R Python, and Ruby clients for GBIF species occurrence data
- Published
- Accepted
- Subject Areas
- Bioinformatics, Ecology, Computational Science
- Keywords
- ecology, bioinformatics, gbif, occurrences, biodiversity, reproducibility, python, ruby
- Copyright
- © 2017 Chamberlain et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. R Python, and Ruby clients for GBIF species occurrence data. PeerJ Preprints 5:e3304v1 https://doi.org/10.7287/peerj.preprints.3304v1
Abstract
Background. The number of individuals of each species in a given location forms the basis for many sub-fields of ecology and evolution. Data on individuals, including which species, and where they're found can be used for a large number of research questions. Global Biodiversity Information Facility (hereafter, GBIF) is the largest of these. Programmatic clients for GBIF would make research dealing with GBIF data much easier and more reproducible.
Methods. We have developed clients to access GBIF data for each of the R, Python, and Ruby programming languages: rgbif, pygbif, gbifrb.
Results. For all clients we describe their design and utility, and demonstrate some use cases.
Discussion. Programmatic access to GBIF will facilitate more open and reproducible science - the three GBIF clients described herein are a significant contribution towards this goal.
Author Comment
This is a preprint submission to PeerJ Preprints. We may submit to a journal for peer-review as well.