The R software environment in reproducible geoscientific research

@article{Pebesma2012TheRS,
  title={The R software environment in reproducible geoscientific research},
  author={Edzer J. Pebesma and Daniel N{\"u}st and Roger S. Bivand},
  journal={Eos, Transactions American Geophysical Union},
  year={2012},
  volume={93},
  pages={163-163}
}
Reproducibility is an important aspect of scientific research, because the credibility of science is at stake when research is not reproducible. Like science, the development of good, reliable scientific software is a social process. A mature and growing community relies on the R software environment for carrying out geoscientific research. Here we describe why people use R and how it helps in communicating and reproducing research. 
REPRODUCIBILITY AND REPLICABILITY FORUM Practical Reproducibility in Geography and Geosciences Reproducible workflows in geography and geosciences
TLDR
It is argued that all researchers working with computers should understand these technologies to control their computing environment, and it is concluded that researchers today can overcome many barriers and achieve a very high degree of reproducibility.
Practical Reproducibility in Geography and Geosciences
TLDR
It is argued that all researchers working with computers should understand these technologies to control their computing environment, and the benefits of reproducible workflows in practice are presented.
Toward the Geoscience Paper of the Future: Best practices for documenting and sharing research from data to software to provenance
TLDR
This article proposes best practices for GPF authors to make data, software, and methods openly accessible, citable, and well documented to accelerate the pace of scientific discovery.
An empirical exploration of the vibrant R ecosystem
TLDR
It was discovered that while initiated by statistics, the development of R benefited greatly from software developers and users coming from various disciplines such as agricultural, biological, environmental, and medical science.
R-functions for Canadian hydrologists: a Canada-wide collaboration
R is an open-source statistical language that is supported by a large user community with many benefits for use in watershed analysis. R has been used widely in the Canadian research community and
An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)
TLDR
The lulccR package is presented, an object-oriented framework for land use change modelling written in the R programming language, to resolve the following limitations associated with the current land use changes modelling paradigm.
Using R in hydrology: a review of recent developments and future directions
TLDR
A roadmap for R's future within hydrology is provided, with R packages as a driver of progress in the hydrological sciences, application programming interfaces (APIs) providing new avenues for data acquisition and provision, enhanced teaching of hydrology in R, and the continued growth of the community via short courses and events.
Spatial Statistics on the Geospatial Web
TLDR
This work presents a concept of script annotations for automatic deployment in server runtime environments and demonstrates it with an implementation based on the open standards and open source components OGC Web Processing Service and R.
Opening Reproducible Research
Open access is not only a form of publishing such that research papers become available to the large public free of charge, it also refers to a trend in science that the act of doing research becomes
Using Free/Libre and Open Source Software in the Geological Sciences
In the Geological Sciences, as in any other academic field, computers and software aided work are essential tools. Although Free and Open Source software is largely used in academic institutions for
...
...

References

SHOWING 1-2 OF 2 REFERENCES
Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis
TLDR
Sweave combines typesetting with LATEX and data anlysis with S into integrated statistical documents that can be automatically updated if data or analysis change, which allows truly reproducible research.