Introduction to Linked Data
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Basic introductory talk about the Web of Linked Data, given to undergraduate and posgraduate students of Universidad del Valle (Cali, Colombia) in September 2010. Knowledge about Semantic Web is ...

Basic introductory talk about the Web of Linked Data, given to undergraduate and posgraduate students of Universidad del Valle (Cali, Colombia) in September 2010. Knowledge about Semantic Web is required

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Introduction to Linked Data Introduction to Linked Data Presentation Transcript

  • IntroductiontoLinked Data
    Oscar Corcho, Asunción Gómez Pérez ({ocorcho, asun}@fi.upm.es)
    Universidad Politécnica de Madrid
    Universidad del Valle, Cali, ColombiaSeptember 10th 2010
    Credits: Raúl García Castro, Oscar Muñoz, Jose Angel Ramos Gargantilla, María del Carmen Suárez de Figueroa, Boris Villazón, Alex de León, Víctor Saquicela, Luis Vilches, Miguel Angel García, Manuel Salvadores, Guillermo Alvaro, Juan Sequeda, Carlos Ruiz Moreno and manyothers
    WorkdistributedunderthelicenseCreativeCommonsAttribution-Noncommercial-Share Alike 3.0
  • Contents
    IntroductiontoLinked Data
    Linked Data publication
    MethodologicalguidelinesforLinked Data publication
    RDB2RDF tools
    Technicalaspects of Linked Data publication
    Linked Data consumption
    2
  • Whatisthe Web of Linked Data?
    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 machineprocessable descriptions of its meaning.
    And technologies and infrastructure to do this
    And clear principles on how to publish data
    data
  • What is Linked Data?
    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.
    Part of the Semantic Web
    Exposing, sharing and connecting data
    Technologies: URIs and RDF (although others are also important)
  • The fourprinciples (Tim Berners Lee, 2006)
    Use URIs as names for things
    Use HTTP URIs so that people can look up those names.
    When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)
    Include links to other URIs, so that they can discover more things.
    http://www.w3.org/DesignIssues/LinkedData.html
    5
    http://www.ted.com/talks/tim_berners_lee_on_the_next_web.html
  • Linked Open Data evolution
    • 2007
    • 2008
    • 2009
  • 7
    LOD Cloud May 2007
    Facts:
    • Focal points:
    • DBPedia: RDFizedvesion of Wikipiedia; many ingoing and outgoing links
    • Music-related datasets
    • Big datasets include FOAF, US Census data
    • Size approx. 1 billion triples, 250k links
    Figure from [4]
  • 8
    LOD Cloud September 2008
    Facts:
    • More than 35 datasets interlinked
    • Commercial players joined the cloud, e.g., BBC
    • Companies began to publish and host dataset, e.g. OpenLink, Talis, or Garlik.
    • Size approx. 2 billion triples, 3 million links
    Figure from [4]
  • 9
    LOD Cloud March 2009
    Facts:
    • Big part from Linking Open Drug cloud and the BIO2RDF project (bottom)
    • Notable new datasets: Freebase, OpenCalais, ACM/IEEE
    • Size > 10 billion triples
    Figure from [4]
  • LOD clouds
  • WhyLinked Data?
    Basically, tomovefrom a Web of documentsto a Web of Data
    Let’s try anexample:
    • Tell me whichfootballplayers, born in theprovince of Albacete, in Spain, havescored a goal in theWorld Cup final
    Disclaimer:
    Sorryto use anexampleaboutfootball, butyouhavetounderstandthatforseveralyearsSpaniardswillbetalkingaboutfootball a lot ;-)
    Example courtesy of Guillermo Alvaro Rey
  • Informationsearch in the Web of documents
    • ¿?
    Example courtesy of Guillermo Alvaro Rey
  • What we were actually looking for
    Example courtesy of Guillermo Alvaro Rey
  • Itwouldbebettertomake a data query…
    (footballplayersfrom Albacete whoplayedEurocup 2008)
    Example courtesy of Guillermo Alvaro Rey
  • Howshouldwepublish data?
    Formats in which data ispublishednowadays…
    XML
    HTML
    DBs
    APIs
    CSV
    XLS

    However, mainlimitationsfrom a Web of Data point of view
    Difficulttointegrate
    Data isnotlinkedtoeachother, as ithappenswith Web documents.
  • Which format do we use then?
    RDF (ResourceDescription Framework)
    Data model
    Basedon triples: subject, predicate, object
    <Oscar> <vive en> <Madrid>
    <Madrid> <es la capital de> <España>
    <España> <es campeona de> <Mundial de Fútbol>

    Serialised in differentformats
    RDF/XML, RDFa, N3, Turtle, JSON…
  • URIs (Universal-UniformResourceIdentifer)
    Two types of identifiers can be used to identify Linked Data resources
    URIRefs(Unique Resource IdentifiersReferences)
    A URI and an optional FragmentIdentifier separated from the URI by the hash symbol ‘#’
    http://www.ontology.org/people#Person
    people:Person
    Plain URIs can also be used, as in FOAF:
    http://xmlns.com/foaf/0.1/Person
    17
  • How do wepublishLinked Data?
    ExposingRelationalDatabasesorother similar formatsintoLinked Data
    D2R
    Triplify
    R2O
    NOR2O
    Virtuoso
    Ultrawrap

    Usingnative RDF triplestores
    Sesame
    Jena
    Owlim
    Talisplatform

    Incorporatingit in theform of RDFa in CMSslikeDrupal
    18
  • How do we consume Linked Data?
    Linked Data browsers
    To explore things and datasets and to navigate between them.
    Tabulator Browser (MIT, USA), Marbles (FU Berlin, DE), OpenLink RDF Browser (OpenLink, UK), Zitgist RDF Browser (Zitgist, USA), Disco Hyperdata Browser (FU Berlin, DE), Fenfire (DERI, Ireland)
    Linked Data mashups
    Sites that mash up (thus combine Linked data)
    Revyu.com (KMI, UK), DBtune Slashfacet (Queen Mary, UK), DBPedia Mobile (FU Berlin, DE), Semantic Web Pipes (DERI, Ireland)
    Search engines
    To search for Linked Data.
    Falcons (IWS, China), Sindice (DERI, Ireland), MicroSearch (Yahoo, Spain), Watson (Open University, UK), SWSE (DERI, Ireland), Swoogle (UMBC, USA)
    Listing on this slide by T. Heath, M. Hausenblas, C. Bizer, R. Cyganiak, O. Hartig
    19
  • Linked Data browsers (Disco)
  • Linked Data Mashup (LinkedGeoData)
    © Migración de datos a la Web de los Datos - Enfoques, técnicas y herramientas
    Luis Manuel Vilches Blázquez
  • Linked Data Mashup (DBpedia Mobile)
    http://wiki.dbpedia.org/DBpediaMobile
    © Migración de datos a la Web de los Datos - Enfoques, técnicas y herramientas
    Luis Manuel Vilches Blázquez
  • Linked Data Search Engines (Sindice and SIG.MA)
    Entity lookup service. Find a document that mentions a URI or a keyword.
  • Linked Data SearchEngines (NYT)
    The New York Times: Alumni In The News
    http://data.nytimes.com/schools/schools.html
  • Linked Data SearchEngines (NYT)
    The New York Times: Source code is available
    … and is based on SPARQL queries
  • Oneadditionalmotivation: Open Government
    Government and state administration should be opened at all levels to effective public scrutiny and oversight
    Objectives:
    Transparency
    Participation
    Collaboration
    Inclusion
    Cost reduction
    Interoperability
    Reusability
    Leadership
    Market & Value
    26
    • Some Links:
    • B. Obama –Transparency and Open Government
    • T. Berners-Lee - Raw data now!
    • J. Manuel Alonso - ¿Qué es Open Data?
    • Open Government Data
    • 8 Principles of Open Government Data
  • Open Government. USA and UK
    27
    BOTTOM-UP
    Top-down
  • Linked Data Mashup (data.gov)
    Clean Air Status and Trends (CASTNET)
    http://data-gov.tw.rpi.edu/demo/exhibit/demo-8-castnet.php
  • Linked Data in the UK
    Education
    http://education.data.gov.uk/id/school/106661
    Parliament
    http://parliament.psi.enakting.org/id/member/1227
    Maps
    E.g., London: http://data.ordnancesurvey.co.uk/id/7000000000041428
    http://map.psi.enakting.org
    Transport
    http://www.dft.gov.uk/naptan/
    SameAs service
    http://www.sameas.org
    Challenges
    http://gov.tso.co.uk/openup/sparql/gov-transport
    29
  • Linked Data Mashup (data.gov.uk)
    Research Funding Explorer
    http://bis.clients.talis.com/
  • Open GovernmentSpain. Euskadi
    31
  • Open GovernmentSpain. Abredatos
    32
  • Open GovernmentSpain. Zaragoza
    33
  • Open GovernmentSpain. Asturias
    34
  • Linked Data Mashup (Waterquality)
    Water quality in Asturias’ beaches
    http://datos.fundacionctic.org/sandbox/asturias/playas/
  • Contents
    IntroductiontoLinked Data
    Linked Data publication
    MethodologicalguidelinesforLinked Data publication
    RDB2RDF tools
    Technicalaspects of Linked Data publication
    Linked Data consumption
    36
  • GeoLinkedData
    It is an open initiative whose aim is to enrich the Web of Data with Spanish geospatial data.
    This initiative has started off by publishing diverse information sources, such as National Geographic Institute of Spain (IGN-E) and National Statistics Institute (INE)
    http://geo.linkeddata.es
  • Motivation
    99.171 % English
    0.019 % Spanish
    The Web of Data ismainlyfor
    Englishspeakers
    Poorpresence of Spanish
    Source:Billion Triples dataset at http://km.aifb.kit.edu/projects/btc-2010/
    Thanks to Aidan and Richard
  • Related Work
  • Impact of Geo.linkeddata.es
    Number of triples in Spanish (July 2010): 1.412.248
    Number of triples in Spanish (EndAugust 2010): 21.463.088
    40
    Asunción Gómez Pérez
  • Processfor Publishing Linked Data onthe Web
    Identification
    of the data sources
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • 1. Identification and selection of the data sources
    Identification
    of the data sources
    Instituto GeográficoNacional
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Instituto Nacionalde Estadística
    Enable effective
    discovery
  • 1. Identification and selection of the data sources
    Instituto Geográfico Nacional (GeographicSpanishInstitute)
    Multilingual (Spanish, Vasc, Gallician, Catalan)
    Conceptualizationmistmatches
    Granularity (scale concept)
    Textual information
    Particularaties
    Longitude
    latitude
    • Instituto Nacional de Estadística (StatisticSpanishInstitute)
    • Monolingual
    • Numericalinformation
    • Particularaties
    Geo (textual level)
    Temporal
    43
    Asunción Gómez Pérez
  • 1. Identification and selection of the data sources
    IGN-E
  • 1. Identification and selection of the data sources
    IndustryProductionIndex
    Year
    Province
  • 2. Vocabulary development
    http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/#whichvocabs
    Identification
    of the data sources
    Vocabulary
    development
    Generation
    of the RDF Data
    Thisisnotenough
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • 2. Vocabularydevelopment
    Features
    Lightweight :
    Taxonomies and a fewproperties
    Consensuatedvocabularies
    Toavoidthemappingproblems
    Multilingual
    Linked data are multilingual
    TheNeOnmethodology can helpto
    Re-enginer Non ontologicalresourcesintoontologies
    Pros: use domainterminologyalreadyconsensuatedbydomainexperts
    Withdraw in heavyweightontologiesthosefeaturesthatyoudon’tneed
    Reuseexistingvocabularies
    47
    Identification
    of the data sources
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
    Asunción Gómez Pérez
  • Knowledge Resources
    Ontological Resources
    O. Design Patterns
    3
    4
    O. Repositories and Registries
    5
    6
    Flogic
    RDF(S)
    OWL
    OntologicalResource
    Reuse
    O. Aligning
    O. Merging
    5
    6
    2
    Ontology Design
    Pattern Reuse
    Non Ontological Resource
    Reuse
    4
    3
    6
    Non Ontological Resources
    2
    Ontological Resource
    Reengineering
    7
    Glossaries
    Dictionaries
    Lexicons
    5
    Non Ontological Resource
    Reengineering
    4
    6
    Classification
    Schemas
    Thesauri
    Taxonomies
    Alignments
    2
    RDF(S)
    1
    Flogic
    O. Conceptualization
    O. Implementation
    O. Formalization
    O. Specification
    Scheduling
    OWL
    8
    Ontology Restructuring
    (Pruning, Extension,
    Specialization, Modularization)
    9
    O. Localization
    1,2,3,4,5,6,7,8, 9
    Ontology Support Activities: Knowledge Acquisition (Elicitation); Documentation;
    Configuration Management; Evaluation (V&V); Assessment
    48
  • Vocabularydevelopment: Specification
    Content requirements: Identifythe set of questionsthattheontologyshouldanswer
    Whichone are theprovinces in Spain?
    Where are thebeaches?
    Where are thereservoirs?
    Identifytheproductionindex in Madrid
    Whichoneisthecitywithhigherproductionindex?
    Give me Madrid latitude and altitude
    ….
    Non-contentrequirements
    Theontologymustbe in thefourofficialSpanishlanguages
    49
    Asunción Gómez Pérez
  • 2. Lightweight Ontology Development
    WGS84 Geo Positioning: an RDF vocabulary
    scv:Dimension
    scv:Item
    scv:Dataset
    hydrographical phenomena (rivers, lakes, etc.)
    Vocabulary for instants, intervals, durations, etc.
    Names and international code systems for territories and groups
    Ontology for OGC Geography Markup Language
    reused
    Following the INSPIRE
    (INfrastructure for SPatial InfoRmation in Europe) recommendation.
    hydrOntology,SCOVO, FAO Geopolitcal, WGS84, GML, and Time
  • Objetivos:
    INSPIRE intenta conseguir fuentes armonizadas de Información Geográfica para dar soporte a la formulación, implementación y evaluación de políticas comunitarias (Medio Ambiente, etc).
    Fuentes de Información Geográfica: Bases de datos de los Estados Miembros (UE) a nivel local, regional, nacional e internacional.
    Contexto – Directiva INSPIRE
    Luis Manuel Vilches Blázquez
  • INSPIRE - Anexos
    Luis Manuel Vilches Blázquez
  • hydrOntology
    Existencia de gran diversidad de problemas (múltiples fuentes, heterogeneidad de contenido y estructuración, ambigüedad del lenguaje natural, etc.) en la información geográfica.
    Necesidad de un modelo compartido para solventar los problemas de armonización y estructuración de la información hidrográfica.
    hydrOntology es una ontología global de dominio desarrollada conforme a un acercamiento top-down.
    Recubrir la mayoría de los fenómenos representables cartográficamente asociados al dominio hidrográfico.
    Servir como marco de armonización entre los diferentes productores de información geo-espacial en el entorno nacional e internacional.
    Comenzar con los pasos necesarios para obtener una mejor organización y gestión de la información geográfica (hidrográfica).
    Luis Manuel Vilches Blázquez
  • Fuentes
    Tesauros y Bibliografía
    Catálogos de fenómenos
    Getty
    FTT ADL
    BCN25
    GEMET
    WFD
    CC.AA.
    EGM & ERM
    Diccionarios y
    Monografías
    BCN200
    Nomenclátor Geográfico Nacional
    Nomenclátor Conciso
    Luis Manuel Vilches Blázquez
  • Criterios de estructuración
    Directiva Marco del Agua
    Propuesta por Parlamento y Consejo de la UE
    Lista de definiciones de fenómenos hidrográficos
    Proyecto SDIGER
    Proyecto piloto INSPIRE
    Dos cuencas, países e idiomas
    Criterios semánticos
    Diccionarios geográficos
    Diccionario de la Real Academia de la Lengua
    WordNet
    Wikipedia
    Bibliografía de varias áreas de conocimiento
    Herencia: Estructuración actual de catálogos
    Asesoramiento expertos en toponimia del IGN
    Luis Manuel Vilches Blázquez
  • Modelización del dominio hidrográfico
    Luis Manuel Vilches Blázquez
  • Implementación & Formalizacón
    + Pellet
    4
    1
    2
    5
    3
    +150 conceptos (classes) , 47 tipos de relaciones (properties) y 64 tipos de atributos (attribute types)
    Luis Manuel Vilches Blázquez
  • 2. Vocabularydevelopment: HydrOntology
    58
    Asunción Gómez Pérez
  • 3. Generation of RDF
    From the Data sources
    Geographic information (Databases)
    Statistic information (.xsl)
    Geospatial information
    Different technologies for RDF generation
    Reengineering patterns
    R20 and ODEMapster
    Annotation tools
    Geometry generation
    Identification
    of the data sources
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • 3. Generation of the RDF Data
    NOR2O
    INE
    ODEMapster
    IGN
    Geometry2RDF
    Geospatial
    column
    IGN
  • 3. Generation of the RDF Data / instances
    NOR2O is a software librarythatimplementsthetransformationsproposedbythePatternsfor Re-engineering Non-OntologicalResources (PR-NOR). Currentlywehave 16 PR-NORs.
    PR-NORs define a procedurethattransforms a Non-OntologicalResource (NOR) componentsintoontologyelements. http://ontologydesignpatterns.org/
    · Classification
    schemes
    NOR2O
    · Thesauri
    · Lexicons
    NOR2O
    FAO Water classification
    · Classification scheme
    · Path enumeration data model
    · Implemented in a database
  • Re-engineeringModelforNORs
    Patterns for Re-engineering
    Non-Ontological Resources
    (PR-NOR)
    Ontology Forward
    Engineering
    Con-
    ceptual
    Speci-
    fication
    NOR Reverse
    Engineering
    Conceptua-
    lization
    Transformation
    Requirements
    Formalization
    Design
    Implementation
    Implementation
    RDF(S)
    Non-Ontological Resource
    Ontology
  • PR-NOR library at the ODP Portal
    Technologicalsupport
    http://ontologydesignpatterns.org/wiki/Submissions:ReengineeringODPs
  • 3. Generation of the RDF Data – NOR2O
    NOR2O
    Year
    Industry Production Index
    Province
  • hydrOntology & databases
    NGN
    1:25.000
    multilingüe
  • 3. Generation of the RDF Data – R2O & ODEMapster
    Creation of the R2O Mappings
  • 3. Generation of the RDF Data – Geometry2RDF
    Oracle STO UTIL package
    SELECT TO_CHAR(SDO_UTIL.TO_GML311GEOMETRY(geometry))
    AS Gml311Geometry
    FROM "BCN200"."BCN200_0301L_RIO" c
    WHERE c.Etiqueta='Arroyo'
  • 3. Generation of the RDF Data – Geometry2RDF
  • 3. Generation of the RDF Data – Geometry2RDF
  • 3. Generation of the RDF data – RDF graphs
    IGN INE
    So far
    7 RDF NamedGraphs
    1.412.248 triples
    BTN25
    BCN200
    IPI
    ….
    http://geo.linkeddata.es/dataset/IGN/BTN25
    http://geo.linkeddata.es/dataset/IGN/BCN200
    http://geo.linkeddata.es/dataset/INE/IPI
  • 4. Publication of the RDF Data
    Identification
    of the data sources
    Vocabulary
    development
    SPARQL
    Linked Data
    HTML
    Generation
    of the RDF Data
    IncludingProvenance
    Support
    Publication
    of the RDF data
    Pubby
    Pubby 0.3
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
    Virtuoso 6.1.0
  • 4. Publication of the RDF Data
  • 4. Publication of the RDF Data - License
    License for GeoLinkedData
    Creative Commons Attribution-ShareAlike 3.0
    GNU Free Documentation License
    Each dataset will have its own specific license, IGN, INE, etc.
  • 5. Data cleansing
    Identification
    of the data sources
    Lack of documentation of the IGN datasets
    Broken links: Spain, IGN resources
    Lack of documentation of theontology
    Missingenglish and spanishlabels
    Building a spanish ontology and importing some concepts of other ontology (in English):
    Importing the English ontology. Add annotations like a Spanish label to them.
    Importing the English ontology, creating new concepts and properties with a Spanish name and map those to the English equivalents.
    Re-declaring the terms of the English ontology that we need (using the same URI as in the English ontology), and adding a Spanish label.
    Creating your own class and properties that model the same things as the English ontology.
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • 5. Data cleansing
    URIs in Spanish
    http://geo.linkeddata.es/ontology/Río
    RDF allows UTF-8 characters for URIs
    But, Linked Data URIs has to be URLs as well
    So, non ASCII-US characters have to be %code
    http://geo.linkeddata.es/ontology/R%C3%ADo
  • 6. Linking of the RDF Data
    Identification
    of the data sources
    Silk - A Link Discovery Framework for the Web of Data
    First set of links: Provinces of Spain
    86% accuracy
    Vocabulary
    development
    Geonames
    Generation
    of the RDF Data
    GeoLinkedData
    DBPedia
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • 6. Linking of the RDF Data
    http://geo.linkeddata.es/page/Provincia/Granada
    77
    Asunción Gómez Pérez
  • 7. Enable effective discovery
    Identification
    of the data sources
    Vocabulary
    development
    Generation
    of the RDF Data
    Publication
    of the RDF data
    Data cleansing
    Linking
    the RDF data
    Enable effective
    discovery
  • DEMO
    http://geo.linkeddata.es/
  • Provinces
  • IndustryProductionIndex – Capital of Province
  • Rivers
  • Beaches
  • Contents
    IntroductiontoLinked Data
    Linked Data publication
    MethodologicalguidelinesforLinked Data publication
    RDB2RDF tools
    Technicalaspects of Linked Data publication
    Linked Data consumption
    84
  • Ontology-based Access to DBs
    1
    3
    2
    4
    Build a new ontology from 1 DB schema and 1 DB
    Align the ontology built with approach 1 with a legacy ontology
    Align an existing DB with a legacy ontology
    a) Massive dump (semantic data warehouse)
    b) Query-driven
    Align an ontology network with n DB schemas and other data sources
    a) Massive dump (semantic data warehouse)
    b) Query-driven
    new ontology
    existing ontology
  • Ontology-based Access to Databases
    Universidad
    Profesor
    Doctorando
    Ontología
    ?
    Organización
    Personal
    BDR
    Modelo
    Relacional
    Pregunta: Nombre de los profesores de la universidad UPM
    * Un profesor es una persona cuyo puesto es “docente”
    * Una universidad es una organización de tipo “3”
    Procesador
    Procesado de la consulta de acuerdo a la descripción formal de correspondencia
    Consulta: valores de la columna nombre de los registros de la tabla Personal para los que el valor de la columna puesto is “docente” que estén relacionados con al menos un registro de la tabla Organización con el valor “3” en la columna tipo y “UPM” en la columna nombre.
  • Align data sourceswithlegacyontologies
    Aeropuertos
    Ontología O2
    Ontología O1
    Centro
    Comunicaciones
    PuntoGPS
    Estación
    Punto Europeo
    Aeropuerto
    PuntoAsiatico
    PuntoEspañol
    Aeropuerto
    f (Aeropuertos)
    =
    PuntoEuropeo
    f (Aeropuertos)
    =
    RC(O2,M1)
    RC(O1,M1)
    Modelo Relacional M1
  • R2O
    is a declarative language to specify mappings between relational data sources and ontologies.
    <xml>
    R2O Mapping
    </xml>
    Organization
    Persons
    University
    RDB
    Professor
    Student
    Relational Model
    Ontology
  • Example: types of mappingsneeded
    Attibute Mapping with transformation
    (Regular Expression)
    Attibute Direct Mapping
    Relation Mapping w. Transformation
    (Regular Expression)
    Relation Mapping w. Transformation
    (Keyword search)
  • Population example (II)
    Population example (II)
    The Operation element defines a transformation based on a regular expression to be applied to the database column for extracting property values
  • For concepts...
    One or more concepts can be extracted from a single data field (not in 1NF).
    A view maps exactly one concept in the ontology.
    For attributes...
    A column in a database view maps directly an attribute or a relation.
    A subset of the columns in the view map a concept in the ontology.
    A subset (selection) of the records of a database view map a concept in the ontology.
    A column in a database view maps an attribute or a relation after some transformation.
    A subset of the records of a database view map a concept in the onto. but the selection cannot be made using SQL.
    A set of columns in a database view map an attribute or a relation.
    R2O (Relational-to-Ontology) Language
  • R2O Basic Syntax
    <conceptmap-defname="Customer">
    <identified-by> Table key </identified-by>
    <uri-as>operation</uri-as>
    <applies-if>condition</applies-if>
    <joins-via> expression </joins-via>
    <documentation>description …</documentation>
    <described-by>attributes,relations</described-by>
    </conceptmap-def>
    <attributemap-defname="http://esperonto/ff#Title">
    <aftertransform>
    <operationoper-id="constant">
    <arg-restrictionon-param="const-val">
    <has-column>fsb_ajut.titol</has-column>
    </arg-restriction>
    </operation>
    </aftertransform>
    </attributemap-def>
    <relationmap-defname="http://esperonto/ff#isCandidateFor">
    <to-concept name="http://esperonto/ff#FundOpp">
    <joins-via>
    <operationoper-id=“equals">
    <arg-restrictionon-param="value1">
    <has-column>fsb_ajut.id</has-column>
    </arg-restriction>
    <arg-restriction on-param="value2">
    <has-column>fsb_candidate.forFund</has-column>
    </arg-restriction>
    </operation>
    </joins-via>
    </relationmap-def>
  • ODEMapster
    generates RDF instances from relational instances based on the mapping description expressed in the R2O document
  • 94
    Mapping Design
    • 3 Mapping Creation Steps
    • Load Ontology
    • Load Database(s)
    • Create mapping
    • 2 Usage Modes
    • Online mode (run time query execution)
    • Offline mode (materialized RDF dump)
  • Contents
    IntroductiontoLinked Data
    Linked Data publication
    MethodologicalguidelinesforLinked Data publication
    RDB2RDF tools
    Technicalaspects of Linked Data publication
    Linked Data consumption
    95
  • Using an RDF repository
    Itallowsstoring and accessing RDF data
    Forexample, SESAME (http://www.openrdf.org/)
    Downloaditfromhttp://www.openrdf.org/download.jsp
    openrdf-sesame-2.3.0-sdk.zip
    Deploythe .war in Tomcat (JDK and Tomcatneeded)
    Create a repository at
    http://localhost:8080/openrdf-sesame
    Check:
    http://localhost:8080/openrdf-sesame/repositories/XXXX
    http://localhost:8080/openrdf-sesame/repositories/XXX/statements
  • Linked Data frontend
    Toexpose data as Linked Data
    Includingcontentnegotiation, etc.
    Forexample, Pubby
    http://www4.wiwiss.fu-berlin.de/pubby/
    Installation
    Use pubby-0.3.zip
    Deploythewebapp folder (and rename)in Tomcat
    Modify config.n3
    Restarttomcat
    Check: http://localhost:8080/XXX/
  • REST API
    • Forexample, RDF2Go
    • Java abstractionover RDF repositories
    http://rdf2go.semweb4j.org/
  • Add SPARQL explorer
    Forexample, SNORQL (http://wiki.github.com/kurtjx/SNORQL/)
  • ValidatingLinked Data URLs
    http://validator.linkeddata.org/vapour
    100
  • Contents
    IntroductiontoLinked Data
    Linked Data publication
    MethodologicalguidelinesforLinked Data publication
    RDB2RDF tools
    Technicalaspects of Linked Data publication
    Linked Data consumption
    101
  • RelFinder: finding relations in Linked Data
    E.g., relations between films
    “Pulp Fiction”, “Kill Bill” y “Reservoir Dogs”
  • Exerciseon data.gov.uk
    • Publicschools in London thatcontaintheword “music”
  • Exercise: find information in DBPedia
    Image by http://www.flickr.com/photos/bflv/
    http://dbpedia.org/resource/Darth_Vader)
    • Findficticious serial killers in DBPedia
    (etc)
  • Designing URI sets forthePublic Sector (UK)
    http://www.cabinetoffice.gov.uk/media/301253/puiblic_sector_uri.pdf
    105
  • Asociación Española de Linked Data
    106
  • IntroductiontoLinked Data
    Oscar Corcho, Asunción Gómez Pérez ({ocorcho, asun}@fi.upm.es)
    Universidad Politécnica de Madrid
    Universidad del Valle, Cali, ColombiaSeptember 10th 2010
    Credits: Raúl García Castro, Oscar Muñoz, Jose Angel Ramos Gargantilla, María del Carmen Suárez de Figueroa, Boris Villazón, Alex de León, Víctor Saquicela, Luis Vilches, Miguel Angel García, Manuel Salvadores, Guillermo Alvaro, Juan Sequeda, Carlos Ruiz Moreno and manyothers
    WorkdistributedunderthelicenseCreativeCommonsAttribution-Noncommercial-Share Alike 3.0