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Link Sets And Why They Are Important (EDF2012)
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Link Sets And Why They Are Important (EDF2012)

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  • 1. Link Sets and Why They ARE Important Anja Jentzsch, Freie Universität Berlin 6 June 2012 Realising and Exploiting the EU data cloud European Data Forum, Copenhagen, Denmark
  • 2. Outline 1.  Motivation 2.  Link Creation Process 3.  LATC Platform
  • 3. Links •  4th Linked Data principle: set RDF links to other data sources on the Web •  fundamental to the Web of Data •  connect data islands into a global, interconnected data space •  enable discovery of additional data sources
  • 4. Links •  Definition: Anexternal RDF link is an RDF triple in which the subject of the triple is a URI reference in the namespace of one data set, while the predicate and/or object of the triple are URI references pointing into the namespaces of other data sets.
  • 5. Link Types 1.  Relationship Links point at related things in other data sources, for instance, other people, places or genes. 2.  Identity Links point at URI aliases used by other data sources to identify the same real-world object or abstract concept. 3.  Vocabulary Links point from data to the definitions of the vocabulary terms that are used to represent the data, as well as from these definitions to the definitions of related terms in other vocabularies.
  • 6. Motivation •  Web of Data is a single global data space because data sources are connected by links •  Over 30 billion triples published as Linked Open Data (09/19/2011) •  But: •  Less than 500 million links •  Most publishers only link to one other dataset LOD data sets by the number of other data sources that are target of outgoing RDF links.
  • 7. State of the LOD Cloud http://lod-cloud.net/state
  • 8. Challenges for Link Discovery •  Large range of domains •  277 data sources in the LOD cloud from a variety of domains Link distribution by topical domain
  • 9. Link Discovery Tools •  Tools enable data publishers to set links •  Most tools generate links based on user-defined linkage rules •  A linkage rule specifies the conditions data items must fulfill in order to be interlinked •  Popular Link Discovery Tools: •  Silk Link Discovery Framework •  LIMES •  Others: http://esw.w3.org/TaskForces/CommunityProjects/LinkingOpenData/ EquivalenceMining
  • 10. (Simplified) Linking Workflow Select Datasets Write Linkage Rule Generate Links • Select two data sources • Specifies how two • Locally or on a Hadoop• Select the entity types entities are compared Cluster to be interlinked • Can be written manually • Write Links to file or a or learned triple store
  • 11. Silk Workbench •  Web application which guides the user through the process of interlinking different data sources •  Enables the user to manage different sets of data sources and linking tasks •  Offers a graphical editor which enables the user to easily create and edit linkage rules •  Offers tools to evaluate the current linkage rule •  Includes support for learning linkage rules
  • 12. LATC Platform
  • 13. LATC Workbench •  Project in Workspace consists of: •  Data Sources •  Holds all information that is needed to retrieve entities from it  •  E.g. a file dump or a SPARQL endpoint •  Linking Tasks •  Interlinks a type of entity between two data sources •  e.g. Interlinking movies in DBpedia and LinkedMDB
  • 14. LATC Linkage Rule Editor •  Allows to view and edit linkage rules •  Linkage Rules are shown as a tree •  Editing using drag & drop
  • 15. Learning Linkage Rules •  Linkage Rules can be learned interactively •  Can be used to generate new linkage rules or to improve existing rules •  Learned Linkage Rule can be viewed and edited by the user
  • 16. Example Linking with LATC Workbench
  • 17. LATC Console
  • 18. LATC Quality Assurance Module
  • 19. References LATC Project: http://latc-project.eu/ LATC Platform: http://latc-project.eu/platform/ Silk Link Discovery Framework: http://www4.wiwiss.fu-berlin.de/silk/