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
收藏
页码：214 / 217
页数：4
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