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Publishing Linked Data
        using Schema.org
      Development and management
         of e-Repositories – OTA

        IODE, Oostende, Belgium,
            April 11th, 2013

       An introduction to the project of
           Mr. Aditya Kakodkar by
Christophe.Dupriez@destin-informatique.com
LinkedData, Why?
●   External/Internal (Reference) Data
    use and reuse
●   (Meta) Data encoded and published along
    standardized, perennial and documented
    measurement systems and categories
●   Massive international efforts for tools and
    interlinked repositories development
●   Opportunity to become a General Reference on
    the Web for a specific domain
●   Your work becomes discoverable
    and well positioned by Search Engines
Data to be linked ?
●
    Metadata provides the context,
     links to a MODEL
●   Observed Data: source, measure/range, unit...
●   Manually entered Data: validation rules
●   Aggregated Data:
     Which indicator for which decision?
●   Published Data: exact? complete? perenial?
●   Reference Data: comparability with other data?
●   Open Data is (not) Public Data! http://opendatacommons.org
●   Personal Data: protection? anonymisation?
●   Big Data: dangers? opportunities?
Linking Data in order to...
●   Denote an “real life” object,
    a concept, a transaction...
    –   not uniquely enough: sameAs.org
●   Document (explain, contextualize)
    the data to the user (HTML document page)
●   Enrich, linking to other data ...
     (RDF data page)
LinkedData semiotic triangle




         https://twitter.com/kidehen/status/312571324742651908
RDF: Resource Description
                Framework
●   A standard to provide (meta)data on the Web
●   Based on a very simple model of triplets:
    subject – property – object
●   Everything is an URI; object can also be a
    “constant value” (a text, a number, a date...)
    suffixed by an indication of the language
●   Example:
    dbpedia:European_Herring_Gull rdfs:label “Goéland argenté”@fr
    where “dbpedia:” stands for URI prefix:
    http://dbpedia.org/resource/
    and “rdfs:” stands for URI prefix:
    http://www.w3.org/2000/01/rdf-schema#
Being a Gull is not Dull !
●   http://en.wikipedia.org/wiki/European_Herring_Gull
●   http://dbpedia.org/resource/European_Herring_Gull
    which redirects to the document
    (HTML for human consumption):
    http://dbpedia.org/page/European_Herring_Gull
●   Data (for machine consumption) is generated separately in
    different formats (N3, Turtle, XML, JSON...) :
    http://dbpedia.org/data/European_Herring_Gull.n3
●   Browser negotiates the suitable format...
●   What is validated there? What are the rules?
●   Can it be a reference to take decisions?
Using a single page?
●
    RDFa and MicroData are two standards to MERGE
    an HTML document (made for humans) and the data
    a machine may wish to extract from it
●   Example from a page in OceanExpert.net:
    <h1>Details of<span itemprop="name">
       <span itemprop="familyName">Dupriez</span>
             ,&nbsp;
       <span itemprop="givenName">Christophe
       </span>
     </span></h1>
●   ANY23.org, an Open Source software to collect data
    embedded in a Web Page will be demonstrated later
    on OceanExpert.net...
Data Model
●   Which processes do we need to automate?
    (use cases)
●   Which entities (real objects, concepts,
    transactions/events) have to be represented?
●   How do those entities interrelate?
●   What measures (properties) are made about
    each type of entity?
●   Reuse: who else will align on the same model?
    What Google may do with my data?
Schema.org
●
    Schema.org is a modelling initiative of
    Google / Microsoft / Yahoo to standardize URIs for RDF
    properties
●   Common model for data published as documents
    harvestable on the web
●   Their goal is to collect the data in our pages.
    Those pages are then better indexed.
    What else? (A.I.?)
●   Schema.org models are far from exhaustive
    (for instance, insufficient for CVs)
    but a “/extension” mechanism exists
●   Examples on the site http://schema.org
Google RichSnippets
●   Google Spider extracts data tagged using RDFa
    or MicroData
●   Pages with such data are promoted...
●   Google Search Engine enriches results using
    this data
●   Example “Apollo Theatre”:
    place, events, reviews...
●   Google RichSnippets tool validates a web page:
    http://www.google.com/webmasters/tools/richsnippets
Data Search Engine
●   ANY23 is used to feed SINDICE,
    the Search Engine for RDF data
●   Example:
    http://www.sindice.com/search?q=apollo+theatre

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Publishing Linked Data using Schema.org

  • 1. Publishing Linked Data using Schema.org Development and management of e-Repositories – OTA IODE, Oostende, Belgium, April 11th, 2013 An introduction to the project of Mr. Aditya Kakodkar by Christophe.Dupriez@destin-informatique.com
  • 2. LinkedData, Why? ● External/Internal (Reference) Data use and reuse ● (Meta) Data encoded and published along standardized, perennial and documented measurement systems and categories ● Massive international efforts for tools and interlinked repositories development ● Opportunity to become a General Reference on the Web for a specific domain ● Your work becomes discoverable and well positioned by Search Engines
  • 3. Data to be linked ? ● Metadata provides the context, links to a MODEL ● Observed Data: source, measure/range, unit... ● Manually entered Data: validation rules ● Aggregated Data: Which indicator for which decision? ● Published Data: exact? complete? perenial? ● Reference Data: comparability with other data? ● Open Data is (not) Public Data! http://opendatacommons.org ● Personal Data: protection? anonymisation? ● Big Data: dangers? opportunities?
  • 4. Linking Data in order to... ● Denote an “real life” object, a concept, a transaction... – not uniquely enough: sameAs.org ● Document (explain, contextualize) the data to the user (HTML document page) ● Enrich, linking to other data ... (RDF data page)
  • 5. LinkedData semiotic triangle https://twitter.com/kidehen/status/312571324742651908
  • 6. RDF: Resource Description Framework ● A standard to provide (meta)data on the Web ● Based on a very simple model of triplets: subject – property – object ● Everything is an URI; object can also be a “constant value” (a text, a number, a date...) suffixed by an indication of the language ● Example: dbpedia:European_Herring_Gull rdfs:label “Goéland argenté”@fr where “dbpedia:” stands for URI prefix: http://dbpedia.org/resource/ and “rdfs:” stands for URI prefix: http://www.w3.org/2000/01/rdf-schema#
  • 7. Being a Gull is not Dull ! ● http://en.wikipedia.org/wiki/European_Herring_Gull ● http://dbpedia.org/resource/European_Herring_Gull which redirects to the document (HTML for human consumption): http://dbpedia.org/page/European_Herring_Gull ● Data (for machine consumption) is generated separately in different formats (N3, Turtle, XML, JSON...) : http://dbpedia.org/data/European_Herring_Gull.n3 ● Browser negotiates the suitable format... ● What is validated there? What are the rules? ● Can it be a reference to take decisions?
  • 8. Using a single page? ● RDFa and MicroData are two standards to MERGE an HTML document (made for humans) and the data a machine may wish to extract from it ● Example from a page in OceanExpert.net: <h1>Details of<span itemprop="name"> <span itemprop="familyName">Dupriez</span> ,&nbsp; <span itemprop="givenName">Christophe </span> </span></h1> ● ANY23.org, an Open Source software to collect data embedded in a Web Page will be demonstrated later on OceanExpert.net...
  • 9. Data Model ● Which processes do we need to automate? (use cases) ● Which entities (real objects, concepts, transactions/events) have to be represented? ● How do those entities interrelate? ● What measures (properties) are made about each type of entity? ● Reuse: who else will align on the same model? What Google may do with my data?
  • 10. Schema.org ● Schema.org is a modelling initiative of Google / Microsoft / Yahoo to standardize URIs for RDF properties ● Common model for data published as documents harvestable on the web ● Their goal is to collect the data in our pages. Those pages are then better indexed. What else? (A.I.?) ● Schema.org models are far from exhaustive (for instance, insufficient for CVs) but a “/extension” mechanism exists ● Examples on the site http://schema.org
  • 11. Google RichSnippets ● Google Spider extracts data tagged using RDFa or MicroData ● Pages with such data are promoted... ● Google Search Engine enriches results using this data ● Example “Apollo Theatre”: place, events, reviews... ● Google RichSnippets tool validates a web page: http://www.google.com/webmasters/tools/richsnippets
  • 12. Data Search Engine ● ANY23 is used to feed SINDICE, the Search Engine for RDF data ● Example: http://www.sindice.com/search?q=apollo+theatre