SisGExp: Rethinking Long-Tail Agronomic Experiments
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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.
KeywordsProvenance R scripts Workflows Precision agriculture
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