SisGExp: Rethinking Long-Tail Agronomic Experiments

  • Sergio Manuel Serra da CruzEmail author
  • José Antonio Pires do Nascimento
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9672)


Reproducibility is a major feature of Science. Even agronomic research of exemplary quality may have irreproducible empirical findings because of random or systematic error. This work presents SisGExp, a provenance-based approach that aid researchers to manage, share, and enact the computational scientific workflows that encapsulate legacy R scripts. SisGExp transparently captures provenance of R scripts and endows experiments reproducibility. SisGExp is non-intrusive, does not require users to change their working way, it wrap agronomic experiments as a scientific workflow system.


Provenance R scripts Workflows Precision agriculture 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sergio Manuel Serra da Cruz
    • 1
    Email author
  • José Antonio Pires do Nascimento
    • 1
  1. 1.UFRRJ – Universidade Federal Rural do Rio de JaneiroSeropédicaBrazil

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