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Architecture for Template-Driven Provenance Recording

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Provenance and Annotation of Data and Processes (IPAW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11017))

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Abstract

Provenance templates define abstract patterns of provenance data and have been shown to be useful when implementing support for provenance capture in existing software tools. Their strength is in exposing only the relevant provenance capture actions through a service interface, whilst hiding the complexities associated with managing the provenance data. We present an architecture for the creation and management of libraries of provenance documents constructed using templates.

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References

  1. Curcin, V., et al.: Templates as a method for implementing data provenance in decision support systems. J. Biomed. Inform. 65(1), 1–21 (2017)

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  2. Kostopoulou, O., et al.: Diagnostic accuracy of GPs when using an early-intervention decision support system: a high-fidelity simulation. Br. J. Gen. Pract. 67(656), e201–e208 (2017)

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Author information

Authors and Affiliations

  1. King’s College London, London, UK

    Elliot Fairweather, Pinar Alper, Talya Porat & Vasa Curcin

Authors
  1. Elliot Fairweather
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  2. Pinar Alper
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  3. Talya Porat
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  4. Vasa Curcin
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Corresponding author

Correspondence to Vasa Curcin .

Editor information

Editors and Affiliations

  1. Paris Dauphine University, Paris, France

    Khalid Belhajjame

  2. SRI International, Menlo Park, CA, USA

    Ashish Gehani

  3. University of Luxembourg, Belvaux, Luxembourg

    Pinar Alper

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© 2018 Springer Nature Switzerland AG

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Fairweather, E., Alper, P., Porat, T., Curcin, V. (2018). Architecture for Template-Driven Provenance Recording. In: Belhajjame, K., Gehani, A., Alper, P. (eds) Provenance and Annotation of Data and Processes. IPAW 2018. Lecture Notes in Computer Science(), vol 11017. Springer, Cham. https://doi.org/10.1007/978-3-319-98379-0_23

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  • DOI: https://doi.org/10.1007/978-3-319-98379-0_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98378-3

  • Online ISBN: 978-3-319-98379-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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