ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs

Paolo Missier, J. Bryans, Carl Gamble, Vasa Curcin, Roxana Danger

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding

    Abstract

    Provenance metadata can be valuable in data sharing settings, where it can be used to help data consumers form judgements regarding the reliability of the data produced by third parties. However, some parts of provenance may be sensitive, requiring access control, or they may need to be simplified for the intended audience. Both these issues can be addressed by a single mechanism for creating abstractions over provenance, coupled with a policy model to drive the abstraction. Such mechanism, which we refer to as abstraction by grouping, simultaneously achieves partial disclosure of provenance, and facilitates its consumption. In this paper we introduce a formal foundation for this type of abstraction, grounded in the W3C PROV model; describe the associated policy model; and briefly present its implementation, the ProvAbs tool for interactive experimentation with policies and abstractions.
    Original languageEnglish
    Title of host publicationProvenance and Annotation of Data and Processes
    EditorsBertram Ludäscher, Beth Plale
    Place of PublicationCham
    PublisherSpringer Verlag
    Pages3-15
    Number of pages13
    Volume8628
    ISBN (Electronic)978-3-319-16462-5
    ISBN (Print)978-3-319-16461-8
    DOIs
    Publication statusPublished - 21 Mar 2015

    Keywords

    • Artificial Intelligence (incl. Robotics)
    • Database Management
    • Information Storage and Retrieval
    • Information Systems Applications (incl. Internet)
    • Management of Computing and Information Systems
    • Computers and Society

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  • Cite this

    Missier, P., Bryans, J., Gamble, C., Curcin, V., & Danger, R. (2015). ProvAbs: Model, Policy, and Tooling for Abstracting PROV Graphs. In B. Ludäscher, & B. Plale (Eds.), Provenance and Annotation of Data and Processes (Vol. 8628, pp. 3-15). Cham: Springer Verlag. https://doi.org/10.1007/978-3-319-16462-5_1