What's this bird? Classify old natural history drawings with R

August 28, 2018

By: Maëlle Salmon

In this new post, we’re taking a break from modern birding data in our birder’s series… let’s explore gorgeous drawings from a natural history collection! Armed with rOpenSci’s packages binding powerful C++ libraries and open taxonomy data, how much information can we automatically extract from images? Maybe not much, but we’ll at least have explored image manipulation, optical character recognition (OCR), language detection, taxonomic name resolution with rOpenSci’s packages.

What birds are observed near Radolfzell? Bird occurrence data in R

August 21, 2018

By: Maëlle Salmon

Thanks to the first post of the series we know where to observe birds near Radolfzell’s Max Planck Institute for Ornithology, so we could go and do that! Or we can stay behind our laptops and take advantage of eBird, a fantastic bird sightings aggregator! As explained by Matt Strimas-Mackey in his recent blog post, “The eBird database currently contains over 500 million records of bird sightings, spanning every country and over 98% of species, making it an extremely valuable resource for bird research and conservation.

Where to go observe birds in Radolfzell? An answer with R and open data

August 14, 2018

By: Maëlle Salmon  |  Mark Padgham

This post is the 1st post of a series showcasing various rOpenSci packages as if Maëlle were a birder trying to make the most of R in general and rOpenSci in particular. Although the series use cases will mostly feature birds, it’ll be the occasion to highlight rOpenSci’s packages that are more widely applicable, so read on no matter what your field is! Moreoever, each post should stand on its own.

Extracting and Processing eBird Data

August 7, 2018

By: Matthew Strimas-Mackey

eBird is an online tool for recording bird observations. The eBird database currently contains over 500 million records of bird sightings, spanning every country and nearly every bird species, making it an extremely valuable resource for bird research and conservation. These data can be used to map the distribution and abundance of species, and assess how species’ ranges are changing over time. This dataset is available for download as a text file; however, this file is huge (over 180 GB!

A package for dimensionality reduction of large data

August 1, 2018

By: Sean Hughes  |  Angela Li  |  Ju Kim  |  Malisa Smith  |  Ted Laderas

Motivation Note: Recently, two new UMAP R packages have appeared. These new packages provide more features than umapr does and they are more actively developed. These packages are: umap, which provides the same Python wrapping function as umapr and also an R implementation, removing the need for the Python version to be installed. It is available on CRAN. uwot, which also provides an R implementation, removing the need for the Python version to be installed.

Page 2 of 42