Jabberwocky Ecology

Fork our course: A semester-long Data Carpentry course for biologists

This is post is co-authored by Zack Brym and Ethan White

Over the last year and a half we have been actively developing a semester-long Data Carpentry course designed to be easily customized and integrated into existing graduate and undergraduate curricula.

Data Carpentry for Biologists contains course materials for teaching scientists how to work more effectively with data. The course provides introductions to data management and relational databases, data manipulation and analysis, and data visualization. It covers the same general types of material as a two-day Data Carpentry workshop, but expands the materials and opportunities for practice into a full-length university course. The teaching material uses R and SQLite, with some corresponding materials for Python as well. To help students understand the direct applications to their interests, the examples and exercises focus on biological questions and working with real data. The course emphasizes using best practices to produce reusable and reproducible data analysis.

Active-learning Teaching Materials

Learning computing requires active practice by working through programming problems. Just diving in to computing is challenging for most scientists, so the course instruction is designed to combine short live-coding introductions to concepts followed immediately by the students working on a related exercise. Additional exercises are assigned later for practice. This follows the “I do”, “We do”, “You do” approach to teaching, which leverages the benefits of active-learning and flipped classrooms without leaving students who are less comfortable with the material feeling lost. The bulk of class time is spent working on assigned exercises with the instructor moving around the room helping guide students through things they don’t understand and engaging with students who are thinking about advanced applications of what they’ve learned.

This approach is the result of lots of reading about effective teaching methods and Ethan’s experience teaching this and related courses over the last six years at Utah State University and the University of Florida. It seems to work well for both students that get the material easily and those that find it more challenging. We’ve also tried to make these materials as useful as possible for self-guided students.

Open course development

Software Carpentry and Data Carpentry have shown how powerful collaborative lesson development can be and we’re interested in bringing that to the university classroom. We have designed the course materials to be modular and easy to modify, and the course website easy to clone and set up. All of the teaching materials and associated website files are openly available at the Data Carpentry for Biologists repository on GitHub under CC-BY and MIT licenses. The course materials are all written in Markdown and everything runs on Jekyll through GitHub Pages. Making your own version of the course should take less than an hour. We’ve developed documentation for how to create your own version of the course and how to contribute to development. Exercises and assignments are modular and changing exercises and assignments simply involves reordering items in a list. Adding a new exercise involves creating a new Markdown file and then adding its title to the list of exercises for an assignment.

Get Involved

If you teach, or want to teach, a course like this, we’d love to get you involved. Here are some useful links for getting started.

–   I want to teach the course.
–   I have some feedback.
–   I want to contribute to the project.

We want to be sure getting involved is as easy as possible. We’ve worked hard to provide documentation and help resources for students and instructors. Students can find all they need to know at our student start guide. Instructors have access to course content and site design documentation.

If your having trouble finding something or getting something to work, or simply have some feedback about the course please open a new issue at GitHub or send us an email.

Acknowledgements

Development of this course was generously support by  the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative through Grant GBMF4563 to Ethan White and the National Science Foundation as part of a CAREER award to Ethan White.

New release of the EcoData Retriever

EcoData Retriever logoWe are very exited to announce the newest release of the EcoData Retriever, our software for automating the downloading, cleaning, and installing of ecological and environmental data. Instead of hours or days trying to get complicated datasets like the Breeding Bird Survey ready for analysis, the Retriever lets you simply click a button or run a single command from R or the command line, and your computer does the rest.

bbs_install_animated

It’s been over a year since the last retriever release and there are lots of new features and improvements to be excited about.

  • We’ve added 21 new datasets, including major ecological and environmental datasets like eBird, Vertnet, and the Global Wood Density Database, and the PRISM climate data.
  • To support all of these datasets we’ve added support for additional data types including greater than memory archive files, and we’ve also improved the ability to control where downloaded files are stored and how they are clustered together.
  • We’ve significantly improved documentation and now have a new automatically built documentation site at Read The Docs.
  • We’ve also made a lot of under the hood improvements.

This is also the first release that has been overseen by Weecology’s new software engineer, Henry Senyondo. We’re excited to have Henry on the team, and now that he’s around development of both the EcoData Retriever and other lab software projects will be happening more quickly.

A big thanks to the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative for funding this development through Grant GBMF4563 and to the National Science Foundation for funding as part of a CAREER award to Ethan White.

UPDATE: Led by Dan McGlinn we also released a new version of the ecoretriever R interface for the Retriever last fall. This makes using the Retriever from R as simple as:

data <- ecoretriever::fetch("BBS")

GEB adds unlimited data references section to papers

In a big step forward for allowing proper credit to be provided to all of the awesome folks collecting and publishing data, the journal Global Ecology & Biogeography has just announced that they will start supporting an unlimited set of references to datasets used in a paper.

A growing concern in the macroecological community has been that many papers whose data are used in meta-analyses or data-compilation papers have not been getting citation credit because most journals require these papers to only be listed in the supplemental material (which is not indexed by most indexing services). GEB is proud to support the inclusion of a second list of references within the main paper for all data papers used… To our knowledge, GEB is the first journal in the ecological field to do this. And we’ll be working with Wiley to further improve options in this area.

These references will be included immediately following the traditional references section in both the html and pdf versions of the paper. You can see an example in Olds et al. (2016).

What this means is that when you combine data from dozens or hundreds of studies to conduct a synthetic analysis, you can cite all of the sources in a way that will provide citation credit to those collecting the data1. It also means that scientists using large data compilations can cite the original data sources as well as the compilation itself2.

This is important for encouraging the publication of data, since one of the common reasons that scientists don’t publish data is a lack of credit, and citation only in non-indexed supplementary materials sections is a common concern.

Facilitating proper citation of all data sources is something the community has been requesting and it’s great to see GEB taking the lead in this area. Since Wiley, the publisher of GEB, is the largest publisher of ecology journals, it should be straightforward to implement this new approach widely. If other journals follow GEB’s lead, we will enter a new era where citation of data can be as complete as possible, allowing proper credit to everyone who collects and publishes data.

1GEB will need to make sure that this section gets properly picked up by the indexers, and tweak the presentation as necessary if it isn’t.
2Provided that the compilation provides a method for compiling a citation list of all associated sources.

How technology can help scientists with chronic illnesses (or Technology FTW!)

This is a guest post by Elita Baldridge (@elitabaldridge)

I am currently the remotely working member of Weecology, finishing up my PhD in the lower elevation and better air of Kansas, while the rest of my colleagues are still in Utah, due to developing a chronic illness and finally getting diagnosed with fibromyalgia.  The relocation is actually working out really well.  I’m in better shape because I’m not having to fight the air too, and I’m finally making real progress toward finishing my dissertation again.

I ruthlessly culled everything that wasn’t directly working on my dissertation.  I was going to attend the Gordon Conference this year, as I had heard fantastic things about it for years, but had not been ready to go yet, but I had to drop that because I wasn’t physically able to travel.  I did not go to ESA, because I couldn’t travel.  There are working groups and workshops galore, all involving travel, which I cannot do.  Right now, the closest thing that we have to bringing absent scientists to an event is live tweeting, which is not nearly as good as hearing a speaker for yourself, and is pretty heartbreaking if you had to cancel your plans to attend an event because you were too infirm to go.The tools that I’m using to do science remotely are not just for increasing accessibility for a single chronically ill macroecologist.  They are good tools for science in general.  I’m using GitHub to version control my code, and Dropbox to share data and figures.  Ethan can see what I’m working on as I’m doing it, and I’ve got a clear record of what I was doing and what decisions that I made. While my cognitive dysfunction may be a bit more extreme of a problem, I know that we’ve all stayed up too late coding and broken something we shouldn’t have and the ability to wave the magic Git wand and make any poor decisions that I made while my brain was out to lunch go away is priceless.

Open access?  Having open access to papers is really important when you are going to be faced shortly with probably not having any institutional access anymore.  Also, important for everyone else who isn’t at a major university with very expensive subscriptions to all the journals.  Having open access to data and code is crucial when you can’t collect your own data and are going to be doing research from your home computer on the cheap because you can’t rely on your body to work reliably at any given point in time.

Video conferencing is working well for me to meet with the lab, but could also be great for attending conferences and workshops.  This would not only be good for a certain macroecologist, but would also be good to include people from smaller universities, etc. who would like to participate in these type of things too, but can’t otherwise due to the travel.  I did my master’s degree at Fort Hays State University, and I still love it dearly.  This type of increased accessibility would have been great for me while I was a perfectly healthy master’s student.  Fort Hays is a primarily undergraduate institution in the middle of Kansas, about four hours away from any major city, and it does not have some of the resources that a larger university would have.  No seminar series, no workshops, not much travel money to go to workshops or conferences, which doesn’t mean that good science can’t still be happening.

Many of my labmates are looking for post-docs, or are already in postdoc positions at this point.  I’m very excited for all of them, and await eagerly all the stories of the exciting new things they are doing.  Having a chronic illness limits what I am capable of doing physically.  I am not going to be able to move across the country for a post-doc.  That does not mean that I do not want to play science too.  I’ve got my home base set up, and I can reach pretty far from here.  I still want to be a part of living science, I don’t want to have to get to the party after everyone else has gone home.

And I wonder, why can I not do these things?  Is it not the future?  Do we not have the internet, with video chat?  I get to meet with Ethan and talk science at our weekly meetings every week.  I go to lab meetings with video chat, and get to see what my labmates are doing, and crack jokes, and laugh at other people’s jokes.  It wouldn’t be hard to get me to conferences and working groups either.

With technology, I get to be a part of living, breathing science, and it is a beautiful thing.

White Lab PhD openings at the University of Florida

I’m looking for one or more graduate students to join my group next fall. In addition to the official add (below) I’d like to add a few extra thoughts. As Morgan Ernest noted in her recent ad, we have a relatively unique setup at Weecology in that we interact actively with members of the Ernest Lab. We share space, have joint lab meetings, and generally maintain a very close intellectual relationship. We do this with the goal of breaking down the barriers between the quantitative side of ecology and the field/lab side of ecology. Our goal is to train scientists who span these barriers in a way that allows them to tackle interesting and important questions.

I also believe it’s important to train students for multiple potential career paths. Members of my lab have gone on to faculty positions, postdocs, and jobs in both science non-profits and the software industry.

Scientists in my group regularly both write papers (e.g., these recent papers from dissertation chapters: Locey & White 2013, Xiao et al. 2014) and develop or contribute to software (e.g., EcoData Retriever, ecoretriever, rpartitions & pypartitions) even if they’ve never coded before they joined my lab.

My group generally works on problems at the population, community, and ecosystem levels of ecology. You can find out more about what we’ve been up to by checking out our website. If you’re interested in learning more about where the lab is headed I recommend reading my recently funded Moore Investigator in Data-Driven Discovery proposal.

PH.D STUDENT OPENINGS IN QUANTITATIVE, COMPUTATIONAL, AND MACRO- ECOLOGY

The White Lab at the University of Florida has openings for one or more PhD students in quantitative, computational, and/or macro- ecology to start fall 2015. The student(s) will be supported as graduate research assistants from a combination of NSF, Moore Foundation, and University of Florida sources depending on their research interests.

The White Lab uses computational, mathematical, and advanced statistical/machine learning methods to understand and make predictions/forecasts for ecological systems using large amounts of data. Background in quantitative and computational techniques is not necessary, only an interest in learning and applying them. Students are encouraged to develop their own research projects related to their interests.

The White Lab is currently at Utah State University, but is moving to the Department of Wildlife Ecology and Conservation at the University of Florida starting summer 2015.

Interested students should contact Dr. Ethan White (ethan@weecology.org) by Nov 15th, 2014 with their CV, GRE scores, and a brief statement of research interests.

UPDATE: Added a note that we work at population, community, and ecosystem levels.

EcoData Retriever now supports R and environmental data, and has more datasets

Retreiver Logo
We are very excited to announce the newest release of our EcoData Retriever software and the first release of a supporting R package, ecoretriever. If you’re not familiar with the EcoData Retriever you can read more here.

The biggest improvement to the Retriever in this set of releases is the ability to run it directly from R. Dan McGlinn did a great job leading the development of this package and we got ton of fantastic help from the folks at rOpenSci (most notably Scott Chamberlain, Gavin Simpson, and Karthik Ram). Now, once you install the main EcoData Retriever, you can run it from inside R by doing things like:

install.packages('ecoretriever')
library(ecoretriever)

# List the datasets available via the Retriever
ecoretriever::datasets()

# Install the Gentry dataset into csv files in your working directory
ecoretriever::install('Gentry', 'csv')

# Download the raw Gentry dataset files, without any processing,
# to the subdirectory named data
ecoretriever::download('Gentry', './data/')

# Install and load a dataset as a list
Gentry = ecoretriever::fetch('Gentry')
names(Gentry)
head(Gentry$counts)

The other big advance in this release is the ability to have the Retriever directly download files instead of processing them. This allows us to support data that doesn’t come in standard tabular forms. So, we can now include things like environmental data in GIS formats and phylogenetic data such as supertrees. We’ve used this new capability to allow the automatic downloading of the Bioclim data, one of the most widely used climate datasets in ecology, and the supertree for mammals from Fritz et al. 2009.

Finally, we’ve also add the very cool mammalian diet dataset from Dryad

Weecology is moving to the University of Florida

And yes... River is doing the Gator Chomp

We are excited to announce that Weecology will be moving to the University of Florida next summer. We were recruited as part of the UF Rising Preeminence Plan, a major hiring campaign to bring together researchers in a number of focal areas including Big Data and Biodiversity. We will both be joining the Wildlife Ecology and Conservation department, Ethan will be part of UF’s new Informatics Institute, and Morgan will be part of UF’s new Biodiversity Initiative.

As excited as we are about the opportunities at Florida, we are also incredibly sad to be saying goodbye to Utah State University. Leaving was not an easy decision. We have amazing colleagues and friends here in Utah that we will greatly miss. We have also felt extremely well treated by Utah State. They were very supportive while we were getting our programs up and running, including helping us solve the two-body problem. They allowed us to take risks in both research and the classroom. They have been incredibly supportive of our desires for work-life balance, and were very accommodating following the birth of our daughter. It was a fantastic place to spend nearly a decade and we will miss it and the amazing people who made it home.

So why are we leaving? It was a many faceted decisions, but at its core was the realization that the scale of the investment and recruiting of talented folks in both of our areas of interest was something we were unlikely to see again in our careers. The University of Florida has always had a strong ecology group, but between the new folks who have already accepted positions and those we know who are being considered, it is going to be such a talented and exciting group that we just had to be part of it!

As part of the move we’ll be hiring for a number of different positions, so stay tuned!