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Linked Data for the Masses: The
      approach and the Software
G. Anadiotis, P. Andriopoulos, P. Alexopoulos, D.
                Vekris, A. Zosakis
             IMC Technologies S.A.
      ELLAK conference 2010 – 15/5/2010
 Licensed under Creative Commons Attribution-
Noncommercial-Share Alike 3.0 Unported License


                Linked Data for the Masses          1
Presentation Structure


1. Introduction: From the World Wide Web to the Semantic
   Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work




                    Linked Data for the Masses             2
Presentation Structure


1. Introduction: From the World Wide Web to the Semantic
   Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work




                    Linked Data for the Masses             3
WWW Shortcomings

• Lack of structure: Information ≠ Data. The WWW gives
  access to information in the form of pages, thus mixing
  content with presentation. Data structure is missing,
  even if it is in fact available - e.g. the information
  presented resides in a Database.
• Lack of semantics: what does this mean? Even if we can
  separate presentation from content, there is no way to
  interpret the latter: it takes a human to 'understand' the
  meaning of the content, thus automatically combining
  and processing data on the web is next to impossible.



                      Linked Data for the Masses               4
The Semantic Web

•   The goal of dealing with these shortcomings gave birth to the
    Semantic Web, which aims to bring elements of Knowledge
    Representation and Artificial Intelligence to WWW in order to help it
    evolve.




                           Linked Data for the Masses                       5
Semantic Web Standards


•             XML (eXtended Markup Language) is a
    standard for data interoperability on the syntactic level.
•             RDF(S). RDF (Resource Description
    Framework) is a model to represent classes and their
    relationships that can also be represented in XML
    notation. RDF Schema defines a set of rules to describe
    RDF classes, properties and hierarchies.
•             OWL (Web Ontology Language) adds extra
    options to RDF(S).
•             SPARQL (Simple Protocol and RDF Query
    Language) is the equivalent of SQL for querying RDF
    data, as well as an access protocol via HTTP.

                        Linked Data for the Masses               6
The RDF Model

• RDF data is different than relational data in their
  underlying model: RDF is a graph
• RDF data are expressed as triples
• <subject><predicate><object> : <cat><is-a><mammal>
• RDF(S) provides a first layer of logic: classes and
  taxonomical relationships (hierarchy)
• OWL adds options for axiomatic restrictions and
  inference




                      Linked Data for the Masses        7
Linked Data


•   Linked Data is about using the Web to connect related data that
    wasn't previously linked, or using the Web to lower the barriers to
    linking data currently linked using other methods
•   Sir Tim Berners Lee set the 4 basic principles of Linked Data,
    aiming to get ‘the Web done right’.
•   Rely on existing standards and 4 basic principles:
    1. Use URIs as names for things
    2. Use HTTP URIs so that people can look up those names
    3. When someone looks up a URI, provide useful information, using the
       standards (RDF, SPARQL)
    4. Include links to other URIs, so that they can discover more things
•   Data structure and semantics specified via vocabularies/ontologies


                            Linked Data for the Masses                      8
The Linked Data cloud




Linked Data for the Masses   9
DBpedia

•   Extracts structured information from Wikipedia and publishes it as
    Linked Data.
•   Uses an OWL to represent and publish extracted information
     –   Places
     –   Person
     –   Organization
     –   …
•   Provides a SPARQL endpoint to access and query data
•   Extracted data stored in a cross-domain knowledge base (479
    million RDF triples)
•   2 versions available:
     – English
     – German

                            Linked Data for the Masses                   10
Presentation Structure


1. Introduction: From the World Wide Web to the Semantic
   Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work




                    Linked Data for the Masses             11
The Inbound/Outbound Linked Data
                            approach

• How can Linked Data be used in real-world applications?
• Each node/application in the Semantic Web can act as a
  Linked Data consumer (Inbound Linked Data) or provider
  (Outbound Linked Data), or both
• As a consumer, the benefit is obvious: applications may
  tap on a rich web database to enhance content and
  provide additional services




                     Linked Data for the Masses             12
The Inbound/Outbound Linked Data
                                  approach

•   As a provider, the benefits are perhaps less clear, yet definitely
    existing:




                            Linked Data for the Masses                   13
The Inbound/Outbound Linked Data
                              approach

• The approach was presented in the context of the 2009
  Linking Open Data Triplification Challenge, a contest
  organized by a group of experts and sponsored by Sir
  Tim Berners Lee, aiming to promote adoption of Linked
  Data by providing:
   – Open Linked Data Datasets
   – Opens software that can be used to produce Linked Data

• Outbound Linked Data application: Liferay Linked Data
  Module
• Inbound Linked Data application: Tag Disambiguiation


                       Linked Data for the Masses             14
Presentation Structure


1. Introduction: From the World Wide Web to the Semantic
   Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work




                    Linked Data for the Masses             15
Outbound Linked Data: Liferay Linked
                              Data Module

•   Liferay: open source Portal/CMS framework (Java, Portlet container)
    – Over 10 years of development
    – Extensive customer base: UN, Cisco, BMW, …




                          Linked Data for the Masses                      16
Outbound Linked Data: Liferay Linked
                          Data Module

• Make Liferay-generated content (blogs, web content,
  forums, wikis…) available as Linked Data
• Meta-information: users, groups, organizations, tags..
• SPARQL endpoint.
• Use of open source software: D2R Server + Mapping
  language
• Use of standard vocabularies
• Available on Sourceforge, LGPL license



                     Linked Data for the Masses            17
Knowledge Representation Vocabularies


• Using appropriate vocabularies for our content:
   – FOAF: Friend-Of-A-Friend
   – DC: Dublin Core
   – SIOC: Semantically Interlinked Online Communities
   – SKOS: Simple Knowledge Organization System
   – MOAT: Meaning Of A Tag

• Relying on standard vocabularies promotes
  interoperability and enables applications to process
  shared data seamlessly.




                       Linked Data for the Masses        18
D2R Server


•   Tool and mapping language to map relational databases to
    semantic vocabularies and publishing relational data as Linked Data
•   RDF data navigation and retrieval
•   SPARQL Endpoint
•   Mapping Liferay Server database to vocabularies of choice




                          Linked Data for the Masses                      19
Inbound Linked Data: Tag
                        Disambiguation Application

• Developed on Liferay Portal
• Provides a GUI for semantically specifying tag meanings
  in their context of use
• Useful for
   – Advanced search
   – Finding related concepts
   – Mapping tags
   – …

• Taps on DBpedia, using its concepts and an
  asynchronous query and matching mechanism

                        Linked Data for the Masses          20
Inbound Linked Data: Tag
                        Disambiguation Application

•   New blog entry, adding tag “Apple”




                        Linked Data for the Masses   21
Inbound Linked Data: Tag
                               Disambiguation Application

•       Interlink Tags
    –      Finding possible tag meanings
    –      Letting the user choose one




                               Linked Data for the Masses   22
Presentation Structure


1. Introduction: From the World Wide Web to the Semantic
   Web and Linked Data
2. The Inbound/Outbound Linked Data approach
3. Implementation: Standards and Software
4. Applications and Future Work




                    Linked Data for the Masses             23
Applications

• Liferay Linked Data Module is part of IMC Technologies’
  eDialogos platform for eParticipation
• Contextual distributed view retrieval application
• Creating a ‘Dialogue ecosystem’
   – Transparency - Accessibility: Open data
   – Compatibility: Direct access on the data level, removing the need
     for proprietary APIs




                        Linked Data for the Masses                       24
Extending standards:
                     eDialogos - eDeliberation Ontology

•   Relying on standard vocabularies to create our domain-specific
    eParticipation ontology




                          Linked Data for the Masses                 25
Dialogue Ecosystem




Linked Data for the Masses   26
The Future

• Collaboration with Liferay
   – Linked Data Module to be included in the official distribution in
     the future
   – Consulting with Liferay to include more advanced features

• Collaboration with DBpedia, Greek Universities
   – Creation of a Greek DBpedia

• Open sourcing eDialogos
   – Timeframe to be established in 2010




                          Linked Data for the Masses                     27
References

•   [1] Anadiotis, G., Andriopoulos, P., Vekris, D. and Zosakis, A. Linked
    data for the masses – using open source infrastructure and the
    inbound/outbound linked data approach to bring added value to end
    user applications. In I-KNOW 09 and I-SEMANTICS 09, 2009. See
    http://i-
    semantics.tugraz.at/2009/triplification/04_liferay_TriplificationChalle
    nge2009.pdf
•   [2] Liferay Linked Data Module:
    http://sourceforge.net/projects/liferayldm/
•   [3] Bryan Cheung (Liferay CEO), “Liferay Linked Data Module”,
    Liferay Blog, December 12, 2009. See
    http://www.liferay.com/web/bryan.cheung/blog/-/blogs/liferay-linked-
    data-module
•   [4] Anadiotis, G., Alexopoulos, P., Mpaslis, K., Zosakis, A.,
    Kafentzis, K. and Kotis, K. (2010). Facilitating Dialogue – Using
    Semantic Web Technology for eParticipation. Extended Semantic
    Web Conference, June 2010, Crete.

                            Linked Data for the Masses                        28
Questions




    ????




Linked Data for the Masses   29

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Linked Data for the Masses: The approach and the Software

  • 1. Linked Data for the Masses: The approach and the Software G. Anadiotis, P. Andriopoulos, P. Alexopoulos, D. Vekris, A. Zosakis IMC Technologies S.A. ELLAK conference 2010 – 15/5/2010 Licensed under Creative Commons Attribution- Noncommercial-Share Alike 3.0 Unported License Linked Data for the Masses 1
  • 2. Presentation Structure 1. Introduction: From the World Wide Web to the Semantic Web and Linked Data 2. The Inbound/Outbound Linked Data approach 3. Implementation: Standards and Software 4. Applications and Future Work Linked Data for the Masses 2
  • 3. Presentation Structure 1. Introduction: From the World Wide Web to the Semantic Web and Linked Data 2. The Inbound/Outbound Linked Data approach 3. Implementation: Standards and Software 4. Applications and Future Work Linked Data for the Masses 3
  • 4. WWW Shortcomings • Lack of structure: Information ≠ Data. The WWW gives access to information in the form of pages, thus mixing content with presentation. Data structure is missing, even if it is in fact available - e.g. the information presented resides in a Database. • Lack of semantics: what does this mean? Even if we can separate presentation from content, there is no way to interpret the latter: it takes a human to 'understand' the meaning of the content, thus automatically combining and processing data on the web is next to impossible. Linked Data for the Masses 4
  • 5. The Semantic Web • The goal of dealing with these shortcomings gave birth to the Semantic Web, which aims to bring elements of Knowledge Representation and Artificial Intelligence to WWW in order to help it evolve. Linked Data for the Masses 5
  • 6. Semantic Web Standards • XML (eXtended Markup Language) is a standard for data interoperability on the syntactic level. • RDF(S). RDF (Resource Description Framework) is a model to represent classes and their relationships that can also be represented in XML notation. RDF Schema defines a set of rules to describe RDF classes, properties and hierarchies. • OWL (Web Ontology Language) adds extra options to RDF(S). • SPARQL (Simple Protocol and RDF Query Language) is the equivalent of SQL for querying RDF data, as well as an access protocol via HTTP. Linked Data for the Masses 6
  • 7. The RDF Model • RDF data is different than relational data in their underlying model: RDF is a graph • RDF data are expressed as triples • <subject><predicate><object> : <cat><is-a><mammal> • RDF(S) provides a first layer of logic: classes and taxonomical relationships (hierarchy) • OWL adds options for axiomatic restrictions and inference Linked Data for the Masses 7
  • 8. Linked Data • Linked Data is about using the Web to connect related data that wasn't previously linked, or using the Web to lower the barriers to linking data currently linked using other methods • Sir Tim Berners Lee set the 4 basic principles of Linked Data, aiming to get ‘the Web done right’. • Rely on existing standards and 4 basic principles: 1. Use URIs as names for things 2. Use HTTP URIs so that people can look up those names 3. When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL) 4. Include links to other URIs, so that they can discover more things • Data structure and semantics specified via vocabularies/ontologies Linked Data for the Masses 8
  • 9. The Linked Data cloud Linked Data for the Masses 9
  • 10. DBpedia • Extracts structured information from Wikipedia and publishes it as Linked Data. • Uses an OWL to represent and publish extracted information – Places – Person – Organization – … • Provides a SPARQL endpoint to access and query data • Extracted data stored in a cross-domain knowledge base (479 million RDF triples) • 2 versions available: – English – German Linked Data for the Masses 10
  • 11. Presentation Structure 1. Introduction: From the World Wide Web to the Semantic Web and Linked Data 2. The Inbound/Outbound Linked Data approach 3. Implementation: Standards and Software 4. Applications and Future Work Linked Data for the Masses 11
  • 12. The Inbound/Outbound Linked Data approach • How can Linked Data be used in real-world applications? • Each node/application in the Semantic Web can act as a Linked Data consumer (Inbound Linked Data) or provider (Outbound Linked Data), or both • As a consumer, the benefit is obvious: applications may tap on a rich web database to enhance content and provide additional services Linked Data for the Masses 12
  • 13. The Inbound/Outbound Linked Data approach • As a provider, the benefits are perhaps less clear, yet definitely existing: Linked Data for the Masses 13
  • 14. The Inbound/Outbound Linked Data approach • The approach was presented in the context of the 2009 Linking Open Data Triplification Challenge, a contest organized by a group of experts and sponsored by Sir Tim Berners Lee, aiming to promote adoption of Linked Data by providing: – Open Linked Data Datasets – Opens software that can be used to produce Linked Data • Outbound Linked Data application: Liferay Linked Data Module • Inbound Linked Data application: Tag Disambiguiation Linked Data for the Masses 14
  • 15. Presentation Structure 1. Introduction: From the World Wide Web to the Semantic Web and Linked Data 2. The Inbound/Outbound Linked Data approach 3. Implementation: Standards and Software 4. Applications and Future Work Linked Data for the Masses 15
  • 16. Outbound Linked Data: Liferay Linked Data Module • Liferay: open source Portal/CMS framework (Java, Portlet container) – Over 10 years of development – Extensive customer base: UN, Cisco, BMW, … Linked Data for the Masses 16
  • 17. Outbound Linked Data: Liferay Linked Data Module • Make Liferay-generated content (blogs, web content, forums, wikis…) available as Linked Data • Meta-information: users, groups, organizations, tags.. • SPARQL endpoint. • Use of open source software: D2R Server + Mapping language • Use of standard vocabularies • Available on Sourceforge, LGPL license Linked Data for the Masses 17
  • 18. Knowledge Representation Vocabularies • Using appropriate vocabularies for our content: – FOAF: Friend-Of-A-Friend – DC: Dublin Core – SIOC: Semantically Interlinked Online Communities – SKOS: Simple Knowledge Organization System – MOAT: Meaning Of A Tag • Relying on standard vocabularies promotes interoperability and enables applications to process shared data seamlessly. Linked Data for the Masses 18
  • 19. D2R Server • Tool and mapping language to map relational databases to semantic vocabularies and publishing relational data as Linked Data • RDF data navigation and retrieval • SPARQL Endpoint • Mapping Liferay Server database to vocabularies of choice Linked Data for the Masses 19
  • 20. Inbound Linked Data: Tag Disambiguation Application • Developed on Liferay Portal • Provides a GUI for semantically specifying tag meanings in their context of use • Useful for – Advanced search – Finding related concepts – Mapping tags – … • Taps on DBpedia, using its concepts and an asynchronous query and matching mechanism Linked Data for the Masses 20
  • 21. Inbound Linked Data: Tag Disambiguation Application • New blog entry, adding tag “Apple” Linked Data for the Masses 21
  • 22. Inbound Linked Data: Tag Disambiguation Application • Interlink Tags – Finding possible tag meanings – Letting the user choose one Linked Data for the Masses 22
  • 23. Presentation Structure 1. Introduction: From the World Wide Web to the Semantic Web and Linked Data 2. The Inbound/Outbound Linked Data approach 3. Implementation: Standards and Software 4. Applications and Future Work Linked Data for the Masses 23
  • 24. Applications • Liferay Linked Data Module is part of IMC Technologies’ eDialogos platform for eParticipation • Contextual distributed view retrieval application • Creating a ‘Dialogue ecosystem’ – Transparency - Accessibility: Open data – Compatibility: Direct access on the data level, removing the need for proprietary APIs Linked Data for the Masses 24
  • 25. Extending standards: eDialogos - eDeliberation Ontology • Relying on standard vocabularies to create our domain-specific eParticipation ontology Linked Data for the Masses 25
  • 26. Dialogue Ecosystem Linked Data for the Masses 26
  • 27. The Future • Collaboration with Liferay – Linked Data Module to be included in the official distribution in the future – Consulting with Liferay to include more advanced features • Collaboration with DBpedia, Greek Universities – Creation of a Greek DBpedia • Open sourcing eDialogos – Timeframe to be established in 2010 Linked Data for the Masses 27
  • 28. References • [1] Anadiotis, G., Andriopoulos, P., Vekris, D. and Zosakis, A. Linked data for the masses – using open source infrastructure and the inbound/outbound linked data approach to bring added value to end user applications. In I-KNOW 09 and I-SEMANTICS 09, 2009. See http://i- semantics.tugraz.at/2009/triplification/04_liferay_TriplificationChalle nge2009.pdf • [2] Liferay Linked Data Module: http://sourceforge.net/projects/liferayldm/ • [3] Bryan Cheung (Liferay CEO), “Liferay Linked Data Module”, Liferay Blog, December 12, 2009. See http://www.liferay.com/web/bryan.cheung/blog/-/blogs/liferay-linked- data-module • [4] Anadiotis, G., Alexopoulos, P., Mpaslis, K., Zosakis, A., Kafentzis, K. and Kotis, K. (2010). Facilitating Dialogue – Using Semantic Web Technology for eParticipation. Extended Semantic Web Conference, June 2010, Crete. Linked Data for the Masses 28
  • 29. Questions ???? Linked Data for the Masses 29