University of Oklahoma

Jan 10-11, 2019

9:00 am - 4:30 pm CST

Instructors: Josh Hatzis, Braden Owsley

Helpers: Dawn Nekorchuk, Mark Laufersweiler

General Information

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: 100 Boyd St, Room N106, Sarkeys Energy Center, Norman, Ok. Get directions with OpenStreetMap or Google Maps.

When: Jan 10-11, 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 or for more information.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


Programming in R

  • Working with R in the RStudio GUI
  • Project management and file organization
  • Importing data into R
  • Introduction to R’s core data types and data structures
  • Manipulation of data frames (tabular data) in R
  • Introduction to visualization
  • Writing data to a file
  • Reference...

Geospatial Concepts

  • Intro to raster and vector data format and attributes
  • Examples of data types raster vs vector format
  • Intro to categorical vs continuous raster data and multi-layer rasters
  • Intro to file types and R packages used
  • Intro to coordinate reference systems and the PROJ4 format
  • Overview of commonly used program and applications
  • Reference...

Geospatial Raster and Vector Data with R

  • Import and export rasters in R
  • Create custom plots with raster and vector data
  • Reproject raster and vector data in R
  • Perform a subtraction between two rasters using multiple methods
  • Work with multi-band and time series rasters in R
  • Import point, line, and polygon shapefiles into R
  • Query and subset vector data by attributes
  • Convert data frames to/from spatial data
  • Extract and export summary pixel value from rasters
  • Reference...


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.


Video Tutorial

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.


Video Tutorial

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.