Towards fast prototyping of cloud-based environmental decision support systems for environmental scientists using R Shiny and Docker

被引:11
作者
Li, Yu [1 ]
机构
[1] Swiss Fed Inst Technol, Dept Civil Environm & Geomat Engn, Inst Environm Engn, Zurich, Switzerland
关键词
Web-based EDSS; Free and open-source software (FOSS); R shiny; Docker; Groundwater model; Crop model; MODEL; TOOLS;
D O I
10.1016/j.envsoft.2020.104797
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Environmental decision support systems (EDSS) have drawn an increasing attention among scientists to tackle with the growing complexity of environmental problems and to support policy makers. Yet, many EDSS reported in literature are case specific, fragmented in development strategies and under-reporting server setup, thus impeding EDSS development and knowledge sharing among the scientific community. In this work we introduce an EDSS development framework mainly based on R language, which is popular among environmental scientists, and Docker related software to lower technical hurdles for deployment in a web-based context. Using two examples, we demonstrate that the framework is able to deliver a unified and cost effective solution for setting up prototypes of modern web-based EDSS without compromising usability. A public repository is created to promote access to more examples from literature, which users can adapt for their own studies.
引用
收藏
页数:9
相关论文
共 56 条
[1]   An open software environment for hydrological model assessment and development [J].
Andrews, F. T. ;
Croke, B. F. W. ;
Jakeman, A. J. .
ENVIRONMENTAL MODELLING & SOFTWARE, 2011, 26 (10) :1171-1185
[2]  
[Anonymous], 2017, R PACKAGE VERSION, DOI DOI 10.14309/CRJ.2017.71
[3]  
[Anonymous], 2014, Fifth assessment report (AR5). Synthesis Report
[4]  
Attali D., 2018, **DATA OBJECT**
[5]   Containers and Cloud: From LXC to Docker to Kubernetes [J].
Bernstein, David .
IEEE CLOUD COMPUTING, 2014, 1 (03) :81-84
[6]  
Bivand R., 2019, **DATA OBJECT**
[7]  
Bivand R., 2019, **DATA OBJECT**
[8]  
Bivand R., 2019, **DATA OBJECT**
[9]  
Chang W., 2018, **DATA OBJECT**
[10]  
Chang W., 2018, **DATA OBJECT**