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LOD2 Webinar Series Classification and Quality Analysis with DL Learner and ORE
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LOD2 Webinar Series Classification and Quality Analysis with DL Learner and ORE

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In this Webinar Lorenz Bühmann presents the ontology repair and enrichment tool ORE and also the DL-Learner , a machine learning tool to solve supervised learnings tasks and support knowledge …

In this Webinar Lorenz Bühmann presents the ontology repair and enrichment tool ORE and also the DL-Learner , a machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge. Those two beneighbored tools in the LOD2 Stack are for classification and the following quality analysis of Linked Data.

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  • 1. Creating Knowledge out of Interlinked Data LOD2 Webinar . 29.11.2011 . Page 1 http://lod2.eu
  • 2. Creating Knowledge out of Interlinked Data 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. LOD2 Webinar . 29.11.2011 . Page 2 http://lod2.eu http://lod2.eu
  • 3. Creating Knowledge out of Interlinked Data 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. LOD2 Webinar . 29.11.2011 . Page 3 http://lod2.eu http://lod2.eu
  • 4. Creating Knowledge out of Interlinked Data About me Lorenz Bühmann • • • Member of Agile Knowledge Engineering and Semantic Web research group (AKSW) since 2009 PhD Student at the University of Leipzig since 2011 Research Interests: – Machine Learning in Semantic Web – Ontology Debugging LOD2 Webinar . 29.11.2011 . Page 4 http://lod2.eu
  • 5. Creating Knowledge out of Interlinked Data Agile Knowledge Engineering and Semantic Web Research Group • • • Founded in 2006 30+ Researchers 3 Sub groups • Goals – – – • Contributing to the advancement of science in Semantic Web, Knowledge Engineering, Software Engineering Cost efficient, high-impact R&D, which proves usefulness at an early stage Bridge the gap between research results and applications Committed to Open Source, Open Access, and Open Knowledge movements LOD2 Webinar . 29.11.2011 . Page 5 http://lod2.eu
  • 6. Creating Knowledge out of Interlinked Data Agile Knowledge Engineering and Semantic Web Research Group EU Funded Projects: – Linked Open Data 2 (LOD2) – GeoKnow – BIG – BioASQ – LinkingLOD – Open Data Portal (ODP) • Further descriptions about projects can be found here: http://aksw.org/Projects Past EU funded Projects – LOD Around the Clock (LATC) – Semantic Content Management Systems for Enterprise Knowledge Management and News Mining (SCMS) – OntoWiki - Semantic Collaboration for Knowledge Management, ELearning and E-Tourism – ... LOD2 Webinar . 29.11.2011 . Page 6 http://lod2.eu
  • 7. Creating Knowledge out of Interlinked Data Project Page: http://aksw.org/Projects/ORE Source Code: https://github.com/AKSW/ORE Demo Page: http://ore.aksw.org/ LOD2 Webinar . 29.11.2011 . Page 7 http://lod2.eu
  • 8. Creating Knowledge out of Interlinked Data Agenda  Introduction and Motivation  Linked Data life cycle and role of ORE within LOD2  Knowledge Base Enrichment  Knowledge Base Repair  Demo  Future Work LOD2 Webinar . 28.11.2013 . Page 8 http://lod2.eu
  • 9. Creating Knowledge out of Interlinked Data Introduction • the quantity and size of RDF knowledge bases has significantly increased • many of those knowledge bases lack sophisticated schemata and instance data adhering to those schemata • for content extracted from legacy sources, crowdsourced content, but also manually curated content, it is challenging to ensure a coevolution of schemata and data, in particular for large knowledge bases • ontology modeling can be difficult and introduce unintended errors LOD2 Webinar . 28.11.2013 . Page 9 http://lod2.eu
  • 10. Creating Knowledge out of Interlinked Data Linked Data Life Cycle Manual revision authoring Interlinking Fusing Quality Analysis Storage Querying Extraction Search Browsing Exploration LOD2 Webinar . 28.11.2013 . Page 10 Classification Enrichment Evolution Repair http://lod2.eu
  • 11. Creating Knowledge out of Interlinked Data Knowledge Base Schema Enrichment Goal: Learn schema axioms in knowledge bases based on the instance data. Apply methods of Inductive Logic Programming(ILP): Positive examples + Negative examples + Background knowledge  Hypothesis ILP in Semantic Web:  OWL Axiom LOD2 Webinar . 28.11.2013 . Page 11 http://lod2.eu
  • 12. Creating Knowledge out of Interlinked Data Knowledge Base Schema Enrichment “How to describe a class MusicalArtist?” Positive Examples: Eric Clapton a Person; instrument Guitar; birthDate 1945-03-30. Elton John a Person; instrument Piano; birthDate 1947-03-25. Whitney Houston a Actor; instrument Vocals; birthDate 1963-08-09. Background Knowledge: Actor SubClassOf Person. Learned Axiom: MusicalArtist EquivalentTo Person and birthDate some xsd:date and instrument some Instrument We can derive from Tina Turner a Person; instrument Vocals; birthDate 1939-11-26. Tina Turner a MusicalArtist. LOD2 Webinar . 28.11.2013 . Page 12 http://lod2.eu
  • 13. Creating Knowledge out of Interlinked Data Knowledge Base Schema Enrichment “How to describe a property birthDate?” Positive Examples: Eric Clapton birthDate 1945-03-30. Elton John birthDate 1947-03-25. Whitney Houston birthDate 1963-08-09. Paracelsus birthDate 1493-11-11, 1493-12-17. Learned Axiom: Functional(birthDate) (3 out of 4 = 75%) LOD2 Webinar . 28.11.2013 . Page 13 http://lod2.eu
  • 14. Creating Knowledge out of Interlinked Data Knowledge Base Schema Enrichment Why schema enrichment? 1. The axioms serve as documentation for the purpose and correct usage of schema elements. 2. They improve the application debugging techniques. 3. Additional implicit information can be inferred. LOD2 Webinar . 28.11.2013 . Page 14 http://lod2.eu
  • 15. Creating Knowledge out of Interlinked Data Knowledge Base Schema Enrichment in ORE LOD2 Webinar . 28.11.2013 . Page 17 http://lod2.eu
  • 16. Creating Knowledge out of Interlinked Data Knowledge Base Repair Goal: Support in detection and repair of modelling errors and problems. ORE in its current version supports the detection and repair of • logical errors • naming problems by integrating the PatOMat framework • “missing data” LOD2 Webinar . 28.11.2013 . Page 18 http://lod2.eu
  • 17. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Logical Errors OWL based on Description Logics Common errors: • unsatisfiable classes • inconsistent ontology cannot have any individuals everything can be derived Both cases are quite easy for a reasoner to detect and for a tool to display when working on OWL ontologies. “Why is the class unsatisfiable?” “Why is the knowledge base inconsistent?” Explanations LOD2 Webinar . 28.11.2013 . Page 19 http://lod2.eu
  • 18. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Logical Errors in ORE LOD2 Webinar . 28.11.2013 . Page 20 http://lod2.eu
  • 19. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Naming Problems • analysis of the naming of entities across ontological structures can reveal • naming issues • underlying conceptualization issues • natural language structure influences the structure of formal knowledge bases and vice versa • content expressed in formal representation languages, such as the semantic web ones, should be accessible not only to logical reasoning machines but also to humans and NLP procedures, and thus resemble the natural language as much as possible Naming in ontologies matters LOD2 Webinar . 28.11.2013 . Page 21 http://lod2.eu
  • 20. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Naming Problems LOD2 Webinar . 28.11.2013 . Page 22 http://lod2.eu
  • 21. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Naming Problems Paper Accepted Rejected Paper AcceptedPaper LOD2 Webinar . 28.11.2013 . Page 23 RejectedPaper http://lod2.eu
  • 22. Creating Knowledge out of Interlinked Data Knowledge Base Repair of Naming Problems in ORE LOD2 Webinar . 28.11.2013 . Page 24 http://lod2.eu
  • 23. Creating Knowledge out of Interlinked Data Knowledge Base Repair by Validation of Constraints Constraints = OWL Axioms Example: Person SubClassOf birthDate some xsd:date “Every person has a birth date” OWL comes with the Open World Assumption(OWA), thus missing information is no error. We assume a Closed World Assumption, such that we can reuse OWL axioms as constraints. Basic Idea: Rewrite OWL axiom into SPARQL query LOD2 Webinar . 28.11.2013 . Page 25 http://lod2.eu
  • 24. Creating Knowledge out of Interlinked Data Knowledge Base Repair by Validation of Constraints Person SubClassOf birthDate some xsd:date SELECT ?s WHERE { ?s a :Person. FILTER NOT EXISTS { ?s :birthDate ?o. FILTER(DATATYPE(?o)=xsd:date) } } LOD2 Webinar . 28.11.2013 . Page 26 http://lod2.eu
  • 25. Creating Knowledge out of Interlinked Data Knowledge Base Repair by Validation of Constraints in ORE LOD2 Webinar . 28.11.2013 . Page 27 http://lod2.eu
  • 26. Creating Knowledge out of Interlinked Data Demonstration http://ore.aksw.org LOD2 Webinar . 28.11.2013 . Page 28 http://lod2.eu
  • 27. Creating Knowledge out of Interlinked Data Future Work  Enrichment  batch mode  Logical repair  detection of unsatisfiable classes on SPARQL knowledge bases  Constraint Validation  add repair option  SPIN support  (better) explanation why resources violate a constraint + support to add missing information LOD2 Webinar . 28.11.2013 . Page 29 http://lod2.eu
  • 28. Creating Knowledge out of Interlinked Data Further Information License: Apache License Version 2.0 Project page: http://aksw.org/Projects/ORE Source code: https://github.com/AKSW/ORE DL-Learner: http://dl-learner.org/ PatOMat: http://patomat.vse.cz/ LOD2 Webinar . 28.11.2013 . Page 30 http://lod2.eu
  • 29. Creating Knowledge out of Interlinked Data Contact Details Lorenz Bühmann Address Work: Augustusplatz 10, Room P618, 04109 Leipzig Email: buehmann@informatik.uni-leipzig.de Skype ID: lorenz.buehmann.uni LOD2 Webinar . 28.11.2013 . Page 31 http://lod2.eu
  • 30. Creating Knowledge out of Interlinked Data Credits Jingle Coordination R.E.M., Martin Kaltenböck, Florian Kondert Thomas Thurner Martin Kaltenböck Moderation Martin Kaltenböck Presented by Lorenz Bühmann LOD2 Webinar . 29.11.2011 . Page 32 http://lod2.eu
  • 31. Creating Knowledge out of Interlinked Data 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 20.12. 2011 - Virtuoso (Open Link Software) 24.01. 2012 - OntoWiki (University of Leipzig, Germany) Have a great day and don’t forget ... LOD2 Webinar . 29.11.2011 . Page 33 http://lod2.eu http://lod2.eu
  • 32. Creating Knowledge out of Interlinked Data LOD2 Webinar . 29.11.2011 . Page 34 http://lod2.eu http://lod2.eu

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