Reproducible research involves the careful, annotated preservation of data, analysis code, and associated files, such that statistical procedures, output, and published results can be directly and fully replicated. As the push for reproducible research has grown, the R community has responded with an increasingly large set of tools for engaging in reproducible research practices (see, for example, the ReproducibleResearch Task View on CRAN).

We just released a new version of taxize - version 0.2.0. This release contains a number of new features, and bug fixes. Here is a run down of some of the changes: First, install and load taxize install.packages("rgbif") library(taxize) New things New functions: class2tree Sometimes you just want to have a visual of the taxonomic relationships among taxa.

Data on more than 10,000 species of ants recorded worldwide are available through from California Academy of Sciences’ AntWeb, a repository that boasts a wealth of natural history data, digital images, and specimen records on ant species from a large community of museum curators.

rgbif is an R package to search and retrieve data from the Global Biodiverity Information Facilty (GBIF). rgbif wraps R code around the [GBIF API][gbifapi] to allow you to talk to GBIF from R. We just pushed a new verion of rgbif to cran - v0.5.0. Source and binary files are now available on CRAN. There are a few new functions: count_facet, elevation, and installations. These are described, with examples, below.

In a recent blog post we discussed caching calls to the web offline, on your own computer. Just like you can cache data on your own computer, a data provider can do the same thing. Most of the data providers we work with do not provide caching. However, at least one does: EOL, or Encyclopedia of Life.

Our team has been cranking out a large number of tools over the past several months. As regular readers are aware, our software packages provide programmatic access to a diverse and extensive trove of scientific data. More recently we’ve expanded our efforts to build more general purpose and cross-domain tools.

I’ve recently heard the idea of “offline first” via especially Hood.ie. We of course don’t do web development, but primarily build R interfaces to data on the web. Internet availablility is increasinghly ubiqutous, but there still are times and places where you don’t have internet, but need to get work done.

Natural history museums have long been valuable repositories of data on species diversity. These data have been critical for fostering and shaping the development of fields such as biogeography and systematics.

A number of the APIs we interact with (e.g., PLOS full text API, and USGS’s BISON API in rplos and rbison, respectively) expose Solr endpoints. Solr is an Apache hosted project - it is a powerful search server.

Upcoming Book on Open Science with R We’re pleased to announce that the rOpenSci core team has just signed a contract with CRC Press/Taylor and Francis R series to publish a new book on practical ways to implement open science into your own research using R. Given all the talk about the importance of open science, the discussion often lacks practical suggestions on how one might actually incorporate these practices into their

rplos is an R package to facilitate easy search and full-text retrieval from all Public Library of Science (PLOS) articles, and we have a little feature which aren’t sure if is useful or not. I don’t actually do any text-mining for my research, so perhaps text-mining folks can give some feedback. You can quickly get a lot of results back using rplos, so perhaps it is useful to quickly browse what you got.