After my presentation yesterday to a group of grad students on R resources, I did a presentation today on intro to R data manipulation, visualizations, and analyses/visualizations of biparite networks and community level analyses (diversity, rarefaction, ordination, etc.). As I said yesterday I’ve been playing with two ways to make reproducible presentations in R: RStudio’s presentations built in to RStudio IDE, and Slidify. Yesterday I went with RStudio’s product - today I used Slidify. See the Markdown file for the presentation here. ...

I’m doing a presentation today to grad students on R resources. I have been writing HTML presentations recently, but some great tools are now available to convert text that is easy to read and write to presentations. RStudio has something called R presentations, that is basically Markdown. This tool is built in to RStudio. See some docs here. A cool feature of RStudio’s presentations is that the preview of the presentation live updates on each save - nice Another option is the slidify package, made by Ramnath Vaidyanathan. The canonical url for slidify is here. Slidify gives you more options and flexibity than RStudio presentations. For this presentation I went with RStudio’s product. See the Markdown file for the presentation here. ...

As ecologists, we often start graduate school worshiping the ivory tower of academia with its freedom to pursue important ecological questions. However, studies have shown that most of us do not end up in academia. Greater numbers of ecology graduates are leaving the ivory tower for non-academic career paths. But for many graduates, moving from an academic environment to a non-academic job may be difficult. In graduate school we are trained to work in a particular way, often with loose deadlines and unlimited intellectual freedom (within reason of course). The culture and expectations of the non-academic world may be quite different. What are the skills that you need in a government job, or in science journalism? How do you market yourself for a non-academic position? This is a timely topic because funding to academic ecologists is being cut, leaving fewer opportunities in the academic arena. In fact, an ESA Student Section survey found that an ESA 2013 session on non-academic career paths in ecology was the topic of greatest interest. ...

I recently engaged with a number of tweeps in response to my tweet: Rule number 1 wrt science code: DO NOT post your code on your personal website That tweet wasn’t super clear, and it’s difficult to convey my thoughts in a tweet. What I should have said was do post your code - ideally on Github/Bitbucket/etc. Here goes with a much longer version to explain what I meant. The tweet was just about where to host code, whereas the following is about more than that, but related. ...

UPDATE As you can see in Patrick’s comment below you can convert to GeoJSON format files with rgdal as an alternative to calling the Ogre web API described below. See here for example code for converting to GeoJSON with rgdal. GitHub recently introduced the ability to render GeoJSON files on their site as maps here, and recently introduced here support for TopoJSON, an extension of GeoJSON can be up to 80% smaller than GeoJSON, support for other file extensions (.topojson and .json), and you can embed the maps on other sites (so awesome). The underlying maps used on GitHub are Openstreet Maps. ...

Have you heard of DataONE? It stands for the Data Observation Network for Earth, and I am involved in the Community Education and Engagement working group at DataONE. We try to communicate about data, data management, and similar things to scientists and other DataONE stakeholders. At our last meeting, we decided to start a blog aggregator to pull in to one place blog posts about data, data management, and related topics. Those reading this blog have likely heard of R-Bloggers - and there are many more aggregator blogs. We are calling this blog aggregator Coffeehouse - as it’s sort of a place to gather to talk/read about ideas. Check it out here. If you blog about data management think about adding your blog to Coffeehouse - go to the Add your blog page to do so. A screenshot: ...

It is getting easier to get data directly into R from the web. Often R packages that retrieve data from the web return useful R data structures to users like a data.frame. This is a good thing of course to make things user friendly. However, what if you want to drill down into the data that’s returned from a query to a database in R? What if you want to get that nice data.frame in R, but you think you may want to look at the raw data later? The raw data from web queries are often JSON or XML data. This type of data, especially JSON, can be easily stored in schemaless so-called NoSQL databases, and queried later. ...

What is PhyloPic? PhyloPic is an awesome new service - I’ll let the creator, Mike Keesey, explain what it is (paraphrasing here): PhyloPic stores silhouette images of organisms, and each image is associated with taxonomic names, and stores the taxonomy of all taxa, allowing searching by taxonomic names. Anyone can submit silhouettes to PhyloPic. What is a silhouette? It’s like this: by Gareth Monger What makes PhyloPic not just awesome, but super awesome? All or most images are licensed under Creative Commons licenses. This means you can use the silhouettes without having to ask or pay - just attribute. ...

The USGS recently released a way to search for and get species occurrence records for the USA. The service is called BISON (Biodiversity Information Serving Our Nation). The service has a web interface for human interaction in a browser, and two APIs (application programming interface) to allow machines to interact with their database. One of the APIs allows you to search and retrieve data, and the other gives back maps as either a heatmap or a species occurrence map. The latter is more appropriate for working in a browser, so I’ll leave that to the web app folks. ...

Scholarly metadata - the meta-information surrounding articles - can be super useful. Although metadata does not contain the full content of articles, it contains a lot of useful information, including title, authors, abstract, URL to the article, etc. One of the largest sources of metadata is provided via the Open Archives Initiative Protocol for Metadata Harvesting or OAI-PMH. Many publishers, provide their metadata through their own endpoint, and implement the standard OAI-PMH methods: GetRecord, Identify, ListIdentifiers, ListMetadataFormats, ListRecords, and ListSets. Many providers use OAI-PMH, including DataCite, Dryad, and PubMed. ...