Posts with the "species" tag

Checklist Recipe - How we created a template to standardize species data

November 20, 2018

By:   Peter Desmet  |   Damiano Oldoni  |   Lien Reyserhove

Imagine you are a fish ecologist who compiled a list of fish species for your country. 🐟 Your list could be useful to others, so you publish it as a supplementary file to an article or in a research repository. That is fantastic, but it might be difficult for others to discover your list or combine it with other lists of species. Luckily there’s a better way to publish species lists: as a standardized checklist that can be harvested and processed by the Global Biodiversity Information Facility (GBIF).

Overlaying species occurrence data with climate data

April 22, 2014

By:   Ted Hart

One of the goals of the rOpenSci is to facilitate interoperability between different data sources around web with our tools. We can achieve this by providing functionality within our packages that converts data coming down via web APIs in one format (often a provider specific schema) into a standard format. The new version of rWBclimate that we just posted to CRAN does just that. In an earlier post I wrote about how users could combine data from both rgbif and rWBclimate.

Accessing iNaturalist data

March 26, 2014

By:   Ted Hart

The iNaturalist project is a really cool way to both engage people in citizen science and collect species occurrence data. The premise is pretty simple, users download an app for their smartphone, and then can easily geo reference any specimen they see, uploading it to the iNaturalist website. It let’s users turn casual observations into meaningful crowdsourced species occurrence data. They also provide a nice robust API to access almost all of their data.

Species occurrence data

March 17, 2014


UPDATE: mapping functions are in a separate package now (mapr). Examples that do mapping below have been updated. The rOpenSci projects aims to provide programmatic access to scientific data repositories on the web. A vast majority of the packages in our current suite retrieve some form of biodiversity or taxonomic data. Since several of these datasets have been georeferenced, it provides numerous opportunities for visualizing species distributions, building species distribution maps, and for using it analyses such as species distribution models.

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