Note: This post is cross-posted on Sandra Chung’s blog here. The rise of the unconference The Ecological Society of America meeting is holding its 98th annual meeting next year in Minneapolis, MN. Several thousand students and professionals in ecological science and education will gather to hear and read the latest work and ideas in ecology in the familiar poster and lecture formats that are the core of every major scientific conference. But a subset of these people will get a taste of something a little bit different: an unconference within the conference. ...

Have you ever wanted to easily visualize your ecology data in Google Earth? R2G2 is a new package for R, available via R CRAN and formally described in this Molecular Ecology Resources article, which provides a user-friendly bridge between R and the Google Earth interface. Here, we will provide a brief introduction to the package, including a short tutorial, and then encourage you to try it out with your own data! Nils Arrigo, with some help from Loren Albert, Mike Barker, and Pascal Mickelson (one of the contributors to Recology), has created a set of R tools to generate KML files to view data with geographic components. Instead of just telling you what the tools can do, though, we will show you a couple of examples using publically available data. Note: a number of individual files are linked to throughout the tutorial below, but just in case you would rather download all the tutorial files in one go, have at it (tutorial zip file). ...

It can be a pain in the ass to get taxonomic names. For example, I sometimes need to get all the Class names for a set of species. This is a relatively easy problem using the ITIS API (example below). The much harder problem is getting all the taxonomic names downstream. ITIS doesn’t provide an API method for this - well, they do (getHirerachyDownFromTSN), but it only provides direct children (e.g., the genera within a tribe - but it won’t give all the species within each genus). ...

I need to simulate balanced and unbalanced phylogenetic trees for some research I am doing. In order to do this, I do rejection sampling: simulate a tree -> measure tree shape -> reject if not balanced or unbalanced enough. But what is enough? We need to define some cutoff value to determine what will be our set of balanced and unbalanced trees. calculate shape metrics A function to calculate shape metrics, and a custom theme for plottingn phylogenies. ...

UPDATE: In response to Jarrett’s query I laid out a separate use case in which you may want to query by higher taxonomic rankings than species. See below. In addition, added examples of querying by location in reply to comments by seminym. We have been working on an R package to get GBIF data from R, with the stable version available through CRAN, and the development version available on GitHub at https://github.com/rgbif ...

We (rOpenSci) started a repo to wrap the API for VertNet, an open access online database of vertebrate specimen records across many collection holders. Find the open source code here - please contribute if you are so inclined. We had a great Google Summer of Code student, Vijay Barve contributing to the repo this summer, so it is getting close to being CRAN-able. Most of the functions in the repo get you the raw data, but there were no functions to visualize the data. Since much of the data records of latitude and longitude data, maps are a natural visualization to use. ...

The problem: There are a lot of figures in published papers in the scholarly literature, like the below, from (Attwood et. al. 2012)): At some point, a scientist wants to ask a question for which they can synthesize the knowledge on that question by collecting data from the published literature. This often requires something like the following workflow: Search for relevant papers (e.g., via Google Scholar). Collect the papers. Decide which are appropriate for inclusion. Collect data from the figures using software on a native application. Examples include GraphClick and ImageJ. Proof data. Analyze data & publish paper. This workflow needs revamping, particularly in step number 3 - collecting the data. This data remains private, moving from one closed source (original publication) to another (personal computer). We can surely do better. ...

Metadata! Metadata is very cool. It’s super hot right now - everybody is talking about it. Okay, maybe not everyone, but it’s an important part of archiving scholarly work. We are working on a repo on GitHub rmetadata to be a one stop shop for querying metadata from around the web. Various repos on GitHub we have started - rpmc, rdatacite, rdryad, rpensoft, rhindawi - will at least in part be folded into rmetadata. As a start we are writing functions to hit any metadata services that use the OAI-PMH: “Open Archives Initiative Protocol for Metadata Harvesting” framework. OAI-PMH has six methods (or verbs as they are called) for data harvesting that are the same across different metadata providers: ...

I created an R package a while back to interact with some APIs that serve up data on what our elected represenatives are up to, including the New York Times Congress API, and the Sunlight Labs API. What kinds of things can you do with govdat? Here are a few examples. How do the two major parties differ in the use of certain words (searches the congressional record using the Sunlight Labs Capitol Words API)? ...

So I want to mine some #altmetrics data for some research I’m thinking about doing. The steps would be: Get journal titles for ecology and evolution journals. Get DOI’s for all papers in all the above journal titles. Get altmetrics data on each DOI. Do some fancy analyses. Make som pretty figs. Write up results. It’s early days, so jus working on the first step. However, getting a list of journals in ecology and evolution is frustratingly hard. This turns out to not be that easy if you are (1) trying to avoid Thomson Reuters, and (2) want a machine interface way to do it (read: API). ...