The R software environment in reproducible geoscientific research

Edzer J Pebesma · Daniel Nüst · Roger Bivand

30 citations0/0 files storedEos

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Scientific Computing and Data Management Research Data Management Practices Data Analysis with R

Abstract

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.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 30 citations exist upstream.

References

2008Applied Spatial Data Analysis with R 2008Applied Spatial Data Analysis with R. Springer

Cited by

2012Open and Free: Software and Scientific Reproducibility 2013Agnotology: learning from mistakes 2016Thou Shalt Be Reproducible! A Technology Perspective 2018Digital Data-Centric Geography: Implications for Geography's Frontier

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.