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Crowdsourcing ontology engineering. Elena Simperl Web and Internet Science, University of Southampton 11 April 2013. Overview. "online, distributed problem-solving and production model“ [ Brabham , 2008]

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crowdsourcing ontology engineering

Crowdsourcing ontology engineering

Elena Simperl

Web and Internet Science, University of Southampton 11 April 2013

overview
Overview
  • "online, distributed problem-solving and production model“ [Brabham, 2008]
  • Varieties: wisdom of the crowds/collective intelligence, open innovation, human computation...
  • Why is it a good idea?
    • Cost and efficiency savings
    • Wider acceptance, closer to user needs, diversity
  • Approaches
    • Collaborative ontology engineering
    • Challenges/competitions
    • Games with a purpose
    • Microtask/paid crowdsourcing
  • In combination with automatic techniques
crowdsourcing ontology alignment
Crowdsourcing ontology alignment
  • Experiments usingMTurk, CrowdFlowerandestablishedbenchmarks
  • Enhancingtheresultsofautomatictechniques
  • Fast, accurate, cost-effective

[Sarasua, Simperl, Noy, ISWC2012]

open questions
Open questions
  • Quality assurance and evaluation
  • Incentives and motivators
  • Choice of crowdsourcing approach and combinations of different approaches
  • Reusable collection of algorithms for quality assurance, task assignment, workflow management, results consolidation etc
  • Schemas recording provenance of crowdsourced data
  • Descriptive framework for classification of human computation systems
    • Typesoftasksandtheirmodeofexecution
    • Participantsandtheirroles
    • Interaction withsystemandamongparticipants
    • Validation ofresults
    • Consolidationandaggregationofinputsintocompletesolution
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