We are organizing the fifth edition of our intensive class in data-driven ecological synthesis, with support from the NSERC BIOS² CREATE program. You can apply on-line, or read the description below. Enrolment is limited to 30 students. The class will run from in the first week of May 2020, at the Laurentians Field Station, just outside of Montréal.
Application deadline is Dec. 31, 2019
Goals and target audience
This week-long intensive class will give early-career ecologists the tools and skills needed to interact with, manage, clean, and analyze data in a transparent and reproducible way. We will specifically work on leveraging open data to address new ecological questions at large spatial and temporal scales. You can read more about the approach of computational ecology in a paper co-authored by students from the 2017 cohort.
We expect that the attendees are able to turn the computer on, or willing to learn how to do so. We will take care of the rest from here. A passing knowledge of statistics and programming is a good thing, but eagerness to learn is far more important than previous knowledge.
The class is open to all, and previous attendees included undergraduate and graduate students, staff scientists, data analysts, and post-doctoral fellows. We think it is particularly relevant for PhD students and post-doctoral fellows.
Over the course of seven days, including learners-led projects that can be continued after the class, we will cover:
- good practices for data management
- good practices in scientific computing
- good practices for programming with data
- useful statistical and mathematical tools
- data cleaning and data analysis tools
- notions of parallel computing for data processing
- data visualization and presentation
- ensuring reproducibility of analyses
The class is conducted in an extremely participatory way, were a lot of training modules are delivered based on the needs expressed by the students. Some of the modules delivered last year included Bayesian statistics, code optimization, introduction to GIS, and how to be less afraid of mathematics. We also watched the second to last episode of Game of Thrones and managed to not spoil any of it.
The summer school will be led by Timothée Poisot and Andrew MacDonald (Université de Montréal), and will include guest appearances by local ecologists. One or two teaching assistants will be here to facilitate the training.
Timothée is a researcher at the Québec Center for Biodiversity Sciences and an assistant professor in Quantitative and Computational Ecology at the Université de Montréal. He is a certified Software Carpentry and Data Carpentry instructor, serves on the editorial board of Ecology Letters, Methods in Ecology & Evolution and PLOS Computational Biology, and on the scientific board of Calcul Québec and the Canadian Institute for Ecology & Evolution. His research focuses on the spatio-temporal dynamics of species interactions, and the applications of graph theory to a variety of ecological questions.
Andrew is a postdoctoral researcher at Université de Montreal. He is also a certified Carpentry instructor, and is passionate about building a community of practice around scientific programming in ecology. He’s currenlty interested in building predictive models for ecological communities.
The summer school will take place at the Station de Biologie des Laurentides (SBL), operated by the Université de Montréal. Situated in the middle of a series of lakes, in the Laurentians, it is a very pleasant and stimulating place to work and relax. The SBL is also a perfect example of an emblematic Canadian biome, sitting at the transition zone between the urbanized Greater Montréal area and the Canadian shield. It is known to have the best food of all field stations in Canada.
Dates & transportation
The intensive class will run from April 27 to May 3. Selected applicants will be notified by the second week of February at the latest.
We will take care of the transportation from the Université de Montréal to the field station on the morning on the first day, and from the field station to the Université de Montréal on the afternoon of the last day. We usually leave at 8am, and return by 4pm. Further details will be given to the selected applicants.
Students from Québec universities can get 4 credits for this class through CRÉPUQ (class code BIO6065). Please indicate if you want to claim these credits when applying.
All days will follow the same template: morning and afternoons are for practice-based learning, and the evenings are shorter tutorials unless it’s dark enough for a bonfire. We emphasize and value peer instruction; all of the attendees will bring unique skills and expertise, and it is common that one of you will take on the role of instructor for a short session.
|1||Transport / cohort expectations||Data life cycle / management plan||installation of required tools|
|2||Data cleaning with Open Refine||The shape of data||using git and github|
|3||Open data (legal and ethical notions)||APIs and automated download||learner’s projects brainstorming|
|4||SQLite 1||SQLite 2||unstructured time|
|5||Scientific computing 101||Programming with data||parallel computing|
|7||Projects||Final presentations / Transport|
The registration fees are around 300 CAD for UdeM or CRÉPUQ students, and around 750 CAD for other students (these will be fixed shortly). The registration fees include room and board at the field station, as well as transportation from and to the university on the first and last days.