SisGExp: Rethinking Long-Tail Agronomic Experiments

被引：2

作者：

Serra da Cruz, Sergio Manuel ^{[1
]}

Pires do Nascimento, Jose Antonio ^{[1
]}

机构：

[1] UFRRJ Univ Fed Rural Rio de Janeiro, Seropedica, RJ, Brazil

来源：

PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, IPAW 2016 | 2016年 / 9672卷

关键词：

Provenance; R scripts; Workflows; Precision agriculture;

D O I：

10.1007/978-3-319-40593-3_24

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：214 / 217

页数：4

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