• DocumentCode
    162487
  • Title

    An Industrial Case Study on Provenance Awareness of Composite Services

  • Author

    Zerva, Paraskevi ; Hamadache, Kahina ; Angouras, George ; Zschaler, Steffen ; Miles, Simon

  • Author_Institution
    Dept. of Inf., King´s Coll., London, UK
  • fYear
    2014
  • fDate
    27-29 Aug. 2014
  • Firstpage
    92
  • Lastpage
    99
  • Abstract
    Provenance awareness adds a new dimension to the engineering of service-based systems, enabling them to increase their accountability through answering questions about the provenance of any data produced. Provenance awareness can be achieved by recording provenance data during system execution. In our previous work we have proposed an overall research agenda towards a design and analysis framework for provenance awareness of composite services. A fundamental element of this framework is the provenance model, Service Provontology, capturing the structure of the provenance data collected which allows designers to query and reason over provenance data instances of composite services. With this paper we contribute an industrial case study exploring real-world provenance data from a service-based system (ORBI). In our study ServiceProv becomes the tool for enabling representation and reasoning over ORB provenance data instances in order to answer specific provenance questions formalized as SPARQL expressions.
  • Keywords
    ontologies (artificial intelligence); query processing; question answering (information retrieval); ORB provenance data instances; ORBI; SPARQL expressions; ServiceProv ontology; composite services; provenance awareness; provenance data instance querying; provenance data recording; question answering; service-based system engineering; system execution; Analytical models; Cognition; Context; Data models; History; Ontologies; Servers; industrial case study; provenance awareness; provenance data; service based systems; service composition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantics, Knowledge and Grids (SKG), 2014 10th International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/SKG.2014.24
  • Filename
    6964670