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.

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.

[Following the development of the ORCID-based Article Claiming Tool (see this blog post), Europe PMC has now integrated ORCIDs into its website, search systems, and web services.

The Global Biodiversity Information Facility (GBIF) is a warehouse of species occurrence data - collecting data from a lot of different sources. Our package rgbif allows you to interact with GBIF from R. We interact with GBIF via their Application Programming Interface, or API. Our last version on CRAN (v0.3) interacted with the older version of their API - this version interacts with the new version of their API.

We are building a taxonomic toolbelt for R called taxize - which gives you programmatic access to many sources of taxonomic data on the web. We just pushed a new version to CRAN (v0.1.5) with a lot of changes (see here for a rundown). Here are a few highlights of the changes.

We have previously written about creating interactive maps on the web from R, with the interactive maps on Github. See here, here, here, and here. A different approach is to use CartoDB, a freemium service with sql interface to your data tables that provides a map to visualize data in those tables.

Previously on this blog we have discussed making geojson maps and uploading to Github for interactive visualization with USGS BISON data, and with GBIF data, and on my own personal blog. This is done using a file format called geojson , a file format based on JSON (JavaScript Object Notation) in which you can specify geographic data along with any other metadata.

I recently attended ScienceOnline Climate, a conference in Washington, D.C. at AAAS. You may have heard of the ScienceOnline annual meeting in North Carolina - this was one of their topical meetings focused on Climate Change. I moderated a session on working with data from the web in R, focusing on climate data. Search Twitter for #scioClimate for tweets from the conference, and #sciordata for tweets from the session I ran.

We have started a new R package interacting with NOAA climate data called rnoaa . You can find our package in development here and documentation for NOAA web services here. It is still early days for this package, but we wanted to demo what you can do with the package.

One of our primary goals at ROpenSci is to wrap as many science API’s as possible. While each package can be used as a standalone interface, there’s lots of ways our packages can overlap and complement each other. Sure He-Man usually rode Battle Cat, but there’s no reason he couldn’t ride a my little pony sometimes too. That’s the case with our packages for GBIF and the worldbank climate data api.