SlideShare une entreprise Scribd logo
1  sur  28
Télécharger pour lire hors ligne
LOD2 is a large-scale integrating project co-funded by the European
Commission within the FP7 Information and Communication Technologies
Work Programme. This 4-year project comprises leading Linked Open
Data technology researchers, companies, and service providers. Coming
from across 12 countries the partners are coordinated by the Agile
Knowledge Engineering and Semantic Web Research Group at the
University of Leipzig, Germany.

LOD2 will integrate and syndicate Linked Data with existing large-scale
applications. The project shows the benefits in the scenarios of Media and
Publishing, Corporate Data intranets and eGovernment.
Once per month the LOD2 webinar series offer a free webinar about
tools and services along the Linked Open Data Life Cycle.

Stay with us and learn more about acquisition, editing, composing,
connected applications – and finally publishing Linked Open Data.
The LOD2 Stack release 2.0
1. The LOD2 Stack: What, how, when?
2. Demo: enrichment with geospatial coordinates
3. Year 3 focus: a specialized LOD2 Stack for the Statistical Office
4. Questions
THE LOD2 STACK RELEASE 2.0
The Linked Open Data Life Cycle

                                     Inter-linking/
                                        Fusing


                         Manual                        Classifi-
                        revision/                       cation/
                        authoring                     Enrichment




             Storage/                                                Quality
             Querying                                               Analysis




                                                      Evolution /
                        Extraction
                                                        Repair


                                       Search/
                                     Browsing/
                                     Exploration
LOD2 stack v3 =             2013
          More inter component integration



                 LOD2 stack v2 =             2012
More components + more inter component integration


                                               2011
          LOD2 stack v1 = Debian repository




Sindice Silk                                   2010
        Virtuoso    PoolParty
   D2R       Sigma.EE                     Dbpedia
     CKAN           OntoWiki                ORE
LOD2 stack Release 2                                                                              (Year 1)
                                                                   Silk
                                                                               Silk-latc          (Year 2)
                                                          Limes
                                           ontowiki
                                                                                      Sieve
                     RDFAuthor


                             PoolParty                                                        DL-Learner



               sparqlED


      sparqlproxy
                                                                 LOD2
                                                                                                           ORE
     Virtuoso RDF Store
         (conductor,
                                                                 Stack
     sparql, isparql, ods)



                          Virtuoso
      PoolParty
                          sponger
      Extractor
                                                                                              LODgrefine

                               Dbpedia
           stanbol
                               Spotlight
                                                      Semantic
                                                       Spatial                  SigmaEE
                  D2R            valiant
                                                      Browser
                                                                  lod2webapi
LOD2 stack contribution process

                                    Debian
              Component                                     Component Owner
                                    Package


                                                           LOD2 stack maintainer
                                   LOD2 Stack
                                     testing


                                                feedback
• Does the Debian package works?
• Does it break flows | UI ?         Valid?



                                   LOD2 Stack
                                     Stable
LOD2 stack prerequisites & support


•   The component providers are responsible for the Debian package
     –   the knowledge and experience with packaging increases
     –   Improves the overall quality of the individual components

•   The LOD2 stack standardizes on Ubuntu 12.04 LTS, Precise edition
     –   Other Linux distributions are in principle possible
     –   Our partner I2G, Poland, successfully installed a version on Debian

•   Requires 2GB RAM, better at least 4GB
     –   Many components are tomcat based web-apps
     –   Footprint can be reduced by only installing the needed applications for your case

•   Technical feedback on the stack via support-stack@lod2.eu
Demo Scenario


• Linked Data has the ability to merge and enrich your data.

• Show that with a few steps this promise comes close to reality.
The demo scenario
The demo scenario


             1. Upload the courts from
            vocabulary.wolterskluwer.de



                                                 2. Extract data from the German DBpedia


                          3. Link the datasets


                                                                 4. Exploit the links to
                                                                 enrich the courts




                                                              5. Display the result
The demo scenario


                  1. Upload the courts from
                 vocabulary.wolterskluwer.de           SPARQLED

     PoolParty                                        2. Extract data from the German DBpedia


                               3. Link the datasets


                                                                      4. Exploit the links to   Virtuoso
                                                                      enrich the courts



                          SILK

                                                                   5. Display the result



                                                                                               Semantic
                                                                                            Spatial Browser
More inter component integration


•   The consortium’s goal is higher inter component integration
     –   Smoothen information flow between components                            2012
                                                                                  2012
•   It is a challenge!
     –   Integration in a general context does not lead to high end-user satisfaction

•   Focus on one domain
     –   Create supportive end-user process flows for this case
     –   They will be described and very likely many of them are applicable for other domains.
The Statistical Office

Selected because …
• many partners deal with statistical data in their projects
     –   The LOD2 consortium is involved in all key aspects:
           • standarization of the schema (DataCube)
           • publishing statistical data (e.g. http://eurostat.linked-statistics.org,
             http://scoreboard.lod2.eu, http://rs.ckan.net/dataset?q=rdf )
           • Tools (e.g. Cubeviz)

•   real world statistical data is accessible for experimentation

•   it offers excellent potential to combine components from LOD2 stack

•   the data integration capabilities of RDF can be exploited
•   the Linked Data paradigm is an enabler to go beyond classical statistics
    management
example scenario

           Downloading     Cleaning        Visualization
           tabular data      RDF              RDF




             Cleaning      Enrichment
              tabular       of the        Publishing
               data          data




                           Transforming
            Harmonizing
            tabular data        into
                           DataCube
example scenario

           Downloading      ORE
                           Cleaning        Visualization
           tabular data      RDF          CubeViz
                                               RDF
                           Sieve




            Cleaning
          LOD enabled      Enrichment
             tabular
                            SILK
                            of the        Publishing
          Open Refine                      CKAN
              data         Limes
                             data




                           Transforming
            Harmonizing
          PoolParty
            tabular data        into
                           DataCube
The Serbian Statistical Office using the LOD2 Stack
•   Our partner IMP collaborates with the Serbian National Statistical Office to
    make their information available to the public as Linked Data.
•   The next video demonstrates how LOD2 Stack components are used
Publink 2013

•   Free Linked Open Data Consultancy for government related organizations
     –   provides your organization with information and coaching around publishing Linked Open Data


•   More details & application info at http://lod2.eu/Article/Publink.html
Jingle          R.E.M., Martin Kaltenb ck, Florian Kondert
Coordination    Thomas Thurner
                Martin Kaltenb ck
Moderation      Martin Kaltenb ck
Presented by Bert Van Nuffelen
LOD2 STACK is realized by the effort from many persons in the LOD2 consortium:
Sebastian T, Valentina, Uros, Vuk, Helmut, Hugh, Robert, Mateja, Jan and many more ...
Hope you enjoyed staying with us – if you need more detailed
information, visit us at www.lod2.eu and let us know how we can
improve to meet your expectations!

Don’t forget to register for our next webinar

 Jan 2013 - Zemanta
 feb 2013 – CKAN and publicdata.eu (Open Knowledge Foundation)

Have a great day and don’t forget ...
LOD2 Webinar: The 2nd release of the LOD2 stack

Contenu connexe

Similaire à LOD2 Webinar: The 2nd release of the LOD2 stack

SSONDE: Semantic Similarity On liNked Data Entities
SSONDE: Semantic Similarity On liNked Data EntitiesSSONDE: Semantic Similarity On liNked Data Entities
SSONDE: Semantic Similarity On liNked Data EntitiesRiccardo Albertoni
 
Node.js Explained
Node.js ExplainedNode.js Explained
Node.js ExplainedJeff Kunkle
 
Putting it all together for digital assets
Putting it all together for digital assetsPutting it all together for digital assets
Putting it all together for digital assetsJon Morley
 
Rdf Processing For Java A Comparative Study
Rdf Processing For Java    A Comparative StudyRdf Processing For Java    A Comparative Study
Rdf Processing For Java A Comparative Studyioanid
 
Introduction to Apache Spark
Introduction to Apache Spark Introduction to Apache Spark
Introduction to Apache Spark Hubert Fan Chiang
 
Session 49 - Semantic metadata management practical
Session 49 - Semantic metadata management practical Session 49 - Semantic metadata management practical
Session 49 - Semantic metadata management practical ISSGC Summer School
 
An Introduction to SOPAC
An Introduction to SOPACAn Introduction to SOPAC
An Introduction to SOPACJohn Blyberg
 
Semantic Technologies and Triplestores for Business Intelligence
Semantic Technologies and Triplestores for Business IntelligenceSemantic Technologies and Triplestores for Business Intelligence
Semantic Technologies and Triplestores for Business IntelligenceMarin Dimitrov
 
Git Presentation - Purple Scout AB Malmö
Git Presentation - Purple Scout AB MalmöGit Presentation - Purple Scout AB Malmö
Git Presentation - Purple Scout AB MalmöEmil Erlandsson
 
NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud
NERD meets NIF:  Lifting NLP Extraction Results to the Linked Data CloudNERD meets NIF:  Lifting NLP Extraction Results to the Linked Data Cloud
NERD meets NIF: Lifting NLP Extraction Results to the Linked Data CloudGiuseppe Rizzo
 
Session 49 Practical Semantic Sticky Note
Session 49 Practical Semantic Sticky NoteSession 49 Practical Semantic Sticky Note
Session 49 Practical Semantic Sticky NoteISSGC Summer School
 
ドワンゴでのScala活用事例「ニコニコandroid」
ドワンゴでのScala活用事例「ニコニコandroid」ドワンゴでのScala活用事例「ニコニコandroid」
ドワンゴでのScala活用事例「ニコニコandroid」Satoshi Goto
 
Sem tech 2011 v8
Sem tech 2011 v8Sem tech 2011 v8
Sem tech 2011 v8dallemang
 

Similaire à LOD2 Webinar: The 2nd release of the LOD2 stack (20)

Yokozuna
YokozunaYokozuna
Yokozuna
 
Limes webinar
Limes webinarLimes webinar
Limes webinar
 
LOD2 Webinar Series: LIMES
LOD2 Webinar Series: LIMESLOD2 Webinar Series: LIMES
LOD2 Webinar Series: LIMES
 
SSONDE: Semantic Similarity On liNked Data Entities
SSONDE: Semantic Similarity On liNked Data EntitiesSSONDE: Semantic Similarity On liNked Data Entities
SSONDE: Semantic Similarity On liNked Data Entities
 
Node.js Explained
Node.js ExplainedNode.js Explained
Node.js Explained
 
Putting it all together for digital assets
Putting it all together for digital assetsPutting it all together for digital assets
Putting it all together for digital assets
 
OSGi Community Updates 2012
OSGi Community Updates 2012OSGi Community Updates 2012
OSGi Community Updates 2012
 
Rdf Processing For Java A Comparative Study
Rdf Processing For Java    A Comparative StudyRdf Processing For Java    A Comparative Study
Rdf Processing For Java A Comparative Study
 
LOD2 Plenary Vienna 2012: WP6 - Interfaces, Integration & LOD2 Stack
LOD2 Plenary Vienna 2012: WP6 - Interfaces, Integration & LOD2 StackLOD2 Plenary Vienna 2012: WP6 - Interfaces, Integration & LOD2 Stack
LOD2 Plenary Vienna 2012: WP6 - Interfaces, Integration & LOD2 Stack
 
Free Webinar: LOD2 Stack - 1st release
Free Webinar: LOD2 Stack - 1st releaseFree Webinar: LOD2 Stack - 1st release
Free Webinar: LOD2 Stack - 1st release
 
Introduction to Apache Spark
Introduction to Apache Spark Introduction to Apache Spark
Introduction to Apache Spark
 
Session 49 - Semantic metadata management practical
Session 49 - Semantic metadata management practical Session 49 - Semantic metadata management practical
Session 49 - Semantic metadata management practical
 
An Introduction to SOPAC
An Introduction to SOPACAn Introduction to SOPAC
An Introduction to SOPAC
 
Semantic Technologies and Triplestores for Business Intelligence
Semantic Technologies and Triplestores for Business IntelligenceSemantic Technologies and Triplestores for Business Intelligence
Semantic Technologies and Triplestores for Business Intelligence
 
Git Presentation - Purple Scout AB Malmö
Git Presentation - Purple Scout AB MalmöGit Presentation - Purple Scout AB Malmö
Git Presentation - Purple Scout AB Malmö
 
NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud
NERD meets NIF:  Lifting NLP Extraction Results to the Linked Data CloudNERD meets NIF:  Lifting NLP Extraction Results to the Linked Data Cloud
NERD meets NIF: Lifting NLP Extraction Results to the Linked Data Cloud
 
Session 49 Practical Semantic Sticky Note
Session 49 Practical Semantic Sticky NoteSession 49 Practical Semantic Sticky Note
Session 49 Practical Semantic Sticky Note
 
Publishing Linked Data from RDB
Publishing Linked Data from RDBPublishing Linked Data from RDB
Publishing Linked Data from RDB
 
ドワンゴでのScala活用事例「ニコニコandroid」
ドワンゴでのScala活用事例「ニコニコandroid」ドワンゴでのScala活用事例「ニコニコandroid」
ドワンゴでのScala活用事例「ニコニコandroid」
 
Sem tech 2011 v8
Sem tech 2011 v8Sem tech 2011 v8
Sem tech 2011 v8
 

Plus de Semantic Web Company

How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...
How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...
How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...Semantic Web Company
 
Introduction to Knowledge Graphs and Semantic AI
Introduction to Knowledge Graphs and Semantic AIIntroduction to Knowledge Graphs and Semantic AI
Introduction to Knowledge Graphs and Semantic AISemantic Web Company
 
Deep Text Analytics - How to extract hidden information and aboutness from text
Deep Text Analytics - How to extract hidden information and aboutness from textDeep Text Analytics - How to extract hidden information and aboutness from text
Deep Text Analytics - How to extract hidden information and aboutness from textSemantic Web Company
 
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Leveraging Knowledge Graphs in your Enterprise Knowledge Management SystemLeveraging Knowledge Graphs in your Enterprise Knowledge Management System
Leveraging Knowledge Graphs in your Enterprise Knowledge Management SystemSemantic Web Company
 
Linking SharePoint Documents with Structured Data
Linking SharePoint Documents with Structured DataLinking SharePoint Documents with Structured Data
Linking SharePoint Documents with Structured DataSemantic Web Company
 
The Fast Track to Knowledge Engineering
The Fast Track to Knowledge EngineeringThe Fast Track to Knowledge Engineering
The Fast Track to Knowledge EngineeringSemantic Web Company
 
Leveraging Taxonomy Management with Machine Learning
Leveraging Taxonomy Management with Machine LearningLeveraging Taxonomy Management with Machine Learning
Leveraging Taxonomy Management with Machine LearningSemantic Web Company
 
PoolParty GraphSearch - The Fusion of Search, Recommendation and Analytics
PoolParty GraphSearch - The Fusion of Search, Recommendation and AnalyticsPoolParty GraphSearch - The Fusion of Search, Recommendation and Analytics
PoolParty GraphSearch - The Fusion of Search, Recommendation and AnalyticsSemantic Web Company
 
Semantics as the Basis of Advanced Cognitive Computing
Semantics as the Basis of Advanced Cognitive ComputingSemantics as the Basis of Advanced Cognitive Computing
Semantics as the Basis of Advanced Cognitive ComputingSemantic Web Company
 
PoolParty 6.0 - Climbing the Semantic Ladder
PoolParty 6.0 - Climbing the Semantic LadderPoolParty 6.0 - Climbing the Semantic Ladder
PoolParty 6.0 - Climbing the Semantic LadderSemantic Web Company
 
PoolParty Semantic Suite - Release 6.0 (Technical Overview)
PoolParty Semantic Suite - Release 6.0 (Technical Overview)PoolParty Semantic Suite - Release 6.0 (Technical Overview)
PoolParty Semantic Suite - Release 6.0 (Technical Overview)Semantic Web Company
 
Taxonomies and Ontologies – The Yin and Yang of Knowledge Modelling
Taxonomies and Ontologies – The Yin and Yang of Knowledge ModellingTaxonomies and Ontologies – The Yin and Yang of Knowledge Modelling
Taxonomies and Ontologies – The Yin and Yang of Knowledge ModellingSemantic Web Company
 
PROPEL . Austrian's Roadmap for Enterprise Linked Data
PROPEL . Austrian's Roadmap for Enterprise Linked DataPROPEL . Austrian's Roadmap for Enterprise Linked Data
PROPEL . Austrian's Roadmap for Enterprise Linked DataSemantic Web Company
 

Plus de Semantic Web Company (20)

How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...
How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...
How Enterprise Architecture & Knowledge Graph Technologies Can Scale Business...
 
Introduction to Knowledge Graphs and Semantic AI
Introduction to Knowledge Graphs and Semantic AIIntroduction to Knowledge Graphs and Semantic AI
Introduction to Knowledge Graphs and Semantic AI
 
Deep Text Analytics - How to extract hidden information and aboutness from text
Deep Text Analytics - How to extract hidden information and aboutness from textDeep Text Analytics - How to extract hidden information and aboutness from text
Deep Text Analytics - How to extract hidden information and aboutness from text
 
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Leveraging Knowledge Graphs in your Enterprise Knowledge Management SystemLeveraging Knowledge Graphs in your Enterprise Knowledge Management System
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
 
Linking SharePoint Documents with Structured Data
Linking SharePoint Documents with Structured DataLinking SharePoint Documents with Structured Data
Linking SharePoint Documents with Structured Data
 
The Fast Track to Knowledge Engineering
The Fast Track to Knowledge EngineeringThe Fast Track to Knowledge Engineering
The Fast Track to Knowledge Engineering
 
Semantic AI
Semantic AISemantic AI
Semantic AI
 
BrightTALK - Semantic AI
BrightTALK - Semantic AI BrightTALK - Semantic AI
BrightTALK - Semantic AI
 
PoolParty Semantic Classifier
PoolParty Semantic ClassifierPoolParty Semantic Classifier
PoolParty Semantic Classifier
 
Leveraging Taxonomy Management with Machine Learning
Leveraging Taxonomy Management with Machine LearningLeveraging Taxonomy Management with Machine Learning
Leveraging Taxonomy Management with Machine Learning
 
Taxonomies put in the right place
Taxonomies put in the right placeTaxonomies put in the right place
Taxonomies put in the right place
 
PoolParty GraphSearch - The Fusion of Search, Recommendation and Analytics
PoolParty GraphSearch - The Fusion of Search, Recommendation and AnalyticsPoolParty GraphSearch - The Fusion of Search, Recommendation and Analytics
PoolParty GraphSearch - The Fusion of Search, Recommendation and Analytics
 
Semantics as the Basis of Advanced Cognitive Computing
Semantics as the Basis of Advanced Cognitive ComputingSemantics as the Basis of Advanced Cognitive Computing
Semantics as the Basis of Advanced Cognitive Computing
 
Structured Content Meets Taxonomy
Structured Content Meets TaxonomyStructured Content Meets Taxonomy
Structured Content Meets Taxonomy
 
PoolParty 6.0 - Climbing the Semantic Ladder
PoolParty 6.0 - Climbing the Semantic LadderPoolParty 6.0 - Climbing the Semantic Ladder
PoolParty 6.0 - Climbing the Semantic Ladder
 
PoolParty Semantic Suite - Release 6.0 (Technical Overview)
PoolParty Semantic Suite - Release 6.0 (Technical Overview)PoolParty Semantic Suite - Release 6.0 (Technical Overview)
PoolParty Semantic Suite - Release 6.0 (Technical Overview)
 
Taxonomies and Ontologies – The Yin and Yang of Knowledge Modelling
Taxonomies and Ontologies – The Yin and Yang of Knowledge ModellingTaxonomies and Ontologies – The Yin and Yang of Knowledge Modelling
Taxonomies and Ontologies – The Yin and Yang of Knowledge Modelling
 
PROPEL . Austrian's Roadmap for Enterprise Linked Data
PROPEL . Austrian's Roadmap for Enterprise Linked DataPROPEL . Austrian's Roadmap for Enterprise Linked Data
PROPEL . Austrian's Roadmap for Enterprise Linked Data
 
Taxonomy Quality Assessment
Taxonomy Quality AssessmentTaxonomy Quality Assessment
Taxonomy Quality Assessment
 
Taxonomy-Driven UX
Taxonomy-Driven UXTaxonomy-Driven UX
Taxonomy-Driven UX
 

LOD2 Webinar: The 2nd release of the LOD2 stack

  • 1.
  • 2. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Programme. This 4-year project comprises leading Linked Open Data technology researchers, companies, and service providers. Coming from across 12 countries the partners are coordinated by the Agile Knowledge Engineering and Semantic Web Research Group at the University of Leipzig, Germany. LOD2 will integrate and syndicate Linked Data with existing large-scale applications. The project shows the benefits in the scenarios of Media and Publishing, Corporate Data intranets and eGovernment.
  • 3. Once per month the LOD2 webinar series offer a free webinar about tools and services along the Linked Open Data Life Cycle. Stay with us and learn more about acquisition, editing, composing, connected applications – and finally publishing Linked Open Data.
  • 4. The LOD2 Stack release 2.0
  • 5. 1. The LOD2 Stack: What, how, when? 2. Demo: enrichment with geospatial coordinates 3. Year 3 focus: a specialized LOD2 Stack for the Statistical Office 4. Questions
  • 6. THE LOD2 STACK RELEASE 2.0
  • 7. The Linked Open Data Life Cycle Inter-linking/ Fusing Manual Classifi- revision/ cation/ authoring Enrichment Storage/ Quality Querying Analysis Evolution / Extraction Repair Search/ Browsing/ Exploration
  • 8. LOD2 stack v3 = 2013 More inter component integration LOD2 stack v2 = 2012 More components + more inter component integration 2011 LOD2 stack v1 = Debian repository Sindice Silk 2010 Virtuoso PoolParty D2R Sigma.EE Dbpedia CKAN OntoWiki ORE
  • 9. LOD2 stack Release 2 (Year 1) Silk Silk-latc (Year 2) Limes ontowiki Sieve RDFAuthor PoolParty DL-Learner sparqlED sparqlproxy LOD2 ORE Virtuoso RDF Store (conductor, Stack sparql, isparql, ods) Virtuoso PoolParty sponger Extractor LODgrefine Dbpedia stanbol Spotlight Semantic Spatial SigmaEE D2R valiant Browser lod2webapi
  • 10.
  • 11. LOD2 stack contribution process Debian Component Component Owner Package LOD2 stack maintainer LOD2 Stack testing feedback • Does the Debian package works? • Does it break flows | UI ? Valid? LOD2 Stack Stable
  • 12. LOD2 stack prerequisites & support • The component providers are responsible for the Debian package – the knowledge and experience with packaging increases – Improves the overall quality of the individual components • The LOD2 stack standardizes on Ubuntu 12.04 LTS, Precise edition – Other Linux distributions are in principle possible – Our partner I2G, Poland, successfully installed a version on Debian • Requires 2GB RAM, better at least 4GB – Many components are tomcat based web-apps – Footprint can be reduced by only installing the needed applications for your case • Technical feedback on the stack via support-stack@lod2.eu
  • 13.
  • 14. Demo Scenario • Linked Data has the ability to merge and enrich your data. • Show that with a few steps this promise comes close to reality.
  • 16. The demo scenario 1. Upload the courts from vocabulary.wolterskluwer.de 2. Extract data from the German DBpedia 3. Link the datasets 4. Exploit the links to enrich the courts 5. Display the result
  • 17. The demo scenario 1. Upload the courts from vocabulary.wolterskluwer.de SPARQLED PoolParty 2. Extract data from the German DBpedia 3. Link the datasets 4. Exploit the links to Virtuoso enrich the courts SILK 5. Display the result Semantic Spatial Browser
  • 18.
  • 19. More inter component integration • The consortium’s goal is higher inter component integration – Smoothen information flow between components 2012 2012 • It is a challenge! – Integration in a general context does not lead to high end-user satisfaction • Focus on one domain – Create supportive end-user process flows for this case – They will be described and very likely many of them are applicable for other domains.
  • 20. The Statistical Office Selected because … • many partners deal with statistical data in their projects – The LOD2 consortium is involved in all key aspects: • standarization of the schema (DataCube) • publishing statistical data (e.g. http://eurostat.linked-statistics.org, http://scoreboard.lod2.eu, http://rs.ckan.net/dataset?q=rdf ) • Tools (e.g. Cubeviz) • real world statistical data is accessible for experimentation • it offers excellent potential to combine components from LOD2 stack • the data integration capabilities of RDF can be exploited • the Linked Data paradigm is an enabler to go beyond classical statistics management
  • 21. example scenario Downloading Cleaning Visualization tabular data RDF RDF Cleaning Enrichment tabular of the Publishing data data Transforming Harmonizing tabular data into DataCube
  • 22. example scenario Downloading ORE Cleaning Visualization tabular data RDF CubeViz RDF Sieve Cleaning LOD enabled Enrichment tabular SILK of the Publishing Open Refine CKAN data Limes data Transforming Harmonizing PoolParty tabular data into DataCube
  • 23. The Serbian Statistical Office using the LOD2 Stack • Our partner IMP collaborates with the Serbian National Statistical Office to make their information available to the public as Linked Data. • The next video demonstrates how LOD2 Stack components are used
  • 24.
  • 25. Publink 2013 • Free Linked Open Data Consultancy for government related organizations – provides your organization with information and coaching around publishing Linked Open Data • More details & application info at http://lod2.eu/Article/Publink.html
  • 26. Jingle R.E.M., Martin Kaltenb ck, Florian Kondert Coordination Thomas Thurner Martin Kaltenb ck Moderation Martin Kaltenb ck Presented by Bert Van Nuffelen LOD2 STACK is realized by the effort from many persons in the LOD2 consortium: Sebastian T, Valentina, Uros, Vuk, Helmut, Hugh, Robert, Mateja, Jan and many more ...
  • 27. Hope you enjoyed staying with us – if you need more detailed information, visit us at www.lod2.eu and let us know how we can improve to meet your expectations! Don’t forget to register for our next webinar Jan 2013 - Zemanta feb 2013 – CKAN and publicdata.eu (Open Knowledge Foundation) Have a great day and don’t forget ...