative) Annotation and Data Integration
• Conclusions and Trends
Data integration applications: key characteristics

• Available at later stages (SW1.0 and SW3.0).
• Still single (usually small) ontologies, many of them
  built manually
   • Although sometimes mappings between local and global
     ontologies
• Still centralised ontologies
• Instances live in distributed DBs, with a focus on run-
  time queries, although also data warehousing
  approach
• Medium heterogeneity and medium scale
• Heterogeneous quality in data
Migrating IGN (Instituto Geográfico Nacional) sources




140
IGN Catalogue Integration: Exploitation of Mappings
                                                                                           Cated.
                                             Query:           NGN
                                 NC       ¿Edif. Religioso
                                            de Soria?
                                                                       Construcción Rel.




                                                                                               Soria




                                BCN200                         BCN25
                                                                                               Cated.

              Edif. Religioso
                                                                                               NS Nieves


                                                                              Catedral


Cated.                                      Response:
Ig. Sto.                                                                      Ermita
                                           Catedral Soria
                                           Ig. Sto. Tomás
                                           Catedral Soria                 Soria
                                         Ermita N.S. Nieves
           Soria                           Catedral Soria
UN FAO Example




Slide 142
Alignments between ontologies and the DB


 Land                        Fishing             Biological           Fisheries   Vessel types    Gear
 areas                        areas               entities          commodities     and size      types




  R2O                        R2O                   R2O                 R2O           R2O           R2O
Document                   Document              Document            Document      Document      Document




                                                                FAO
                                                              FIGIS DB




           http://www.fao.org/aims/aos/fi/
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web
Introduction to the Semantic Web

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Introduction to the Semantic Web

  • 1. Introduction to the Semantic Web Oscar Corcho (ocorcho@fi.upm.es) Universidad Politécnica de Madrid Universidad del Valle, Cali, Colombia September 7th 2010 Acknowledgements: Asunción Gómez-Pérez, Jesús Barrasa, Angel López Cima, Oscar Muñoz, Jose Angel Ramos Gargantilla, María del Carmen Suárez de Figueroa, Boris Villazón, Mariano Fernández López, Luis Vilches, Carlos Ruíz Moreno Work distributed under the license Creative Commons Attribution- Noncommercial-Share Alike 3.0
  • 2. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 3. Health and Safety Notice Classification Disclaimer: This is not the only way that applications can be classified or grouped. In fact, many other possibilities exist for the classification of Semantic Web application.
  • 4. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 5. The beginning: Web 1.0 WWW HTTP URI
  • 6. From Web1.0 to Web2.0 More than 30M pages More than 1000M users New requirements start arising • Cooperation WWW • Dynamicity HTTP, HTML, URI • Decentralised change • Heterogeneity • Multimedia content
  • 7. Web2.0 basic sites and services
  • 8. Web1.0 vs Web2.0 • Cooperation • Dynamicity • Decentralised change • Heterogeneity • Multimedia content
  • 9. Web Applications • Who doesn‟t know what is a Web application? • Let‟s define it • A web application is an application that is accessed over a network such as the Internet or an intranet. • The term may also mean a computer software application that is… • … hosted in a browser-controlled environment (e.g. a Java applet) • … or coded in a browser-supported language (such as JavaScript, combined with a browser-rendered markup language like HTML) • … and reliant on a common web browser to render the application executable. • Some comments • Too many technology-related terms in the definition • No mentions to the evolution of user-generated content (Web1.0  Web2.0), although it is already well understood.
  • 10. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 11. (Syntactic) Web Limitations Resource href href href Resource Resource Resource Resource href href href href Resource href href href Resource Resource Resource href href Resource • A place where computers do the presentation (easy) and people do the linking and interpreting (hard). • Why not get computers to do more of the hard work?
  • 12. Hard Work using the Syntactic Web… Find images of Oscar Corcho …Marta Millán (Universidad del Valle)…
  • 13. What’s the Problem? • Typical web page markup consists of: • Rendering information (e.g., font size and colour) • Hyper-links to related content • Semantic content is accessible to humans but not (easily) to computers…
  • 14. Information we can see… Universidad del Valle Organización Universitaria Alumnos Investigación Deporte Eventos y actividades… (en la universidad/fuera…?) Noticias Tipos de personas a los que va dirigido Alumnos Profesores Personal de Administración y Servicios …
  • 15. Information a machine can see… WWW2002 The eleventh inteqnational woqld wide webcon Sheqaton waikiki hotel Honolulu, hawaii, USA 7-11 may 2002 1 location 5 days leaqn inteqact Registeqed paqticipants coming fqom austqalia, canada, chile denmaqk, fqance, geqmany, ghana, hong kong, india, iqeland, italy, japan, malta, new zealand, the netheqlands, noqway, singapoqe, switzeqland, the united kingdom, the united states, vietnam, zaiqe Registeq now On the 7th May Honolulu will pqovide the backdqop of the eleventh inteqnational woqld wide web confeqence. This pqestigious event  Speakeqs confiqmed Tim beqneqs-lee Tim is the well known inventoq of the Web,…
  • 16. Solution: XML markup with “meaningful” tags? <name>WWW2002 The eleventh inteqnational woqld wide webcon</name> <date>7-11 may 2002</date> <location>Sheqaton waikiki hotel Honolulu, hawaii, USA</location> <introduction>Registeq now On the 7th May Honolulu will pqovide the backdqop of the eleventh inteqnational woqld wide web confeqence. This pqestigious event  Speakeqs confiqmed</introduction> <speaker>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speaker> <speaker>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speaker> <registration>Registeqed paqticipants coming fqom austqalia, canada, chile denmaqk, fqance, geqmany, ghana, hong kong, india, iqeland, italy, japan, malta, new zealand, the netheqlands, noqway, singapoqe, switzeqland, the united kingdom, the united states, vietnam, zaiqe<registration>
  • 17. But What About…? <conf>WWW2002 The eleventh inteqnational woqld wide webcon</conf> <date>7-11 may 2002</date> <place>Sheqaton waikiki hotel Honolulu, hawaii, USA</place> <introduction>Registeq now On the 7th May Honolulu will pqovide the backdqop of the eleventh inteqnational woqld wide web confeqence. This pqestigious event  Speakeqs confiqmed</introduction> <speaker>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speaker> <speaker>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speaker> <registration>Registeqed paqticipants coming fqom austqalia, canada, chile denmaqk, fqance, geqmany, ghana, hong kong, india, iqeland, italy, japan, malta, new zealand, the netheqlands, noqway, singapoqe, switzeqland, the united kingdom, the united states, vietnam, zaiqe<registration>
  • 18. Still the Machine only sees… <conf>WWW2002 The eleventh inteqnational woqld wide webcon<conf> <date>7-11 may 2002</date> <place>Sheqaton waikiki hotel Honolulu, hawaii, USA<place> <intqoduction>Registeq now On the 7th May Honolulu will pqovide the backdqop of the eleventh inteqnational woqld wide web confeqence. This pqestigious event  Speakeqs confiqmed</intqoduction> <speakeq>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speakeq> <speakeq>Tim beqneqs-lee <bio>Tim is the well known inventoq of the Web,</bio> </speakeq> <qegistqation>Registeqed paqticipants coming fqom austqalia, canada, chile denmaqk, fqance, geqmany, ghana, hong kong, india, iqeland, italy, japan, malta, new zealand, the netheqlands, noqway, singapoqe, switzeqland, the united kingdom, the united states, vietnam,
  • 19. What is the Semantic Web? • An extension of the current Web… • … where information and services are given well-defined and explicitly represented meaning, … • … so that it can be shared and used by humans and machines, ... • ... better enabling them to work in cooperation • How? • Promoting information exchange by tagging web content with machine processable descriptions of its meaning. • And technologies and infrastructure to do this
  • 20. Need to Add “Semantics” • Agreement on the meaning of annotations • Shared understanding of a domain of interest • Formal and machine manipulable model of a domain of interest • An ontology is an engineering artifact, which provides: • A vocabulary of terms • A set of explicit assumptions regarding the intended meaning of the vocabulary. • Almost always including concepts and their classification • Almost always including properties between concepts • Besides... • The meaning (semantics) of such terms is formally specified • New terms can be formed by combining existing ones • Can also specify relationships between terms in multiple ontologies
  • 21. Types of ontologies Thesauri General “narrower term” Frames Logical Formal relation (properties) constraints Catalog/ID is-a Terms/ Informal Formal Value Disjointness, glossary is-a instance Restrs. Inverse, part-Of ...  Lassila O, McGuiness D (2001) The Role of Frame-Based Representation on the Semantic Web. Technical Report. Knowledge Systems Laboratory. Stanford University. KSL-01-02
  • 22. A catalog Consoles and Accessories (1150) Amiga (12) Amstrad (28) Atari (22) Commodore (13) Microsoft (31) Xbox (20) Catalog: finite list of terms. It can provide Xbox360 (11) an unambiguous interpretation of terms. Nintendo (338) (E.g. 1150 unambiguously denotes GameBoy (47) “consoles and accessories“.) GameBoy Advance (40) GameBoy Color (16) Gamecube (38) GameBoy Micro (2) Nintendo 64 (74) http://www.todocoleccion.net/catalogo.cfm SuperNintendo (51) Nintendo DS (52) Nintendo wii (16)
  • 23. A glossary of terms Action - Proceeding taken in a court of law. Synonymous with case, suit lawsuit. Adjudication - A judgment or decree Adversary system - Basic U.S. trial system in which each Glossary: list of terms and meanings, of the opposing parties has opportunity to state his which are expressed as natural language viewpoints before the court. Plaintiff argues for defendant's statements. guilt (criminal) or liability (civil). Defense argues for defendant's innocence (criminal) or against liability civil) Affidavit - A written or printed declaration or statement http://www.headinjury.com/lawglossary.htm under oath Affirm - The assertion of an appellate court that the judgment of the lower court is correct and should stand.
  • 24. Thesauri Agricultural economics MT 6.35 Agriculture FR Agroéconomie SP Economía agraria NT1 Agricultural credit NT1 Agricultural development Thesaurus: list of terms that specifies NT2 Subsistence agriculture what terms are preferred, the relation NT1 Agricultural markets narrower term, etc. (e.g. “agricultural NT1 Agricultural planning credit“ is a narrower term [NT] than NT1 Agricultural policy “agricultural economics“) NT2 Agricultural prices NT2 Food security NT1 Agricultural production NT1 Agricultural statistics NT2 Food statistics NT1 Land economics NT2 Agrarian structure http://www2.ulcc.ac.uk/unesco/ NT3 Land reform NT2 Farm size NT2 Land reclamation A searching system uses ”agroindustry” when the query NT2 Land tenure includes ”agrocultural industry”, NT2 Land value RT Agricultural enterprises RT Agroindustry Agricultural industry USE Agroindustry RT Rural economy
  • 25. Informal is-a Term hierarchies: they provide a general notion of generalization and specialization. http://dir.yahoo.com/
  • 26. Formal is-a Strict subclass hierarchies: if A is a subclass of B, then if an object is an instance of A necessarily implies that the object is instance of B. http://www.xml.com/pub/a/2005/01/26/formtax.html … <owl:Class rdf:ID="Transportation"/> <owl:Class rdf:ID="AirVehicle"> <rdfs:subClassOf rdf:resource="#Transportation"/> </owl:Class> <owl:Class rdf:about="#GroundVehicle"> <rdfs:subClassOf rdf:resource="#Transportation"/> </owl:Class> <owl:Class rdf:about="#Automobile"> <rdfs:subClassOf> <owl:Class rdf:ID="GroundVehicle"/> </rdfs:subClassOf> </owl:Class> <owl:Class rdf:ID="Truck"> <rdfs:subClassOf> <owl:Class rdf:about="#GroundVehicle"/> </rdfs:subClassOf> </owl:Class> …
  • 27. Logical constraints Ontologies with general logical constraints: they include constraints, explicit formal definitions, etc. <!-- http://www.owl-ontologies.com/unnamed.owl#hasDeparturePlace --> <owl:ObjectProperty rdf:about="#hasDeparturePlace"> <rdfs:domain rdf:resource="#travel"/> <rdfs:range rdf:resource="#place"/> </owl:ObjectProperty> <!-- http://www.owl-ontologies.com/unnamed.owl#hasArrivalPlace --> <owl:ObjectProperty rdf:about="#hasArrivalPlace"> <rdfs:domain rdf:resource="#travel"/> <rdfs:range rdf:resource="#place"/> </owl:ObjectProperty> TRAVEL  Gómez-Pérez A, Fernández-López M, Corcho O (2003) Has departure place Has arrival place Ontological engineering. Springer-Verlag, London PLACE travel (= 1 departurePlace.place) (= 1 arrivalPlace.place) ( hasTransportMean.string)
  • 28. Ontology Languages • A large amount of work on Semantic Web has concentrated on the definition of a collection or “stack” of languages. • Used to support the representation and use of metadata • Basic machinery that we can use to represent the extra semantic information needed for the Semantic Web SWRL OWL RDFS RDF(S) RDF XML
  • 29. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 29
  • 30. RDF: Resource Description Framework • W3C recommendation • RDF is graphical formalism ( + XML syntax + semantics) • For representing metadata • For describing the semantics of information in a machine- accessible way • Resources are described in terms of properties and property values using RDF statements • Statements are represented as triples, consisting of a subject, predicate and object. [S, P, O] “Oscar Corcho García” person:hasName person:hasColleague oeg:Oscar oeg:Asun person:hasColleague person:hasHomePage oeg:Raul “http://www.fi.upm.es/” 30
  • 31. URIs (Universal-Uniform Resource Identifer) • Two types of identifiers can be used to identify Linked Data resources • Hash URIs or URIRefs (Unique Resource Identifiers References) • A URI and an optional Fragment Identifier separated from the URI by the hash symbol „#‟ • http://www.ontology.org/people#Person • people:Person • Slash URIs or plain URIs can also be used, as in FOAF: • http://xmlns.com/foaf/0.1/Person 31
  • 32. RDF Serialisations • Normative • RDF/XML (www.w3.org/TR/rdf-syntax-grammar/) • Alternative (for human consumption) • N3 (http://www.w3.org/DesignIssues/Notation3.html) • Turtle (http://www.dajobe.org/2004/01/turtle/) • TriX (http://www.w3.org/2004/03/trix/) • … Important: the RDF serializations allow different syntactic variants. E.g., the order of RDF statements has no meaning 32
  • 33. RDF Serialisations. RDF/XML <?xml version="1.0"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:person="http://www.ontologies.org/ontologies/people#" xmlns="http://www.oeg-upm.net/ontologies/people#" xml:base="http://www.oeg-upm.net/ontologies/people"> <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasHomePage"/> <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasColleague"/> <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasName"/> <rdf:Description rdf:about="#Raul"/> <rdf:Description rdf:about="#Asun"> <person:hasColleague rdf:resource="#Raul"/> <person:hasHomePage>http://www.fi.upm.es</person:hasHomePage> </rdf:Description> <rdf:Description rdf:about="#Oscar"> <person:hasColleague rdf:resource="#Asun"/> <person:hasName>Oscar Corcho García</person:hasName> </rdf:Description> </rdf:RDF> 33
  • 34. RDF Serialisations. N3 @base <http://www.oeg-upm.net/ontologies/people > @prefix person: <http://www.ontologies.org/ontologies/people#> :Asun person:hasColleague :Raul ; person:hasHomePage “http://www.fi.upm.es/”. :Oscar person:hasColleague :Asun ; person:hasName “Óscar Corcho García”. 34
  • 35. Exercise • Objective • Get used to the different syntaxes of RDF • Tasks • Take the text of an RDF file and create its corresponding graph • Take an RDF graph and create its corresponding RDF/XML and N3 files 35
  • 36. Exercise 1.a. Create a graph from a file • Open the file StickyNote_PureRDF.rdf • Create the corresponding graph from it • Compare your graph with those of your colleagues 36
  • 38. Exercise 1.b. Create files from a graph • Transform the following graph into N3 syntax hasMeasurement Measurement8401 includes Sensor029 hasTemperature atTime Class01 includes 29 2010-06-12T12:00:12 Computer101 hasOwner User10A hasName Pedro 38
  • 39. Blank nodes: structured property values • Most real-world data involves structures that are more complicated than sets of RDF triple statements This intermediate URI does not “Oscar Corcho García” need to have a name person:hasName person:hasPostalAddress oeg:Oscar address:city address:hasStreetName city:BoadillaDelMonte Campus de Montegancedo s/n • In RDF/XML, it is an <rdf:Description> node with no rdf:about • In N3, it is a resource identifier that starts with „_‟ • E.g., “_:nodeX” 39
  • 40. Typed literals • So far, all values have been presented as strings • XML Schema datatypes can be used to specify values (objects in some RDF triple statements) person:hasBirthDate oeg:Oscar 1976-02-02 • In RDF/XML, this is expressed as: • <rdf:Description rdf:about=”#Oscar”> <person:hasBirthDate rdf:datatype="http://www.w3.org/2001/XMLSchema#date">1976-02-02 </person:hasBirthDate> </rdf:Description> • In N3, this is expressed as: • oeg:Oscar person:hasBirthDate ”1976-02-02”^^xsd:date . 40
  • 41. RDF Containers • There is often the need to describe groups of things • A book was created by several authors • A lesson is taught by several persons • etc. • RDF provides a container vocabulary • rdf:Bag  A group of resources or literals, possibly including duplicate members, where the order of members is not significant • rdf:Seq  A group of resources or literals, possibly including duplicate members, where the order of members is significant • rdf:Alt  A group of resources or literals that are alternatives (typically for a single value of a property) person:hasEmailAddress rdf:type oeg:Oscar rdf:Seq rdf:_1 rdf:_2 “ocorcho@fi.upm.es” “oscar.corcho@upm.es” 41
  • 42. RDF Reification • RDF statements about other RDF statements • “Raúl believes that Oscar‟s birthdate is on Feb 2nd, 1976 and that his e-mail address is ocorcho@fi.upm.es” modal:believes oeg:Raúl oeg:Oscar person:hasEmailAddress person:hasBirthDate “ocorcho@fi.upm.es” 02/02/1976 • RDF Reification • Allows expressing beliefs (and other modalities) • Allows expressing trust models, digital signatures, etc. • Allows expressing metadata about metadata 42
  • 43. Main value of a structured value • Sometimes one of the values of a structured value is the main one • The weight of an item is 2.4 kilograms • The most important value is 2.4, which is expressed with rdf:value • Scarcely used product:hasWeight product:Item1 rdf:value units:hasWeightUnit 2.4 units:kilogram 43
  • 44. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 44
  • 45. RDF inference. Graph matching techniques • RDF inference is based on graph matching techniques • Basically, the RDF inference process consists of the following steps: • Transform an RDF query into a template graph that has to be matched against the RDF graph • It contains constant and variable nodes, and constant and variable edges between nodes • Match against the RDF graph, taking into account constant nodes and edges • Provide a solution for variable nodes and edges 45
  • 46. RDF inference. Examples (I) • Sample RDF graph “Oscar Corcho García” person:hasName person:hasColleague oeg:Oscar oeg:Asun person:hasColleague person:hasHomePage oeg:Raúl “http://www.fi.upm.es/” • Query: “Tell me who are the persons who have Asun as a colleague” person:hasColleague ? oeg:Asun • Result: oeg:Oscar and oeg:Raúl 46
  • 47. RDF inference. Examples (II) • Query: “Tell me which are the relationships between Oscar and Asun” ? oeg:Oscar oeg:Asun • Result: oeg:hasColleague • Query: “Tell me the homepage of Oscar colleagues” person:hasColleague oeg:Oscar person:hasHomePage ? • Result: “http://www.fi.upm.es/” 47
  • 49. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 49
  • 50. RDFS: RDF Schema • W3C Recommendation • RDF Schema extends RDF to enable talking about classes of resources, and the properties to be used with them • Class definition: rdfs:Class, rdfs:subClassOf • Property definition: rdfs:subPropertyOf, rdfs:range, rdfs:domain • Other primitives: rdfs:comment, rdfs:label, rdfs:seeAlso, rdfs:isDefinedBy • RDFS vocabulary adds constraints on models, e.g.: • x,y,z type(x,y) and subClassOf(y,z) type(x,z) ex:Animal rdfs:subClassOf rdf:type ex:Oscar ex:Person 50
  • 51. RDF(S) Serialisations. RDF/XML syntax <?xml version="1.0"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:person="http://www.ontologies.org/ontologies/people#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://www.oeg-upm.net/ontologies/people#" xml:base="http://www.oeg-upm.net/ontologies/people"> <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Professor"> <rdfs:subClassOf> <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Person"/> </rdfs:subClassOf> </rdfs:Class> <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#Lecturer"> <rdfs:subClassOf rdf:resource="http://www.ontologies.org/ontologies/people#Person"/> </rdfs:Class> <rdfs:Class rdf:about="http://www.ontologies.org/ontologies/people#PhD"> <rdfs:subClassOf rdf:resource="http://www.ontologies.org/ontologies/people#Person"/> </rdfs:Class> … 51
  • 52. RDF(S) Serialisations. RDF/XML syntax … <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasHomePage"/> <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasColleague"> <rdfs:domain rdf:resource=" http://www.ontologies.org/ontologies/people#Person"/> <rdfs:range rdf:resource=" http://www.ontologies.org/ontologies/people#Person"/> </rdf:Property> <rdf:Property rdf:about="http://www.ontologies.org/ontologies/people#hasName"> <rdfs:domain rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> </rdf:Property> <person:PhD rdf:ID="Raul"/> <person:Professor rdf:ID=“Asun"> <person:hasColleague rdf:resource="#Raul"/> <person:hasHomePage>http://www.fi.upm.es</person:hasHomePage> </person:Professor> <person:Lecturer rdf:ID="Oscar"> <person:hasColleague rdf:resource="#Asun"/> <person:hasName>Óscar Corcho García</person:hasName> </person:Lecturer> </rdf:RDF> 52
  • 53. RDF(S) Serialisations. N3 @base <http://www.oeg-upm.net/ontologies/people > @prefix person: <http://www.ontologies.org/ontologies/people#> person:hasColleague a rdf:Property; rdfs:domain person:Person; rdfs:range person:Person. person:Professor rdfs:subClassOf person:Person. person:Lecturer rdfs:subClassOf person:Person. person:PhD rdfs:subClassOf person:Person. :Asun a person:Professor; person:hasColleague :Raul ; person:hasHomePage “http://www.fi.upm.es/”. :Oscar a person:Lecturer; person:hasColleague :Asun ; person:hasName “Óscar Corcho García”. :Raul a person:PhD. a is equivalent to rdf:type 53
  • 54. RDF(S) Example RDFS rdfs:Literal rdfs:Class rdf:Type rdfs:range rdfs:domain rdf:Type Flight arrivalDate rdfs:domain rdfs:domain rdfs:domain departureDate company-name singleFare rdfs:range rdfs:range rdfs:range rdf:Type units:currencyQuantity rdf:Type rdf:Type rdf:Type time:Date RDF rdf:Property rdf:Type rdf:Type company-name rdf:Type “Iberia” arrivalDate IB-4321 singleFare departureDate 10/11/2005 500 euros 54
  • 55. Exercise •Objective • Get used to the different syntaxes of RDF(S) •Tasks • Take the text of an RDF(S) file and create its corresponding graph • Take an RDF(S) graph and create its corresponding RDF/XML and N3 files 55
  • 56. Exercise 2.a. Create a graph from a file • Open the files StickyNote.rdf and StickyNote.rdfs • Create the corresponding graph from them • Compare your graph with those of your colleagues 56
  • 59. Exercise 2.b. Create files from a graph • Transform the following graph into N3 syntax Room Object Measurement Person hasMeasurement includes Sensor029 hasTemperature atTime Class01 includes 29 2010-06-12T12:00:12 Computer101 hasOwner User10A hasName Pedro 59
  • 60. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 60
  • 63. RDF(S) limitations • RDFS too weak to describe resources in sufficient detail • No localised range and domain constraints • Can‟t say that the range of hasChild is person when applied to persons and elephant when applied to elephants • No existence/cardinality constraints • Can‟t say that all instances of person have a mother that is also a person, or that persons have exactly 2 parents • No boolean operators • Can‟t say or, not, etc. • No transitive, inverse or symmetrical properties • Can‟t say that isPartOf is a transitive property, that hasPart is the inverse of isPartOf or that touches is symmetrical • Difficult to provide reasoning support • No “native” reasoners for non-standard semantics • May be possible to reason via FOL axiomatisation 63
  • 64. Exercise •Objective • Understand the features of RDF(S) for implementing ontologies, including its limitations •Tasks • Given a scenario description, build a simple ontology in RDF Schema 64
  • 65. Exercise 3. Domain description • Un lugar puede ser un lugar de interés. • Los lugares de interés pueden ser lugares turísticos o establecimientos, pero no las dos cosas a la vez. • Los lugares turísticos pueden ser palacios, iglesias, ermitas y catedrales. • Los establecimientos pueden ser hoteles, hostales o albergues. • Un lugar está situado en una localidad, la cual a su vez puede ser una villa, un pueblo o una ciudad. • Un lugar de interés tiene una dirección postal que incluye su calle y su número. • Las localidades tienen un número de habitantes. • Las localidades se encuentran situadas en provincias. • Covarrubias es un pueblo con 634 habitantes de la provincia de Burgos. • El restaurante “El Galo” está situado en Covarrubias, en la calle Mayor, número 5. • Una de las iglesias de Covarrubias está en la calle de Santo Tomás. 65
  • 66. Exercise 3. Sample resulting ontology 66
  • 67. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 67
  • 68. Sample RDF APIs • RDF libraries for different languages: • Java, Python, C, C++, C#, .Net, Javascript, Tcl/Tk, PHP, Lisp, Obj-C, Prolog, Perl, Ruby, Haskell • List in http://esw.w3.org/topic/SemanticWebTools • Usually related to a RDF repository • Multilanguage: • Redland RDF Application Framework (C, Perl, PHP, Python and Ruby): http://www.redland.opensource.ac.uk/ • Java: • Jena: http://jena.sourceforge.net/ • Sesame: http://www.openrdf.org/ • PHP: • RAP - RDF API for PHP: http://www4.wiwiss.fu-berlin.de/bizer/rdfapi/ • Python: • RDFLib: http://rdflib.net/ • Pyrple: http://infomesh.net/pyrple/ 68
  • 69. Jena • Java framework for building Semantic Web applications • Open source software from HP Labs • The Jena framework includes: • A RDF API • An OWL API • Reading and writing RDF in RDF/XML, N3 and N-Triples • In-memory and persistent storage • A rule based inference engine • SPARQL query engine 69
  • 70. Sesame • A framework for storage, querying and inferencing of RDF and RDF Schema • A Java Library for handling RDF • A Database Server for (remote) access to repositories of RDF data • Highly expressive query and transformation languages • SeRQL, SPARQL • Various backends • Native Store • RDBMS (MySQL, Oracle 10, DB2, PostgreSQL) • main memory • Reasoning support • RDF Schema reasoner • OWL DLP (OWLIM) • domain reasoning (custom rule engine) 70
  • 71. Jena example. Graph creation http://.../JohnSmith vcard:FN vcard:N John Smith vcard:Given vcard:Family John Smith // some definitions String personURI = "http://somewhere/JohnSmith"; String givenName = "John"; String familyName = "Smith"; String fullName = givenName + " " + familyName; // create an empty Model Model model = ModelFactory.createDefaultModel(); // create the resource // and add the properties cascading style Resource johnSmith = model.createResource(personURI) .addProperty(VCARD.FN, fullName) .addProperty(VCARD.N, model.createResource() .addProperty(VCARD.Given, givenName) .addProperty(VCARD.Family, familyName)); 71
  • 72. Jena example. Read and write // create an empty model Model model = ModelFactory.createDefaultModel(); // use the FileManager to find the input file InputStream in = FileManager.get().open( inputFileName ); if (in == null) { throw new IllegalArgumentException("File not found"); } <rdf:RDF // read the RDF/XML file model.read(in, ""); xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#' xmlns:vcard='http://www.w3.org/2001/vcard-rdf/3.0#' // write it to standard out > model.write(System.out); <rdf:Description rdf:nodeID="A0"> <vcard:Family>Smith</vcard:Family> <vcard:Given>John</vcard:Given> </rdf:Description> <rdf:Description rdf:about='http://somewhere/JohnSmith/'> <vcard:FN>John Smith</vcard:FN> <vcard:N rdf:nodeID="A0"/> </rdf:Description> ... </rdf:RDF> 72
  • 73. Some RDF editors • IsaViz • http://www.w3.org/2001/11/IsaViz/ • Morla • http://www.morlardf.net/ • RDFAuthor • http://rdfweb.org/people/damian/RDFAuthor/ • RdfGravity • http://semweb.salzburgresearch.at/apps/rdf-gravity/ • Rhodonite • http://rhodonite.angelite.nl/ 73
  • 74. Main References • Brickley D, Guha RV (2004) RDF Vocabulary Description Language 1.0: RDF Schema. W3C Recommendation http://www.w3.org/TR/PR-rdf-schema/ • Lassila O, Swick R (1999) Resource Description Framework (RDF) Model and Syntax Specification. W3C Recommendation http://www.w3.org/TR/REC-rdf-syntax/ • RDF validator: http://www.w3.org/RDF/Validator/ • RDF resources: http://planetrdf.com/guide/ 74
  • 75. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 75
  • 76. RDF(S) query languages • Languages developed to allow accessing datasets expressed in RDF(S) (and in some cases OWL) Application Application SQL queries SPARQL, RQL, etc., queries Relational RDF(S) DB OWL • Supported by the most important language APIs • Jena (HP labs) • Sesame (Aduna) • Boca (IBM) • ... • There are some differences wrt. languages like SQL, such as • Combination of different sources • Trust management • Open World Assumption 76
  • 77. Query types • Selection and extraction • “Select all the essays, together with their authors and their authors‟ names” • “Select everything that is related to the book „Bellum Civille‟” • Reduction: we specify what it should not be returned • “Select everything except for the ontological information and the book translators” • Restructuring: the original structure is changed in the final result • “Invert the relationship „author‟ by „is author of‟” • Aggregation • “Return all the essays together with the mean number of authors per essay” • Combination and inferences • “Combine the information of a book called „La guerra civil‟ and whose author is Julius Caesar with the book whose identifier is „Bellum Civille‟” • “Select all the essays, together with its authors and author names”, including also the instances of the subclasses of Essay • “Obtain the relationship „coauthor‟ among persons who have written the same book” 77
  • 78. RDF(S) query language families • SquishQL Family Triple • RQL Family Description • SquishQL database • RQL graphs Query Query • SeRQL • rdfDB Query Language structure semantics • eRQL • RDQL • Controlled natural language • BRQL • Metalog • TriQL • Other • XPath, XSLT, XQuery XML • Algae • XQuery for RDF repository • iTQL Query • N3QL • XsRQL syntax • PerlRDF Query Language • TreeHugger and RDFTwig • RDEVICE Deductive • RDFT, Nexus Query Language Language • RDFQBE • RDFPath, Rpath and RXPath • RDFQL • Versa • TRIPLE SPARQL • WQL W3C Recommendation 15 January 2008 78
  • 79. SPARQL • SPARQL Protocol and RDF Query Language • Supported by: Jena, Sesame, IBM Boca, etc. • Features • It supports most of the aforementioned queries • It supports datatype reasoning (datatypes can be requested instead of actual values) • The domain vocabulary and the knowledge representation vocabulary are treated differently by the query interpreters • It allows making queries over properties with multiple values, over multiple properties of a resource and over reifications • Queries can contain optional statements • Some implementations support aggregation queries • Limitations • Neither set operations nor existential or universal quantifiers can be included in the queries • It does not support recursive queries 79
  • 80. SPARQL is also a protocol • SPARQL is a Query Language … Find names and websites of contributors to PlanetRDF: PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?website FROM <http://planetrdf.com/bloggers.rdf> WHERE { ?person foaf:weblog ?website . ?person foaf:name ?name . ?website a foaf:Document } • ... and a Protocol http://.../qps?query-lang=http://www.w3.org/TR/rdf-sparql-query/ &graph-id=http://planetrdf.com/bloggers.rdf&query=PREFIXfoaf: <http://xmlns.com/foaf/0.1/... • Services running SPARQL queries over a set of graphs • A transport protocol for invoking the service • Based on ideas from earlier protocol work such as Joseki • Describing the service with Web Service technologies 80
  • 81. SPARQL Endpoints • SPARQL protocol services • Enables users (human or other) to query a knowledge base using SPARQL • Results are typically returned in one or more machine-processable formats • List of SPARQL Endpoints • http://esw.w3.org/topic/SparqlEndpoints • Programmatic access using libraries: • ARC, RAP, Jena, Sesame, Javascript SPARQL, PySPARQL, etc. • Examples: Project Endpoint DBpedia http://dbpedia.org/sparql BBC Programmes and Music http://bbc.openlinksw.com/sparql/ data.gov http://semantic.data.gov/sparql data.gov.uk http://data.gov.uk/sparql Musicbrainz http://dbtune.org/musicbrainz/sparql 81
  • 82. A simple SPARQL query Data: @prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . :book1 dc:title "SPARQL Tutorial" . Query: SELECT ?title WHERE { <http://example.org/book/book1> <http://purl.org/dc/elements/1.1/title> ?title . } Query result: title "SPARQL Tutorial" • A pattern is matched against the RDF data • Each way a pattern can be matched yields a solution • The sequence of solutions is filtered by: Project, distinct, order, limit/offset • One of the result forms is applied: SELECT, CONSTRUCT, DESCRIBE, ASK 82
  • 83. Graph patterns • Basic Graph Patterns, where a set of triple patterns must match • Group Graph Pattern, where a set of graph patterns must all match • Optional Graph patterns, where additional patterns may extend the solution • Alternative Graph Pattern, where two or more possible patterns are tried • Patterns on Named Graphs, where patterns are matched against named graphs 83
  • 84. Multiple matches @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Johnny Lee Outlaw" . _:a foaf:mbox <mailto:jlow@example.com> . _:b foaf:name "Peter Goodguy" . _:b foaf:mbox <mailto:peter@example.org> . _:c foaf:mbox <mailto:carol@example.org> . PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?mbox WHERE { ?x foaf:name ?name . ?x foaf:mbox ?mbox } name mbox "Johnny Lee Outlaw" <mailto:jlow@example.com> "Peter Goodguy" <mailto:peter@example.org> 84
  • 85. Matching RDF literals @prefix dt: <http://example.org/datatype#> . @prefix ns: <http://example.org/ns#> . @prefix : <http://example.org/ns#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . :x ns:p "cat"@en . :y ns:p "42"^^xsd:integer . :z ns:p "abc"^^dt:specialDatatype . SELECT ?v WHERE { ?v ?p "cat" } v v SELECT ?v WHERE { ?v ?p "cat"@en } <http://example.org/ns#x> v SELECT ?v WHERE { ?v ?p 42 } <http://example.org/ns#y> SELECT ?v WHERE { ?v ?p "abc"^^<http://example.org/datatype#specialDatatype> } v <http://example.org/ns#z> 85
  • 86. Blank node labels in query results @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:b foaf:name "Bob" . PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?x ?name WHERE { ?x foaf:name ?name } x name x name _:c "Alice" = _:r "Alice" _:d "Bob" _:s "Bob" 86
  • 87. Group graph pattern PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?mbox WHERE { { ?x foaf:name ?name . } { ?x foaf:mbox ?mbox . } } SELECT ?x WHERE {} PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?mbox WHERE { { ?x foaf:name ?name . } { ?x foaf:mbox ?mbox . FILTER regex(?name, "Smith")} } 87
  • 88. Optional graph patterns @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . _:a rdf:type foaf:Person . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@example.com> . _:a foaf:mbox <mailto:alice@work.example> . _:b rdf:type foaf:Person . _:b foaf:name "Bob" . PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?mbox WHERE { ?x foaf:name ?name . OPTIONAL { ?x foaf:mbox ?mbox } } name mbox "Alice" <mailto:alice@example.com> "Alice" <mailto:alice@work.example> “Bob" 88
  • 89. Multiple optional graph patterns @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:homepage <http://work.example.org/alice/> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> . PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?mbox ?hpage WHERE { ?x foaf:name ?name . OPTIONAL { ?x foaf:mbox ?mbox } . OPTIONAL { ?x foaf:homepage ?hpage } } name mbox hpage "Alice" <http://work.example.org/alice/> “Bob" <mailto:bob@work.example> 89
  • 90. Alternative graph patterns @prefix dc10: <http://purl.org/dc/elements/1.0/> . @prefix dc11: <http://purl.org/dc/elements/1.1/> . _:a dc10:title "SPARQL Query Language Tutorial" . _:a dc10:creator "Alice" . _:b dc11:title "SPARQL Protocol Tutorial" . _:b dc11:creator "Bob" . _:c dc10:title "SPARQL" . _:c dc11:title "SPARQL (updated)" . PREFIX dc10: <http://purl.org/dc/elements/1.0/> title PREFIX dc11: <http://purl.org/dc/elements/1.1/> "SPARQL Protocol Tutorial" SELECT ?title "SPARQL" WHERE { { ?book dc10:title ?title } UNION { ?book dc11:title ?title } } "SPARQL (updated)" "SPARQL Query Language Tutorial" SELECT ?x ?y x y WHERE { { ?book dc10:title ?x } UNION "SPARQL (updated)" { ?book dc11:title ?y } } "SPARQL Protocol Tutorial" "SPARQL" "SPARQL Query Language Tutorial" SELECT ?title ?author WHERE author title { { ?book dc10:title ?title . ?book dc10:creator ?author } "Alice" "SPARQL Protocol Tutorial" UNION { ?book dc11:title ?title . ?book dc11:creator ?author }} “Bob” "SPARQL Query Language Tutorial" 90
  • 91. Patterns on named graphs # Named graph: http://example.org/foaf/aliceFoaf @prefix foaf:<http://.../foaf/0.1/> . @prefix rdf:<http://.../1999/02/22-rdf-syntax-ns#> . @prefix rdfs:<http://.../2000/01/rdf-schema#> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@work.example> . _:a foaf:knows _:b . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> . _:b foaf:nick "Bobby" . _:b rdfs:seeAlso <http://example.org/foaf/bobFoaf> . <http://example.org/foaf/bobFoaf> rdf:type foaf:PersonalProfileDocument . # Named graph: http://example.org/foaf/bobFoaf @prefix foaf:<http://.../foaf/0.1/> . @prefix rdf:<http://.../1999/02/22-rdf-syntax-ns#> . @prefix rdfs:<http://.../2000/01/rdf-schema#> . _:z foaf:mbox <mailto:bob@work.example> . _:z rdfs:seeAlso <http://example.org/foaf/bobFoaf> . _:z foaf:nick "Robert" . <http://example.org/foaf/bobFoaf> rdf:type foaf:PersonalProfileDocument . 91
  • 92. Patterns on named graphs II PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?src ?bobNick FROM NAMED <http://example.org/foaf/aliceFoaf> src bobNick FROM NAMED <http://example.org/foaf/bobFoaf> <http://example.org/foaf/aliceFoaf> "Bobby" WHERE { <http://example.org/foaf/bobFoaf> "Robert" GRAPH ?src { ?x foaf:mbox <mailto:bob@work.example> . ?x foaf:nick ?bobNick } } PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX data: <http://example.org/foaf/> SELECT ?nick FROM NAMED <http://example.org/foaf/aliceFoaf> nick FROM NAMED <http://example.org/foaf/bobFoaf> WHERE "Robert" { GRAPH data:bobFoaf { ?x foaf:mbox <mailto:bob@work.example> . ?x foaf:nick ?nick } } 92
  • 93. Restricting values @prefix dc: <http://purl.org/dc/elements/1.1/> . @prefix : <http://example.org/book/> . @prefix ns: <http://example.org/ns#> . :book1 dc:title "SPARQL Tutorial" . :book1 ns:price 42 . :book2 dc:title "The Semantic Web" . :book2 ns:price 23 . PREFIX dc: <http://purl.org/dc/elements/1.1/> SELECT ?title title WHERE { ?x dc:title ?title FILTER regex(?title, "^SPARQL") "SPARQL Tutorial" } PREFIX dc: <http://purl.org/dc/elements/1.1/> SELECT ?title title WHERE { ?x dc:title ?title FILTER regex(?title, "web", "i" ) "The Semantic Web" } PREFIX dc: <http://purl.org/dc/elements/1.1/> PREFIX ns: <http://example.org/ns#> title price SELECT ?title ?price WHERE { ?x ns:price ?price . "The Semantic Web" 23 FILTER (?price < 30.5) ?x dc:title ?title . } 93
  • 94. Value tests • Based on XQuery 1.0 and XPath 2.0 Function and Operators • XSD boolean, string, integer, decimal, float, double, dateTime • Notation <, >, =, <=, >= and != for value comparison Apply to any type • BOUND, isURI, isBLANK, isLITERAL • REGEX, LANG, DATATYPE, STR (lexical form) • Function call for casting and extensions functions 94
  • 95. Solution sequences and modifiers • Order modifier: put the solutions in SELECT ?name order WHERE { ?x foaf:name ?name ; :empId ?emp } ORDER BY ?name DESC(?emp) • Projection modifier: choose certain SELECT ?name variables WHERE { ?x foaf:name ?name } • Distinct modifier: ensure solutions in the sequence are unique SELECT DISTINCT ?name WHERE { ?x foaf:name ?name } • Reduced modifier: permit elimination of some non-unique SELECT REDUCED ?name solutions WHERE { ?x foaf:name ?name } • Limit modifier: restrict the number of solutions SELECT ?name WHERE { ?x foaf:name ?name } LIMIT 20 • Offset modifier: control where the solutions start from in the overall SELECT ?name WHERE { ?x foaf:name ?name } sequence of solutions ORDER BY ?name LIMIT 5 OFFSET 10 95
  • 96. SPARQL query forms • SELECT • Returns all, or a subset of, the variables bound in a query pattern match • CONSTRUCT • Returns an RDF graph constructed by substituting variables in a set of triple templates • ASK • Returns a boolean indicating whether a query pattern matches or not • DESCRIBE • Returns an RDF graph that describes the resources found 96
  • 97. SPARQL query forms: SELECT @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:knows _:b . _:a foaf:knows _:c . _:b foaf:name "Bob" . _:c foaf:name "Clare" . _:c foaf:nick "CT" . PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?nameX ?nameY ?nickY WHERE { ?x foaf:knows ?y ; foaf:name ?nameX . ?y foaf:name ?nameY . OPTIONAL { ?y foaf:nick ?nickY } } nameX nameY nickY "Alice" "Bob" "Alice" "Clare" "CT" 97
  • 98. SPARQL query forms: CONSTRUCT @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:mbox <mailto:alice@example.org> . PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX vcard: <http://www.w3.org/2001/vcard-rdf/3.0#> CONSTRUCT { <http://example.org/person#Alice> vcard:FN ?name } WHERE { ?x foaf:name ?name } Query result: @prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0#> . <http://example.org/person#Alice> vcard:FN "Alice" . 98
  • 99. SPARQL query forms: ASK @prefix foaf: <http://xmlns.com/foaf/0.1/> . _:a foaf:name "Alice" . _:a foaf:homepage <http://work.example.org/alice/> . _:b foaf:name "Bob" . _:b foaf:mbox <mailto:bob@work.example> . PREFIX foaf: <http://xmlns.com/foaf/0.1/> ASK { ?x foaf:name "Alice" } Query result: yes 99
  • 100. SPARQL query forms: DESCRIBE PREFIX ent: <http://org.example.com/employees#> DESCRIBE ?x WHERE { ?x ent:employeeId "1234" } Query result: @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix vcard: <http://www.w3.org/2001/vcard-rdf/3.0> . @prefix exOrg: <http://org.example.com/employees#> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix owl: <http://www.w3.org/2002/07/owl#> _:a exOrg:employeeId "1234" ; foaf:mbox_sha1sum "ABCD1234" ; vcard:N [ vcard:Family "Smith" ; vcard:Given "John" ] . foaf:mbox_sha1sum rdf:type owl:InverseFunctionalProperty . 100
  • 101. Main References • Prud‟hommeaux E, Seaborne A (2008) SPARQL Query Language for RDF. W3C Recommendation http://www.w3.org/TR/rdf-sparql-query/ • SPARQL validator: http://www.sparql.org/validator.html • SPARQL implementations: http://esw.w3.org/topic/SparqlImplementations • SPARQL Endpoints http://esw.w3.org/topic/SparqlEndpoints • SPARQL in Dbpedia http://dbpedia.org/sparql 101
  • 102. Index • Resource Description Framework (RDF) • RDF primitives • Reasoning with RDF • RDF Schema • RDF Schema primitives • Reasoning with RDFS • RDF(S) Management APIs • SPARQL • OWL 102
  • 103. OWL Basics (on top of RDF and RDFS) • Set of constructors for concept expressions • Booleans: and/or/not • A Session is a TheoreticalSession or a HandsonSession • Slides are not the same as Code • Quantification: some/all • Sessions must have some EducationalMaterial • Sessions can only have Presenters that have developed Grid applications or Grid middleware • Axioms for expressing constraints • Necessary and Sufficient conditions on classes • A Session that hasEducationalMaterial Code is a HandsonSession. • Disjointness • TheoreticalSessions are disjoint with HandsonSessions • Property characteristics: transitivity, inverse
  • 104. OWL Ontology Example. BioPAX ontology • http://www.biopax.org/release/biopax-level2.owl
  • 105. Description Logics • A family of logic based Knowledge Representation formalisms • Descendants of semantic networks and KL-ONE • Describe domain in terms of concepts (classes), roles (relationships) and individuals • Specific languages characterised by the constructors and axioms used to assert knowledge about classes, roles and individuals. • Example: ALC (the least expressive language in DL that is propositionally closed) • Constructors: boolean (and, or, not) • Role restrictions • Distinguished by: • Model theoretic semantics • Decidable fragments of FOL • Closely related to Propositional Modal & Dynamic Logics • Provision of inference services • Sound and complete decision procedures for key problems • Implemented systems (highly optimised)
  • 106. Structure of DL Ontologies • A DL ontology can be divided into two parts: • Tbox (Terminological KB): a set of axioms that describe the structure of a domain : • Doctor Person • Person Man Woman • HappyFather Man hasDescendant.(Doctor hasDescendant.Doctor) • Abox (Assertional KB): a set of axioms that describe a specific situation : • John HappyFather • hasDescendant (John, Mary)
  • 107. Most common constructors in class definitions • Intersection: C1 ... Cn Human Male • Union: C1 ... Cn Doctor Lawyer • Negation: C Male • Nominals: {x1} ... {xn} {john} ... {mary} • Universal restriction: P.C hasChild.Doctor • Existential restriction: P.C hasChild.Lawyer • Maximum cardinality: nP.C 3hasChild.Doctor • Minimum cardinality: nP.C 1hasChild.Male • Specific Value: P.{x} hasColleague.{Matthew} • Nesting of constructors can be arbitrarily complex • Person hasChild.(Doctor hasChild.Doctor) • Lots of redundancy • A B is equivalent to ( A B) • P.C is equivalent to P. C
  • 108. OWL (1.0 and 1.1) February 2004 Web Ontology Language Built on top of RDF(S) Three layers: - OWL Lite - A small subset of primitives - Easier for frame-based tools to transition to - OWL DL - Description logic - Decidable reasoning - OWL Full - RDF extension, allows metaclasses Several syntaxes: - Abstract syntax - Manchester syntax - RDF/XML
  • 109. OWL 2 (I). New features • October 2009 • New features • Syntactic sugar • Disjoint union of classes • New expressivity • Keys • Property chains • Richer datatypes, data ranges • Qualified cardinality restrictions • Asymmetric, reflexive, and disjoint properties • Enhanced annotation capabilities • New syntax • OWL2 Manchester syntax
  • 110. OWL 2 (II). Three new profiles • OWL2 EL • Ontologies that define very large numbers of classes and/or properties, • Ontology consistency, class expression subsumption, and instance checking can be decided in polynomial time. • OWL2 QL • Sound and complete query answering is in LOGSPACE (more precisely, in AC0) with respect to the size of the data (assertions), • Provides many of the main features necessary to express conceptual models (UML class diagrams and ER diagrams). • It contains the intersection of RDFS and OWL 2 DL. • OWL2 RL • Inspired by Description Logic Programs and pD*. • Syntactic subset of OWL 2 which is amenable to implementation using rule- based technologies, and presenting a partial axiomatization of the OWL 2 RDF-Based Semantics in the form of first-order implications that can be used as the basis for such an implementation. • Scalable reasoning without sacrificing too much expressive power. • Designed for • OWL applications trading the full expressivity of the language for efficiency, • RDF(S) applications that need some added expressivity from OWL 2.
  • 111. OWL: Most common constructors Intersection: C1 ... Cn intersectionOf Human Male Union: C1 ... Cn unionOf Doctor Lawyer Negation: C complementOf Male Nominals: {x1} ... {xn} oneOf {john} ... {mary} Universal restriction: P.C allValuesFrom hasChild.Doctor Existential restriction: P.C someValuesFrom hasChild.Lawyer Maximum cardinality: nP[.C] maxCardinality (qualified or not) 3hasChild[.Doctor] Minimum cardinality: nP[.C] minCardinality (qualified or not) 1hasChild[.Male] Exact cardinality: =nP[.C] exactCardinality (qualified or not) =1hasMother[.Female] Specific Value: P.{x} hasValue hasColleague.{Matthew} Local reflexivity: -- hasSelf Narcisist Person hasSelf(loves) Keys -- hasKey hasKey(Person, passportNumber, country) Subclass C1 C2 subClassOf Human Animal Biped Equivalence C1 C2 equivalentClass Man Human Male Disjointness C1 C2 disjointWith, AllDisjointClasses Male Female DisjointUnion C C1 ... Cn and Ci Cj forall i≠j disjointUnionOf Person DisjointUnionOf (Man, Woman) Metaclasses and annotations on axioms are also valid in OWL2, and declarations of classes have to provided. Full list available in reference specs and in the Quick Reference Guide: http://www.w3.org/2007/OWL/refcard
  • 112. OWL: Most common constructors Subproperty P1 P2 subPropertyOf hasDaughter hasChild Equivalence P1 P2 equivalentProperty cost price DisjointProperties P1 ... Pn disjointObjectProperties hasDaughter hasSon Inverse P1 P2- inverseOf hasChild hasParent- Transitive P+ P TransitiveProperty ancestor+ ancestor Functional 1P FunctionalProperty T 1hasMother InverseFunctional 1P- InverseFunctionalProperty T 1hasPassportID- Reflexive ReflexiveProperty Irreflexive IrreflexiveProperty Asymmetric AsymmetricProperty Property chains P P1 o ... o Pn propertyChainAxiom hasUncle hasFather o hasBroth Equivalence {x1} {x2} sameIndividualAs {oeg:OscarCorcho} {img:Oscar} Different {x1} {x2} differentFrom, AllDifferent {john} {peter} NegativePropertyAssertion NegativeDataPropertyAssertion {hasAge john 35} NegativeObjectPropertyAssertion {hasChild john peter} Besides, top and bottom object and datatype properties exist
  • 113. Basic Inference Tasks • Subsumption – check knowledge is correct (captures intuitions) • Does C subsume D w.r.t. ontology O? (in every model I of O, CI DI ) • Equivalence – check knowledge is minimally redundant (no unintended synonyms) • Is C equivalent to D w.r.t. O? (in every model I of O, CI = DI ) • Consistency – check knowledge is meaningful (classes can have instances) • Is C satisfiable w.r.t. O? (there exists some model I of O s.t. CI ) • Instantiation and querying • Is x an instance of C w.r.t. O? (in every model I of O, xI CI ) • Is (x,y) an instance of R w.r.t. O? (in every model I of O, (xI,yI) RI ) • All reducible to KB satisfiability or concept satisfiability w.r.t. a KB • Can be decided using highly optimised tableaux reasoners
  • 115. Main References W3C OWL Working Group (2009) OWL2 Web Ontology Language Document Overview. http://www.w3.org/TR/2009/REC-owl2-overview-20091027/ Dean M, Schreiber G (2004) OWL Web Ontology Language Reference. W3C Recommendation. http://www.w3.org/TR/owl-ref/ Gómez-Pérez, A.; Fernández-López, M.; Corcho, O. Ontological Engineering. Springer Verlag. 2003 Capítulo 4: Ontology languages Baader F, McGuinness D, Nardi D, Patel-Schneider P (2003) The Description Logic Handbook: Theory, implementation and applications. Cambridge University Press, Cambridge, United Kingdom Jena web site: http://jena.sourceforge.net/ Jena API: http://jena.sourceforge.net/tutorial/RDF_API/ Jena tutorials: http://www.ibm.com/developerworks/xml/library/j-jena/index.html http://www.xml.com/pub/a/2001/05/23/jena.html Pellet: http://clarkparsia.com/pellet RACER: http://www.racer-systems.com/ FaCT++: http://owl.man.ac.uk/factplusplus/ HermIT: http://hermit-reasoner.com/
  • 116. Ontology Languages • A large amount of work on Semantic Web has concentrated on the definition of a collection or “stack” of languages. • Used to support the representation and use of metadata • Basic machinery that we can use to represent the extra semantic information needed for the Semantic Web SWRL Inference OWL Integration Integration RDFS RDF(S) Annotation RDF Reasoning over the information we have Could be light-weight (taxonomy) XML Could be heavy-weight (logic-style) Integrating information sources Associating metadata to resources (bindings)
  • 117. The evolution of the Semantic Web pre-Semantic Web Semantic Web 1.0 Semantic Web 3.0 Semantic Web Challenge 2004 2008 No standardised formats RDFS, OWL • Cooperation Dynamicity e.g., (KA)2 • Decentralised change • Heterogeneity Multimedia
  • 118. [Semantic | Web]+ Applications (I) • No definition in Wikipedia… ;-( • Why [Semantic | Web]+ application?
  • 119. [Semantic | Web]+ Applications (II) • Why [Semantic | Web]+ application? • Most of them are focused on the use of semantics • In fact, probably it would be better to use Semantic [Web]* application • However, many of them are not so Web-oriented • E.g., very common in data integration approaches • http://www.readwriteweb.com/archives/10_semantic_ apps_to_watch.php • A key element [of a Semantic Web App] is that the apps all try to determine the meaning of text and other data, and then create connections for users. Besides, data portability and connectibility are keys to these new semantic apps - i.e. using the Web as platform.
  • 120. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 121. What is the Web of Linked Data? • An extension of the current Web… • … where informationdata services and are given well-defined and explicitly represented meaning, … • … so that it can be shared and used by humans and machines, ... • ... better enabling them to work in cooperation • How? • Promoting information exchange by tagging web content with machine processable descriptions of its meaning. • And technologies and infrastructure to do this • And clear principles on how to publish data
  • 122. What is a Linked Data application • Again, no definition yet • Linked Data is a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF. • So every element from the definition of SW application applies
  • 123. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 126. Ontologies Metadata <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> The web
  • 127. The Web of Data
  • 128. The Web of Data
  • 129. Ontologies Alignments <RDF triple> <RDF triple> <RDF triple> Onto. - Schema <RDF triple> <RDF triple> <RDF triple> Metadata Data Sources <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> Resources
  • 130. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 131. Annotation-focused applications: key characteristics • Available at all stages (pre-Semantic Web, SW1.0 and SW3.0), although predominantly in the early ones • Single (usually small) ontologies, many of them built manually • Centralised ontologies • Instances stored in a centralised manner, together with the ontologies, or in separate files/DBs • Low heterogeneity and relatively small scale • Homogeneous quality in data
  • 132. Annotation in the pre-Semantic Web • (KA)2
  • 133. Semantic Web Portals Semantic Driven Permission-based User Oriented Portal Administrators Ontologies and Software O2 O1 Oi Oj Extranet Users Agents External resources
  • 136. Semantic-based Visualisation Workpackage has associated Deliverable is generated by has Q.A. partner Organization
  • 137. Extranet View (RDF lives behind)
  • 138. Overview • Coming to terms: The Web (1.0 and 2.0), the Semantic Web, the Web of Linked Data and all its applications • The Web (1.0 and 2.0) • Web applications • The Semantic Web (pre-SemanticWeb, SW1.0 and SW3.0) • Semantic Web Applications Or [Semantic | Web]+ Applications • The Web of Linked Data • Linked Data Applications • Semantic-based Applications • preSemanticWeb Applications • Annotation • Semantic Web 1.0 Applications • Annotation, Data Integration and Decision Support Systems • Semantic Web 3.0 Applications • (Collaborative) Annotation and Data Integration • Conclusions and Trends
  • 139. Data integration applications: key characteristics • Available at later stages (SW1.0 and SW3.0). • Still single (usually small) ontologies, many of them built manually • Although sometimes mappings between local and global ontologies • Still centralised ontologies • Instances live in distributed DBs, with a focus on run- time queries, although also data warehousing approach • Medium heterogeneity and medium scale • Heterogeneous quality in data
  • 140. Migrating IGN (Instituto Geográfico Nacional) sources 140
  • 141. IGN Catalogue Integration: Exploitation of Mappings Cated. Query: NGN NC ¿Edif. Religioso de Soria? Construcción Rel. Soria BCN200 BCN25 Cated. Edif. Religioso NS Nieves Catedral Cated. Response: Ig. Sto. Ermita Catedral Soria Ig. Sto. Tomás Catedral Soria Soria Ermita N.S. Nieves Soria Catedral Soria
  • 143. Alignments between ontologies and the DB Land Fishing Biological Fisheries Vessel types Gear areas areas entities commodities and size types R2O R2O R2O R2O R2O R2O Document Document Document Document Document Document FAO FIGIS DB http://www.fao.org/aims/aos/fi/