July 11-12, 2019
8:30 a.m.-4:30 p.m.
Instructors: Carolyn Voter, Sarah Graves, Maria Kamenetsky
Helpers: Trisha Adamus, Srikanth Aravamuthan, Karl Broman, Cid Freitag, Christina Koch, Michael Liou, Tobin Magle, Sarah Stevens, Steve Wangen
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 geospatial analysis, but you should have at least some basic familiarity with R.
Where: Memorial Union, 800 Langdon St, Madison, WI 53706. Get directions with OpenStreetMap or Google Maps.
When: July 11-12, 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).
Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
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.
If you are a student and the workshop fee is unaffordable for you, ask your advisor if they have funds to cover the cost as this workshop considered professional development. If your advisor does not have funds to cover this cost or or you are not able to ask them about the cost and you can not afford the workshop, please contact us at the address below to apply for a special assitance fee waiver.
Contact: Please email facilitator@datascience.wisc.edu for more information.
Please be sure to complete these surveys before and after the workshop.
| Before starting | Pre-workshop survey |
| 8:30 - 9:00 | Setup help |
| 9:00 - 10:30 | Introduction to R, lessons 1-4 [Intro to R and R Studio] [Project Management] [Data Structures] [Exploring Data Frames] |
BREAK | |
| 10:45 - 12:30 | Introduction to R, lessons 5-8 [Subsetting Data] [Data Frames with dplyr] [Intro to Visualization] [Writing Data] |
| 12:30 - 1:30 | LUNCH |
| 1:30 - 3:00 | Introduction to Geospatial Concepts |
BREAK | |
| 3:15 - 4:45 | Introduction to Geospatial Concepts |
| Introduction to Geospatial Raster and Vector Data with R (Setup) | |
| Evening | END |
| 8:30 - 9:00 | Setup help |
| 9:00 - 10:30 | Geospatial data in R, lessons 1-5 [Introduction to Raster Data] [Plot Raster Data] [Reproject Raster Data] [Raster Calculations] [Multi-band Raster] |
BREAK | |
| 10:45 - 12:30 | Geospatial data in R, lessons 6-10 [Open and Plot Shapefiles] [Explore and Plot Shapefile attributes] [Plot Multiple Shapefiles] [Handling Spatial Projection & CRS] [Convert from .csv to Shapefile] |
| 12:30 - 1:30 | LUNCH |
| 1:30 - 3:00 | Geospatial data in R, lessons 11-12 [Manipulate Raster Data] [Raster Time Series Data] |
| 3:00 - 4:15 | Introduction to Geospatial Raster and Vector Data with R (Lessons 12-14) [Create Publication Quality Graphics] [Derive Values from Raster Time Series] |
| 4:15 - 4:30 | Final Remarks |
| Evening | Post-workshop survey |
| END |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
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.
For the Geospatial Data Carpentry Workshop, you will also need to follow the directions here (Option A) for the geospatial specific software.