Collaborative Computing: Networking, Applications, and Worksharing. 11th International Conference, CollaborateCom 2015, Wuhan, November 10-11, 2015, China. Proceedings

Research Article

Crowdstore: A Crowdsourcing Graph Database

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  • @INPROCEEDINGS{10.1007/978-3-319-28910-6_7,
        author={Vitaliy Liptchinsky and Benjamin Satzger and Stefan Schulte and Schahram Dustdar},
        title={Crowdstore: A Crowdsourcing Graph Database},
        proceedings={Collaborative Computing: Networking, Applications, and Worksharing. 11th International Conference, CollaborateCom 2015, Wuhan, November 10-11, 2015, China. Proceedings},
        proceedings_a={COLLABORATECOM},
        year={2016},
        month={2},
        keywords={Database theory Graph query languages Crowdsourcing},
        doi={10.1007/978-3-319-28910-6_7}
    }
    
  • Vitaliy Liptchinsky
    Benjamin Satzger
    Stefan Schulte
    Schahram Dustdar
    Year: 2016
    Crowdstore: A Crowdsourcing Graph Database
    COLLABORATECOM
    Springer
    DOI: 10.1007/978-3-319-28910-6_7
Vitaliy Liptchinsky,*, Benjamin Satzger1,*, Stefan Schulte2,*, Schahram Dustdar2,*
  • 1: Microsoft
  • 2: TU Wien
*Contact email: liptchinsky@dsg.tuwien.ac.at, benjamin.satzger@microsoft.com, schulte@dsg.tuwien.ac.at, dustdar@dsg.tuwien.ac.at

Abstract

Existing crowdsourcing database systems fail to support complex, collaborative or responsive crowd work. These systems implement human computation as independent tasks published online, and subsequently chosen by individual workers. Such pull model does not support worker collaboration and its expertise matching relies on workers’ subjective self-assessment. An extension to graph query languages combined with an enhanced database system components can express and facilitate social collaboration, sophisticated expert discovery and low-latency crowd work. In this paper we present such an extension, CRowdPQ, backed up by the database management system Crowdstore.