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Towards Complete Tracking of Provenance in Experimental Distributed Systems Research

  • Tomasz Buchert
  • Lucas Nussbaum
  • Jens Gustedt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9523)

Abstract

Running experiments on modern systems like supercomputers, cloud infrastructures or P2P networks became very complex, both technically and methodologically. It is difficult to re-run an experiment or understand its results even with technical background on the technology and methods used. Storing the provenance of experimental data, i.e., storing information about how the results were produced, proved to be a powerful tool to address similar problems in computational natural sciences. In this paper, we (1) survey provenance collection in various domains of computer science, (2) introduce a new classification of provenance types, and (3) sketch a design of a provenance system inspired by this classification.

Keywords

Business Process Modeling General Computing Experiment Description Data Provenance Provenance Information 
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 2015

Authors and Affiliations

  • Tomasz Buchert
    • 1
    • 2
    • 3
  • Lucas Nussbaum
    • 1
    • 2
    • 3
  • Jens Gustedt
    • 1
    • 4
    • 5
  1. 1.InriaVillers-lès-NancyFrance
  2. 2.Université de Lorraine, LORIANancyFrance
  3. 3.CNRS, LORIA - UMRNancyFrance
  4. 4.Université de StrasbourgStrasbourgFrance
  5. 5.CNRS, Icube - UMRStrasbourgFrance

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