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Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
Doing Clever Things with the Semantic Web
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Doing Clever Things with the Semantic Web

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Invited talk at the EPIA 2011 conference

Invited talk at the EPIA 2011 conference

Published in: Technology, Education
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  • Would be nice to have a bit of loted here…
  • Transcript

    • 1. Doing Clever Things With the Semantic Web
      Mathieu d’Aquin
      Knowledge Media Institute, the Open University
    • 2. The Semantic Web
      Using the Web to publish, share and exploit information/knowledge
      From machines to machines
      Using graph-based data modeling, knowledge representation (ontologies) and reasoning
    • 3. Linked Data
      http://lucero-project.info/lb/what-is-linked-data/
      As set of principles and technologies for a Web of Data
      Putting the “raw” data online in a standard representation (RDF)
      Make the data Web addressable (URIs)
      Link to other Data
      http://linkeddata.org
    • 4. Galen
      NCI

      Music
      DC
      WORDNET
      RSS
      TAP
      FOAF




      Metadata
      <rdf:RDF>
      <channel rdf:about=“http://watson.kmi.open.ac.uk/blog”>
      <title>Elementaries - The Watson Blog</title>
      <link>http://watson.kmi.open.ac.uk:8080/blog/</link>
      <description>
      "Oh dear! Where the Semantic Web is going to go now?" -- imaginary user 23
      </description>
      <language>en</language>
      <copyright>Watson team</copyright>
      <lastBuildDate>Thu, 01 Mar 2007 13:49:52 GMT</lastBuildDate>
      <generator>Pebble (http://pebble.sourceforge.net)</generator>
      <docs>http://backend.userland.com/rss</docs>

      <rdf:RDF>
      <foaf:Imagerdf:about='http://static.flickr.com/132/400582453_e1e1f8602c.jpg'>
      <dc:title>Zen wisteria</dc:title>
      <dc:description></dc:description>
      <foaf:pagerdf:resource='http://www.flickr.com/photos/xcv/400582453/'/>
      <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/vittelgarden/'/>
      <foaf:topicrdf:resource='http://www.flickr.com/photos/tags/wisteria/'/>
      <dc:creator>
      <foaf:Person><foaf:name>Mathieu d'Aquin</foaf:name>

      <rdf:RDF>
      <owl:Ontology rdf:about="">
      <owl:imports rdf:resource="http://usefulinc.com/ns/doap#"/>
      </owl:Ontology>
      <j.1:Organization rdf:ID="KMi">
      <rdfs:comment rdf:datatype="http://www.w3.org/2001/XMLSchema#string"
      >The Knoledge Media Institute of the Open University, Milton Keynes UK</rdfs:comment>
      </j.1:Organization>
      <j.1:Document rdf:ID="KMiWebSite">

      UoD
    • 5. The Semantic Web
      Knowledge/
      Problem Solving Methods
      Semantic Web Applications
      Doing Clever Things With the Semantic Web
      Intelligent Agent
      Smart Features
      Clever Things…
    • 6. What I Want to Talk About
      Using the Semantic Web as A Knowledge Base
      KMi Watson and Finding Ontologies
      Doing More with Links
      Exploring the Web of Data
      Back to the Future
      AI + Linked Data = Semantic Web?
    • 7. Using the Semantic Web
      Need for a Gateway to the Semantic Web
      Dynamically retrieving, exploiting and combining relevant semantic resources from the Semantic Web
    • 8. KMi Watson
    • 9. Architecture
    • 10. Interface
      http://watson.kmi.open.ac.uk
      Watson: More than a Semantic Web Search Engine, Semantic Web Journal
    • 11. Watson as a Service
      Providing Web accessible APIs to a collection of online ontologies and semantic data sources
    • 12. Chose an entity to search
      Integrate statements
      Into the edited ontology
      Get entities from online ontologies
      Example Application: Ontology Construction
      Reusing Knowledge from the Semanrtic Web with the Watson Plugin, Demo at ISWC 2008
    • 13. Concept Relation Discovery
      SeaFood
      Meat
      wine.owl
      AcademicStaff
      Semantic Web
      Semantic Web
      Researcher
      ka2.rdf
      Meat
      SeaFood
      Ham
      pizza-to-go
      NALT
      AcademicStaff
      Researcher
      Ham
      SeaFood
      ISWC
      SWRC
      NALT
      Agrovoc
    • 14. Exploring the Semantic Web as Background Knowledge for Ontology Matching, Journal of Data Semantics
    • 15. PowerAqua: Question Answering
    • 16. From Semantic Web Research to Linked Data Applications
      Watson as a platform to research applications and techniques on top of semantic web resources
      But how can the Semantic Web be exploited and used in real-world application?
      Starting from what we know best…
    • 17. Applying Linked Data
      The Open University is the largest University in the UK, where all the courses are realized at a distance
      Creating the first University Linked Data platform: data.open.ac.uk
      Demonstrate the value of the technology and push the research through real-world scenarios
    • 18. data.open.ac.uk
    • 19. Applications
      Mobile and Personal Semantics
      Social
      Resource Discovery
      Research
      Exploration
    • 20. Example application: Finding relevant resources
      Zablithet al, LinkedLearning 2011
    • 21. Data as Web resources, accessible everywhere
    • 22. See also: Zablith et al., COLD 2011
    • 23. http://people.kmi.open.ac.uk/mathieu/about/discobro-discovering-linked-datat-resources-while-browsing/
      http://discovery.ac.uk/developers/competition/
    • 24. Supporting Researchers: The Reading Experience Database
      http://www.open.ac.uk/Arts/reading/
      40,000 accounts of somebody reading something at some time in some place
      Used by researchers in literature and history to explore research hypotheses
    • 25. Event
      Location
      locatedIn
      subClassOf
      subClassOf
      Experience
      City
      Country
      date: Date
      readerInvolved
      originCountry
      textInvolved
      occupation
      givesBackgroundTo
      Person
      religion
      gender
      creator/editor
      LinkedEvent Ontology
      Document
      CITO Citation Ontology
      Dublin Core
      title: String
      description: String
      published: Date
      providesExcerptFor
      FOAF
      DBPedia
    • 26.
    • 27. Back to the Future
      The Semantic Web is both a vision and a reality
      Making the Web more than a network of documents: the biggest, most distributed knowledge base ever
      What could AI do with such a knowledge base?
    • 28. Linked Data Mining
      Finding unexpected patterns in the use of the distributed data graph
    • 29. Linked Data Mining: Example
      Using Formal Concept Analysis + Reasoning to build a hierarchy of questions a linked dataset can answer
      Use statistical metrics to identify the ones that are most likely to be interesting
      Extracting Relevant Questions to an RDF Dataset Using Formal Concept Amalysis at KCAP 2011
      http://lucero-project.info/lb/2011/06/what-to-ask-linked-data/
    • 30.
    • 31.
    • 32. Reasoning
      To analyze and understand raw data in relation with online resources
      Example: Online personal information management
      Online Activities Ontology
      HTTP Ontology
      Parameters and Website info.
      Web Site Information
      Personal Information
      Trust Model
      Location Information
    • 33. Enriched with linked data
      Google Services
      Entertainment Websites
      Web Analytics
      Internet Search Engine
      subject/category
      Video sharing
      Video Hosting
      www.google-analytics.com
      Company
      developer
      Web Search Engine
      Search Engine
      type
      subject/category
      google
      owner
      subsediaryOf
      www.youtube.com
      www.google.com
      parent
      DBpedia
      freebase
    • 34. Basic processing/analysis
      Requests by time of day
      Requests by User Agents
      Interests
      Trust
    • 35. http://uciad.info
      http://uciad.info
    • 36. Understanding knowledge representation and data modeling
      The Semantic Web also represents a very large, collaborative base of formally represented knowledge
      This can also be mined, to discover things about knowledge representation and data modeling
    • 37. Ontologies on the Semantic Web
      Underlying description logic
      Number of entities
      Domain covered
    • 38. Relationships between ontologies
      DOOR: Towards a Formalization of Ontology Relations at KEOD 2009
    • 39. Detecting versions of ontologies
      When published on the Web, the information about the evolution of ontologies is lost
      Using URI patterns to find candidate versions of ontologies
      http://loki.cae.drexel.edu/wbs/ontology/2003/10/iso-metadata
      http://loki.cae.drexel.edu/wbs/ontology/2004/01/iso-metadata
      Applying machine learning algorithms (SVM, Naïve Bayes and Decision tree to recognize chains of versions of ontologies
      Allocca at ESWC 2011
      Obtained 90% Precision (SVM)
      Collected thousands of ontology version sequences to be analysed
      For example, distribution of similarity in version and non-version ontologies (right)
    • 40. Agreement/Disagreement between ontologies
      Ontologies are knowledge artifacts, they express opinions and beliefs and contradict each others
      Assessing (dis)agreement in ontologies is very useful to understand how to combine knowledge from different sources
    • 41. Assessing Statements related to SeaFood
      Nb1: #ontologies in which the statement appears.Nb2: #ontologies containing entities matching the subject and object of the statement.
      a: global agreement, d: global disagreement, cs: consensus, ct: controversy
    • 42. 21 different ontologies with a SeaFood concept
      Disagreement
      Agreement
      Formally Measuring Agreement and Disagreement in Ontologies at K-CAP 2009
    • 43. http://uciad.info
      Vegan subClass Vegetarian
      SeaFoodsubClassOf Meat
      SeaFooddisjointWith Meat
    • 44. The brighter the blue the higher the positive consensus (higher agreement)
      The brighter the red the lower the negative consensus (higher disagreement)
      Dark = controversy: no clear cut between disagreement and agreement
      Example: The statements attached to the class Employee are controversial: some ontologies agree, others disagree (often due to alternative representations of roles)
      AKT Portal
      Using consensus to assess an ontology(a new NeOn toolkit plugin
      Visualizing Consensus with Online Ontologies to Support Quality in Ontology Development at ONTOQUAL@EKAW 2010
    • 45. So my point is…
      The Semantic Web is a fantastic open field for AI
      It is going to become omnipresent, hidden, personal
      Exploring, Exploiting and Excavating the Semantic Web for
      Research in technology (creating it and studying it)
      Research in other areas
      Everyday tasks
      Still, after 10 years of research, represent new directions for many fields of the AI community, with their own issues, challenges and applications
    • 46. Thank You!
      More at:
      http://people.kmi.open.ac.uk/mathieu
      m.daquin@open.ac.uk
      @mdaquin

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