Jan 22-23, 2019
9:00 am - 4:30 pm
Instructors: Jarrett Byrnes, Katie Lotterhos, Klaus Schliep
Helpers: Isaac Rosenthal, Caroline David, Christopher Beltz, Laura Ganley
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
For more information on what we teach and why, please see our paper "Good Enough Practices for Scientific Computing".
Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: Room 2110, University Hall, 100 Morrissey Blvd, Boston, MA. Get directions with OpenStreetMap or Google Maps.
When: Jan 22-23, 2019. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email jarrett.byrnes@umb.edu for more information.
Please be sure to complete these surveys before and after the workshop.
| Before starting | Pre-workshop survey Please install all of the requisite software and data |
| Morning | Introduction to Geospatial Concepts |
| Afternoon | Introduction to R for Geospatial Data |
| Evening |
| Morning | Introduction to Geospatial Raster and Vector Data with R |
| Afternoon | Continuation of Geospatial Raster and Vector Data with R |
| Evening | Post-workshop survey |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code. Code generated during the class can be found in this github repository
To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager (e.g. for Debian/Ubuntu
run sudo apt-get install r-base and for Fedora run
sudo dnf install R). Also, please install the
RStudio IDE.
Unlike other workshops, there is a good bit of additional software and very large data files to install for these lessons. We advise you to install these after R at least one week before the workshop as well as downloading the data. Please follow the relevant instructions on this page carefully and contact the instructors with any installation issues.