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PrIMe: a software engineering methodology for developing provenance-aware applications

Published: 10 November 2006 Publication History

Abstract

Provenance is a concept often used in the Art world to refer to the documented history of an artifact, providing information about the artifact's lineage and authenticity. Provenance-aware applications similarly allow their users to have confidence about the data they produce, and can enable users to make judgements relating to notions of trust, accountability, validation, replication and compliance of their data. PrIMe is a software engineering methodology for adapting applications to enable them to interact with a provenance middleware layer, thereby making them provenance-aware. Such applications allow users to answer questions about provenance use cases, which are descriptions of scenarios in which a user interacts with a system by performing particular functions on that system. In order to illustrate how PrIMe can make applications provenance-aware, an Organ Transplant Management example application is used.

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Cited By

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  • (2018)Behavioral Analysis of Scientific Workflows With Semantic InformationIEEE Access10.1109/ACCESS.2018.28780436(66030-66046)Online publication date: 2018
  • (2015)How much domain data should be in provenance databases?Proceedings of the 7th USENIX Conference on Theory and Practice of Provenance10.5555/2814579.2814588(9-9)Online publication date: 8-Jul-2015
  • (2015)Scientific provenance metadata capture and management using Semantic WebInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2015.07082910:2(123-138)Online publication date: 1-Jul-2015
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    cover image ACM Conferences
    SEM '06: Proceedings of the 6th international workshop on Software engineering and middleware
    November 2006
    74 pages
    ISBN:1595935851
    DOI:10.1145/1210525
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    Published: 10 November 2006

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    Author Tags

    1. data provenance
    2. distributed applications
    3. methodology
    4. provenance

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    Cited By

    View all
    • (2018)Behavioral Analysis of Scientific Workflows With Semantic InformationIEEE Access10.1109/ACCESS.2018.28780436(66030-66046)Online publication date: 2018
    • (2015)How much domain data should be in provenance databases?Proceedings of the 7th USENIX Conference on Theory and Practice of Provenance10.5555/2814579.2814588(9-9)Online publication date: 8-Jul-2015
    • (2015)Scientific provenance metadata capture and management using Semantic WebInternational Journal of Metadata, Semantics and Ontologies10.1504/IJMSO.2015.07082910:2(123-138)Online publication date: 1-Jul-2015
    • (2013)Using Provenance to Support Good Laboratory Practice in Grid EnvironmentsData Provenance and Data Management in eScience10.1007/978-3-642-29931-5_7(157-180)Online publication date: 2013
    • (2012)ProvManager: a provenance management system for scientific workflowsConcurrency and Computation: Practice & Experience10.1002/cpe.187024:13(1513-1530)Online publication date: 1-Sep-2012
    • (2011)SciProvProceedings of the Second international conference on Information technology in bio- and medical informatics10.5555/2035485.2035495(68-81)Online publication date: 31-Aug-2011
    • (2011)PrIMeACM Transactions on Software Engineering and Methodology10.1145/2000791.200079220:3(1-42)Online publication date: 26-Aug-2011
    • (2011)SciProv: An Architecture for Semantic Query in Provenance Metadata on e-Science ContextInformation Technology in Bio- and Medical Informatics10.1007/978-3-642-23208-4_7(68-81)Online publication date: 2011
    • (2010)Uncovering DEVS simulation behaviour throughout the open provenance modelProceedings of the 2010 Spring Simulation Multiconference10.1145/1878537.1878661(1-8)Online publication date: 11-Apr-2010
    • (2009)A model of process documentation to determine provenance in mash-upsACM Transactions on Internet Technology10.1145/1462159.14621629:1(1-31)Online publication date: 23-Feb-2009
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