Prov2ONE: An Algorithm for Automatically Constructing ProvONE Provenance Graphs

  • Ajinkya PrabhuneEmail author
  • Aaron Zweig
  • Rainer Stotzka
  • Michael Gertz
  • Juergen Hesser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9672)


Provenance traces history within workflows and enables researchers to validate and compare their results. Currently, modelling provenance in ProvONE is an arduous task and lacks an automated approach. This paper introduces a novel algorithm, called Prov2ONE that automatically generates the ProvONE prospective provenance for scientific workflows defined in BPEL4WS. The same prospective ProvONE graph is updated with the relevant retrospective provenance, preventing provenance to be captured in various non-standard provenance models and thus enabling research communities to share, compare and analyze workflows and its associated provenance. Finally, using the Prov2ONE algorithm, a ProvONE provenance graph for the nanoscopy workflow is generated.


ProvONE Proven Ones Provenance Graph Retrospective Provenance Scientific Workflows 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ajinkya Prabhune
    • 1
    Email author
  • Aaron Zweig
    • 1
  • Rainer Stotzka
    • 1
  • Michael Gertz
    • 2
  • Juergen Hesser
    • 3
  1. 1.Institute for Data Processing and ElectronicsKarslruhe Institute of TechnologyKarlsruheGermany
  2. 2.Institute of Computer ScienceHeidelberg UniversityHeidelbergGermany
  3. 3.Department of Radiation OncologyHeidelberg UniversityHeidelbergGermany

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