Towards fast prototyping of cloud-based environmental decision support systems for environmental scientists using R Shiny and Docker. (October 2020)

• Record Type: Journal Article
• Authors: Li, Yu
• Is Part Of: Environmental modelling & software. Volume 132(2020)
• Publication Date: 2020-10
• Subjects: Web-based EDSS -- Free and open-source software (FOSS) -- R shiny -- Docker -- Groundwater model -- Crop model; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104797
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Highlights: We highlight the potential of Shiny and Docker for fast prototyping of a web-based environmental decision support system. We implement a development framework to facilitate the work flow of EDSS construction and deployment. We provide two examples for demonstration and set up a public repository for knowledge sharing.