• DocumentCode
    249358
  • Title

    Provenance as a Service: A Data-centric Approach for Real-Time Monitoring

  • Author

    Hammad, Rafat ; Ching-Seh Wu

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Oakland Univ., Oakland, MI, USA
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    258
  • Lastpage
    265
  • Abstract
    Provenance of electronic data is an important piece of the metadata of a data object. Making systems provenance-aware can greatly benefit all parties involved. This paper discusses the importance of data provenance and presents an open cloud architecture named CloudProv, a framework to integrate, model, and monitor the provenance data. Our elastic cloud architecture will provide an open APIs which allows independent organizations to develop applications that can share and integrate provenance data across internal and external organizational boundaries. We propose a method to model the collected provenance information in such a way that can be used for continuous compliance monitoring and for root cause analysis. We have implemented a prototype of our framework, and used it to verify how we can generate a service model for provenance data using a small, but interesting set of data. We present a design of our proposed framework and its components along with a prototype implementation.
  • Keywords
    application program interfaces; cloud computing; data integration; meta data; open systems; software architecture; CloudProv framework; application development; continuous compliance monitoring; data object; data-centric approach; dependence service model; elastic cloud architecture; electronic data provenance; external organizational boundaries; internal organizational boundaries; metadata; open API; open cloud architecture; provenance data integration; provenance data modelling; provenance data monitoring; provenance data sharing; provenance information collection; provenance-as-a-service; provenance-aware systems; real-time data monitoring; root cause analysis; Adaptation models; Business; Cloud computing; Data models; Electronic mail; Engines; Monitoring; Provenance; cloud; data streams; distributed event-based systems; message dependence graph; provenance management; real-time monitoring; root cause analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2014 IEEE International Congress on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5056-0
  • Type

    conf

  • DOI
    10.1109/BigData.Congress.2014.46
  • Filename
    6906787