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Linking Open Data
                   with Drupal


Emmanuel Jamin



 Drupal.cat      October 4th, 2012   Citilab, Cornellá
Who am I?
Emmanuel Jamin
   –   PhD
        •    At Paris XI university (LIMSI-CNRS, Orsay)


   –   Research and development (EU projects)
        •    At Edelweiss (INRIA, Sophia Antipolis)
        •    At the Knowledge Lab (ATOS, Barcelona)


   –   Now
        •    Semantic Web consultant in Barcelona
        •    www.OpenData-consulting.com
        •    @openDataC
Plan
Introduction to Open Data


Introduction to the Semantic Web


From Open Data to Linked Data
A – OD - Definition


“Open data is    data that can be freely used,
 reused and       redistributed by anyone –
 subject only,   at most, to the requirement to
 attribute and   sharealike.”

                         http://OpenDefinition.org
A – OD - Principles

> Availability and Access
   Availability and
                    Access


   Reuse and Redistribution
               > Reuse and Redistribution

   Universal Participation
     > Universal Participation
A – OD – Small history
1957-1958: 1st concept
           “open access to scientific data”

2001: 1st definition
           “the web of data” (Tim Berners Lee)

2004-05: 1st fondation
           Open Knowledge Fondation (http://okfn.org/)

2009-05: 1st Open Government platform in US
           http://data.gov

2012-09: 1st Open Knowledge Festival
           http://okfestival.org
Image by Peter Ito (2009): http://www.flickr.com/photos/peterito/3054501076/lightbox/
A – OD - Platforms

                                       Open Cities
   Open Science
Open Government
                        Transparency
Open Science
          Open
Open Cities           Government
               Participation
Open Education                     Collaboration
 Open Culture
Open Health                    Open Health
…
         Open Education
A – OD – Status of OD
Topics




         From: http://okfn.org/opendata/
A – OD – Status of OD
                      Database
Types of Data
                         Structured Data
  Documents
     Documents


  Raw data       Open Data
                                 Raw Data
  Structured data
        Linked Data
  Linked data               Geo Data
A – OD – Status of OD
Heterogenous standards (Open Standard)
            TXT
PDF - DOC                      PDF
CSV                  CSV
      ZIP
XML                                      ODT
RDF JSON
                             RDF
KML-KMZ                XML
                                   XSL
            JSON
A – OD – Comparison
              Barcelona                   Catalunya                      España
   Datos.gov.es / Gen.cat / barcelona.cat
Website   http://w20.bcn.cat/opendata/ http://www20.gencat.cat/portal/site/dadesobertes/
                                                                  http://datos.gob.es/datos/




Topics    Economy,                    Cartography and             Public sector,
          Cartography,                maps, Facilities            Culture and hobbies,
          Population,                 Statistics,                 Science and
          Environment,                Meteorology.                technologies,
          Administration              Nomenclators,               Environment,
                                      Health, Public              Education,
                                      transport, Turism           Tansport



Formats   CSV, PDF, XLS,     TMX, ZIP, PDF,                       XHTML, HTML,
          XML, RDF, TXT, ZIP CSV, KML-KMZ,                        PDF, XLS, XML, ZIP
                             DOC, XLS, XML,
                             JSON, RDF, SHP,
                             SPARQL
A – OD – Why opening up data?




Why opening up the data?
   Why opening up the Data
                      Data?
A – OD – Why opening up data?
Facet search and browsing
Data integration
    to compare easily




                            http://civio.es
A – OD http://manybills.researchlabs.ibm.com/
       – Why opening up data?
A – OD – Why opening up data?
                                   Big Data analysis
Graphic representation of dataset
     Statistics
                         Graphic representation
    to visualize it easily
Data reuse and combination
 Data vizualization
                                  Data integration
Data integration
       Data reuse
    to compare easily
                   Facet search and browsing
Facet search and browsing
   – to contextualize information easily
 Data contextualization
                                      Data mapping
A – OD – Why opening up data?

   Analyze it …                 Reuse it …
Opening the data
    Reuse it
                   Open Data
    Mix it
    Analyse it
    Mix it …                   Visualise it …
    Vizualize it


For for a better comprehension!
    a better comprehension
OD – The big challenge
The OD movement has:
 The big challenge
    The energy
    The Open Mind philosophy
    The public resources
    Etc.


But something is missing ...
From: http://www.nathan.com/thoughts/unified/3.html
OD – The big challenge

Opening the data is great !

    But it is not enough …




    Linking Open Data !
Semantic Web
From: http://salesenablement.wordpress.com/2010/09/07/the-importance-of-context/
B – SW - Principios


 Do not read the next slide
Do not read the next slide!
B – SW - Principios

You loose!
B – SW - Principios

 Humans identify and interpret information
Humans identify and interpret information


Machines don't
      Machines don't
B – Towards the structured web

 Separate the content and the form
Separate the form and the content
    XML and metadata
B–
                 Towards the Structured Web
Arbitrary metadata
 XML and the metadata

    <book/>
       |
        <chapter/>
             |
              <paragraph/>
B–

  What do really understand the machines?
Arbitrary metadata

    <hbskm/>
       |
        <rzañokt/>
             |
               <kmcsuhdd/>
B–

What is the last document have your read?




    Which is the last document you read?
B–

    Document?
Document
{ book, newspaper, paper, post-card … }
B–
                    The answer is based on a
                       Shared Ontology
The answer is based on a shared knowledge

We can understand




                            You can reason
B–
                Document

Document

Book
                 Book

Roman / Novel
       Roman               Novel
B–

“An ontology is a specification of a
conceptualization”

   (i.e. the logical description of the concepts
       and relationships that can exist for an
       agent or a community of agents).

                   Tom Grüber (1993)
B–

Towards the Semantic Web
   Towards the Semantic Web
B – SW - Definition

the Semantic Web is


        "a web of data that can be
 processed directly and indirectly by
 machines."

                       Tim Berners Lee (2001)
B–

The W3C normalization / scale




          From: http://mmt.me.uk/slides/london011209/#(2)
B – SW – Resources
           Everything is a resource
Everything is a resource
    –   Person             Berners Lee
    –   Organisation       W3C
    –   Document           paper.html
    –   Event              SW conference 2012
    –   … etc.
B – SW – Resources
            Each resource is identified
               with a unique reference.
Each resource identified with an URI


    www.w3c.org/people/timbl.html#this     Berners Lee

    www.w3c.org/index.html#this            W3C

    www.w3c.org/papers/paper.html#this     paper.html


    www.w3c.org/events/swcon12.html#this   SW con'12
B – SW – Resources
    Namespace to reference
Namespace to simplify URI                     the URI
   Namespace:
        www.w3c.org/people/timbl.html#

   Prefix
        tbl: www.w3c.org/people/timbl.html#

   CURIE
        tbl:this
B – SW – Resources
        CURIE to simplify the URI
Namespace to simplify URI


     w3c:timbl        foaf:Person

     w3c:this         foaf:Organisation

     dblp:this        foaf:Document

     event:this       foaf:Event
B – SW – Triples

RDFRDF

   (Subject, predicate, object)
         (Subject, predicate, object)
B – SW – Triples
RDF triples

      web.html has author Tim Berners Lee


      LinkedData.html has author Hausenblas


      W3C has employee Tim Berners Lee


      web.html is published at SW conference
B – SW – Ontologies

RDF-S → RDF-Schema

   Definition of the
        •   Classes (concepts)
        •   and Properties (conceptual relations)


   Hierachy organisation with conceptual
      relations
B – SW – Ontologies


RDFS

–   Book is sub-type of Document

–   Novel is sub-type of Book
–   Roman is sub-type of Book
B – SW – RDF graph
          RDF triples => Linked Data
RDF triples = LinkedData
    –   W3C.html has author Tim Berners Lee

    –   W3C.html is type of Document

    –   Tim Berners Lee is type of Person

    –   W3C.html is presented at Web Conference 2012

    –   Web Conference 2012 is type of Conference

    –   Conference is sub class of Event
B – SW – RDF graph
              RDF triples => RDF graph
                                                       Organisation


 RDF triples = RDF graph
 Event

                 Document       Person


         RDF graph                                               W3C


Conference
                     web.html               Tim
                                         Berners Lee




     SW conference
B – SW – Federated Dataset
               Federated dataset

    All resources are connected
Resources are connected over the web
                                      over the Web
  LOD site 1                    LOD site 2


               w3c:this              w3c:this



       tim:this                          ivan:this



                                                 doc3:this
     doc1:this                   doc2:this
                    doc2:this
B – SW – SPARQL
     Search and retrieve information
Find and retrieve information from the graph
          from the graph with SPARQL
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?document ?authorName
WHERE {
           ?person rdf:type foaf:Person
           ?person foaf:name ?authorName
           ?authorName foaf:made ?document
}
B – SW – Giant Global Graph
                Global Giant Graph



The web becomes one giant database
B – SW
Is this a fiction?




             Is it a fiction?
B – SW
Google Rich Snippet
                                            Rich Snippets




 From: http://openspring.net/blog/2011/09/30/schemaorg-rich-snippets-drupal-7-rdfa
B – SW
Facebook




                    Open Graph
B – SW
                   Knowledge Graph
Google Knowledge Graph
C – OD + LD
C – OD + LD
        From Open Data to Linked Data
From Open Data to Linked Data
                                      RDFS
  Open Data
                                RDF



                         JSON
                                                    Linked Data
                                       XML


              CSV




  PDF

                                             Structured Data
CFrom PDF to RDF
                – OD + LD
From PDF to RDF
   1. Document engineering
       •   Content extraction
       •   Content format
       •   Multimedia extraction

   2. Knowledge engineering
       •   Term extraction (indexation)
       •   Recognition of Named Entities
       •   Ontology engineering
       •   Conceptual recognition and mapping
C – OD + LD
       Synthesis about data formats
Síntesis de los formatos (table)
C – to arrive in LOD
         To succeed with Linked Data
Linking Open Data
    1. Data formalization
          •   Create or reuse ontologies (RDF, RDFS, OWL)

    2. Data annotation
          •   Associate semantic metadata (RDF, RDFa, Microdata)

    3. Data publication
          •   Publish your semantic data (RDFa, Microdata)

    4. Data consumption
          •   Reuse all available data (SPARQL endpoints)
C – OD + LD
From Open Data to Linked Data




   Data quality
B – SW – Big Giant Graph
Open Data + Data Interconnection

         Linked
Linked Open Data    Open Data

   25 billion RDF triples over the web
  25 billion of RDF triples over the web
From: http://www.w3.org/DesignIssues/diagrams/lod/2010-color.png
B – SW – Big Giant Graph
Open Data + Data Interconnection

         Linked
Linked Open Data        Open Data

    25 billion RDF triples over the web




   http://dbpedia.org
B – SW – Big Giant Graph
Open Data + Data Interconnection


Linked Open Data


   25 billion RDF triples over the web
  The Web 3.0

             is already here ...
Linking Open Data with Drupal
D – LODrupal - Drupal
                  LOD and Drupal

    Availability and Access
Entities ↔ Resources
   Entities ↔ Resources

RDFReuse and Redistribution
    in Core
                   RDF in Drupal Core
    Universal Participation
Semantic Web modules
    and Semantic Web modules
Main Microdata Web modules
     Semantic
 Import Linked Data
                          schema.org
  Microdata
  SPARQL         RDFx
  SPARQL Views
                          SPARQL Views
  RDFx
      SPARQL
D – LODrupal – Mod1 ...
         RDFx




     From: http://drupal.org/project/rdfx
D – LODrupal – Mod1 ...
       schemaorg




    From: http://drupal.org/project/schemaorg
D – LODrupal – Mod1 ...
        SPARQL




     From: http://drupal.org/project/sparql
D – LODrupal – Drupal Prototype



Demonstration



                     Demo
E – LODrupal Hackathon




LOD + Drupal hackathon
E –LOD + Drupal hackathon
         LODrupal Hackathon

Sprint 1:             Sprint 2:

A1 - Consume OD       B1 - Publish LOD


A2 - OD Integration   B2 - Build LOD
                      applications

Saturday
                      Saturday
    10/11/2012
                          08/12/2012
E – LODrupal Hackathon
              References

−   http://okfn.org/opendata/

−   http://www.slideshare.net/fabien_gandon/web-smantique-
    donnes-lies-et-smantique-des-schmas-2184768
−   http://www.slideshare.net/scorlosquet/how-to-build-
    linked-data-sites-with-drupal-7-and-rdfa

−   http://www20.gencat.cat/portal/site/dadesobertes/
−   http://w20.bcn.cat/opendata/
−   http://datos.gob.es/datos/

−   http://drupal.org/project/odv
Questions

        Questions?




                     Thanks!

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121004 linking open_data_with_drupal_v1

  • 1. Linking Open Data with Drupal Emmanuel Jamin Drupal.cat October 4th, 2012 Citilab, Cornellá
  • 2. Who am I? Emmanuel Jamin – PhD • At Paris XI university (LIMSI-CNRS, Orsay) – Research and development (EU projects) • At Edelweiss (INRIA, Sophia Antipolis) • At the Knowledge Lab (ATOS, Barcelona) – Now • Semantic Web consultant in Barcelona • www.OpenData-consulting.com • @openDataC
  • 3. Plan Introduction to Open Data Introduction to the Semantic Web From Open Data to Linked Data
  • 4.
  • 5. A – OD - Definition “Open data is data that can be freely used, reused and redistributed by anyone – subject only, at most, to the requirement to attribute and sharealike.” http://OpenDefinition.org
  • 6. A – OD - Principles > Availability and Access Availability and Access Reuse and Redistribution > Reuse and Redistribution Universal Participation > Universal Participation
  • 7. A – OD – Small history 1957-1958: 1st concept “open access to scientific data” 2001: 1st definition “the web of data” (Tim Berners Lee) 2004-05: 1st fondation Open Knowledge Fondation (http://okfn.org/) 2009-05: 1st Open Government platform in US http://data.gov 2012-09: 1st Open Knowledge Festival http://okfestival.org
  • 8. Image by Peter Ito (2009): http://www.flickr.com/photos/peterito/3054501076/lightbox/
  • 9. A – OD - Platforms Open Cities Open Science Open Government Transparency Open Science Open Open Cities Government Participation Open Education Collaboration Open Culture Open Health Open Health … Open Education
  • 10. A – OD – Status of OD Topics From: http://okfn.org/opendata/
  • 11. A – OD – Status of OD Database Types of Data Structured Data Documents Documents Raw data Open Data Raw Data Structured data Linked Data Linked data Geo Data
  • 12. A – OD – Status of OD Heterogenous standards (Open Standard) TXT PDF - DOC PDF CSV CSV ZIP XML ODT RDF JSON RDF KML-KMZ XML XSL JSON
  • 13. A – OD – Comparison Barcelona Catalunya España Datos.gov.es / Gen.cat / barcelona.cat Website http://w20.bcn.cat/opendata/ http://www20.gencat.cat/portal/site/dadesobertes/ http://datos.gob.es/datos/ Topics Economy, Cartography and Public sector, Cartography, maps, Facilities Culture and hobbies, Population, Statistics, Science and Environment, Meteorology. technologies, Administration Nomenclators, Environment, Health, Public Education, transport, Turism Tansport Formats CSV, PDF, XLS, TMX, ZIP, PDF, XHTML, HTML, XML, RDF, TXT, ZIP CSV, KML-KMZ, PDF, XLS, XML, ZIP DOC, XLS, XML, JSON, RDF, SHP, SPARQL
  • 14. A – OD – Why opening up data? Why opening up the data? Why opening up the Data Data?
  • 15.
  • 16. A – OD – Why opening up data? Facet search and browsing Data integration to compare easily http://civio.es
  • 17. A – OD http://manybills.researchlabs.ibm.com/ – Why opening up data?
  • 18.
  • 19. A – OD – Why opening up data? Big Data analysis Graphic representation of dataset Statistics Graphic representation to visualize it easily Data reuse and combination Data vizualization Data integration Data integration Data reuse to compare easily Facet search and browsing Facet search and browsing – to contextualize information easily Data contextualization Data mapping
  • 20. A – OD – Why opening up data? Analyze it … Reuse it … Opening the data Reuse it Open Data Mix it Analyse it Mix it … Visualise it … Vizualize it For for a better comprehension! a better comprehension
  • 21. OD – The big challenge The OD movement has: The big challenge The energy The Open Mind philosophy The public resources Etc. But something is missing ...
  • 23. OD – The big challenge Opening the data is great ! But it is not enough … Linking Open Data !
  • 26. B – SW - Principios Do not read the next slide Do not read the next slide!
  • 27. B – SW - Principios You loose!
  • 28. B – SW - Principios Humans identify and interpret information Humans identify and interpret information Machines don't Machines don't
  • 29. B – Towards the structured web Separate the content and the form Separate the form and the content XML and metadata
  • 30. B– Towards the Structured Web Arbitrary metadata XML and the metadata <book/> | <chapter/> | <paragraph/>
  • 31. B– What do really understand the machines? Arbitrary metadata <hbskm/> | <rzañokt/> | <kmcsuhdd/>
  • 32. B– What is the last document have your read? Which is the last document you read?
  • 33. B– Document? Document { book, newspaper, paper, post-card … }
  • 34. B– The answer is based on a Shared Ontology The answer is based on a shared knowledge We can understand You can reason
  • 35. B– Document Document Book Book Roman / Novel Roman Novel
  • 36. B– “An ontology is a specification of a conceptualization” (i.e. the logical description of the concepts and relationships that can exist for an agent or a community of agents). Tom Grüber (1993)
  • 37. B– Towards the Semantic Web Towards the Semantic Web
  • 38. B – SW - Definition the Semantic Web is "a web of data that can be processed directly and indirectly by machines." Tim Berners Lee (2001)
  • 39. B– The W3C normalization / scale From: http://mmt.me.uk/slides/london011209/#(2)
  • 40. B – SW – Resources Everything is a resource Everything is a resource – Person Berners Lee – Organisation W3C – Document paper.html – Event SW conference 2012 – … etc.
  • 41. B – SW – Resources Each resource is identified with a unique reference. Each resource identified with an URI www.w3c.org/people/timbl.html#this Berners Lee www.w3c.org/index.html#this W3C www.w3c.org/papers/paper.html#this paper.html www.w3c.org/events/swcon12.html#this SW con'12
  • 42. B – SW – Resources Namespace to reference Namespace to simplify URI the URI Namespace: www.w3c.org/people/timbl.html# Prefix tbl: www.w3c.org/people/timbl.html# CURIE tbl:this
  • 43. B – SW – Resources CURIE to simplify the URI Namespace to simplify URI w3c:timbl foaf:Person w3c:this foaf:Organisation dblp:this foaf:Document event:this foaf:Event
  • 44. B – SW – Triples RDFRDF (Subject, predicate, object) (Subject, predicate, object)
  • 45. B – SW – Triples RDF triples web.html has author Tim Berners Lee LinkedData.html has author Hausenblas W3C has employee Tim Berners Lee web.html is published at SW conference
  • 46. B – SW – Ontologies RDF-S → RDF-Schema Definition of the • Classes (concepts) • and Properties (conceptual relations) Hierachy organisation with conceptual relations
  • 47. B – SW – Ontologies RDFS – Book is sub-type of Document – Novel is sub-type of Book – Roman is sub-type of Book
  • 48. B – SW – RDF graph RDF triples => Linked Data RDF triples = LinkedData – W3C.html has author Tim Berners Lee – W3C.html is type of Document – Tim Berners Lee is type of Person – W3C.html is presented at Web Conference 2012 – Web Conference 2012 is type of Conference – Conference is sub class of Event
  • 49. B – SW – RDF graph RDF triples => RDF graph Organisation RDF triples = RDF graph Event Document Person RDF graph W3C Conference web.html Tim Berners Lee SW conference
  • 50. B – SW – Federated Dataset Federated dataset All resources are connected Resources are connected over the web over the Web LOD site 1 LOD site 2 w3c:this w3c:this tim:this ivan:this doc3:this doc1:this doc2:this doc2:this
  • 51. B – SW – SPARQL Search and retrieve information Find and retrieve information from the graph from the graph with SPARQL PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?document ?authorName WHERE { ?person rdf:type foaf:Person ?person foaf:name ?authorName ?authorName foaf:made ?document }
  • 52. B – SW – Giant Global Graph Global Giant Graph The web becomes one giant database
  • 53. B – SW Is this a fiction? Is it a fiction?
  • 54. B – SW Google Rich Snippet Rich Snippets From: http://openspring.net/blog/2011/09/30/schemaorg-rich-snippets-drupal-7-rdfa
  • 55. B – SW Facebook Open Graph
  • 56. B – SW Knowledge Graph Google Knowledge Graph
  • 57.
  • 58. C – OD + LD
  • 59. C – OD + LD From Open Data to Linked Data From Open Data to Linked Data RDFS Open Data RDF JSON Linked Data XML CSV PDF Structured Data
  • 60. CFrom PDF to RDF – OD + LD From PDF to RDF 1. Document engineering • Content extraction • Content format • Multimedia extraction 2. Knowledge engineering • Term extraction (indexation) • Recognition of Named Entities • Ontology engineering • Conceptual recognition and mapping
  • 61. C – OD + LD Synthesis about data formats Síntesis de los formatos (table)
  • 62. C – to arrive in LOD To succeed with Linked Data Linking Open Data 1. Data formalization • Create or reuse ontologies (RDF, RDFS, OWL) 2. Data annotation • Associate semantic metadata (RDF, RDFa, Microdata) 3. Data publication • Publish your semantic data (RDFa, Microdata) 4. Data consumption • Reuse all available data (SPARQL endpoints)
  • 63. C – OD + LD From Open Data to Linked Data Data quality
  • 64. B – SW – Big Giant Graph Open Data + Data Interconnection Linked Linked Open Data Open Data 25 billion RDF triples over the web 25 billion of RDF triples over the web
  • 66. B – SW – Big Giant Graph Open Data + Data Interconnection Linked Linked Open Data Open Data 25 billion RDF triples over the web http://dbpedia.org
  • 67. B – SW – Big Giant Graph Open Data + Data Interconnection Linked Open Data 25 billion RDF triples over the web The Web 3.0 is already here ...
  • 68. Linking Open Data with Drupal
  • 69. D – LODrupal - Drupal LOD and Drupal Availability and Access Entities ↔ Resources Entities ↔ Resources RDFReuse and Redistribution in Core RDF in Drupal Core Universal Participation Semantic Web modules and Semantic Web modules
  • 70. Main Microdata Web modules Semantic Import Linked Data schema.org Microdata SPARQL RDFx SPARQL Views SPARQL Views RDFx SPARQL
  • 71. D – LODrupal – Mod1 ... RDFx From: http://drupal.org/project/rdfx
  • 72. D – LODrupal – Mod1 ... schemaorg From: http://drupal.org/project/schemaorg
  • 73.
  • 74. D – LODrupal – Mod1 ... SPARQL From: http://drupal.org/project/sparql
  • 75. D – LODrupal – Drupal Prototype Demonstration Demo
  • 76. E – LODrupal Hackathon LOD + Drupal hackathon
  • 77.
  • 78. E –LOD + Drupal hackathon LODrupal Hackathon Sprint 1: Sprint 2: A1 - Consume OD B1 - Publish LOD A2 - OD Integration B2 - Build LOD applications Saturday Saturday 10/11/2012 08/12/2012
  • 79. E – LODrupal Hackathon References − http://okfn.org/opendata/ − http://www.slideshare.net/fabien_gandon/web-smantique- donnes-lies-et-smantique-des-schmas-2184768 − http://www.slideshare.net/scorlosquet/how-to-build- linked-data-sites-with-drupal-7-and-rdfa − http://www20.gencat.cat/portal/site/dadesobertes/ − http://w20.bcn.cat/opendata/ − http://datos.gob.es/datos/ − http://drupal.org/project/odv
  • 80. Questions Questions? Thanks!