June 11-12, 2019
8:30 am - 4:30 pm
Instructors: Trisha Adamus, Erin Jonaitis, Maria Kamenetsky, Tobin Magle
Helpers: Srikanth Aravamuthan, Steve Goldstein, Michael Liou, Heather Shimon, Sarah Stevens
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".
Registration fee covers morning coffee and snacks, lunch is available at the UW Hospital Cafeteria, a short walk away.
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: Interactive Learning Center at HSLC, 3rd floor, Rooms 3110 A & C, 750 Highland Ave, Madison, WI 53705-2221. Get directions with OpenStreetMap or Google Maps.
When: June 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 - 9:00am | Software set-up help |
| 9:00 - 9:15am | Introduction [ Slides ] |
| 9:15 - 10:30am | Data organization in spreadsheets |
| 10:30 - 10:45am | Break |
| 10:45am - 12:00pm | OpenRefine for data cleaning |
| 12:00 - 1:00pm | Lunch |
| 1:00 - 2:30pm | Data management with SQL |
| 2:30 - 2:45pm | Break |
| 2:45 - 4:30pm | Data management with SQL |
| 4:30 - 4:45pm | Wrap-Up |
| 4:45pm | END |
| 8:30 - 9:00 | Installation Help |
| 9:00 - 9:15 | Day 2 intro |
| 9:15 - 10:30 | Intro to R |
| 10:30 - 10:45 | Break |
| 10:45 - 12:00 | Data manipulation with dplyr |
| 12:00 - 1:00 | Lunch Break |
| 1:00 - 2:30 | Data Visualization with ggplot2 |
| 2:30 - 2:45 | Coffee |
| 2:45 - 3:15 | Reproducible reports with R Markdown |
| 3:15 - 4:00 | Capstone Project |
| 4:00 - 4:15 | Wrap up and fill out the post-workshop survey (see above) [ Slides ] |
| 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.
For the spreadsheets lessons you will need to have a spreadsheet program, such as Microsoft Excel or the Calc program in OpenOffice . If you do not already have one of these programs installed, please follow the links above to install.
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.
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.
Visit SqliteBrowser and download and install it. Version 3.11.0 or greater.
Visit SqliteBrowser and download and install it. Version 3.11.0 or greater.
Visit SqliteBrowser and download and install it. Version 3.11.0 or greater.
If you installed Anaconda, it also has a copy of SQLite
without support to readline.
Instructors will provide a workaround for it if needed.
For this lesson you will need OpenRefine and a web browser. Note: this is a Java program that runs on your machine (not in the cloud). It runs inside a web browser, but no web connection is needed.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It will not run correctly in Internet Explorer.
Download software from http://openrefine.org/
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by right-clicking and selecting "Extract ...".
Go to your newly created OpenRefine directory.
Launch OpenRefine by clicking openrefine.exe (this will launch a command prompt window, but you can ignore that - just wait for OpenRefine to open in the browser).
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It may not run correctly in Safari.
Download software from http://openrefine.org/.
Create a new directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory by double-clicking it.
Go to your newly created OpenRefine directory.
Launch OpenRefine by dragging the icon into the Applications folder.
Use Ctrl-click/Open ... to launch it.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.
Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser.
Download software from http://openrefine.org/.
Make a directory called OpenRefine.
Unzip the downloaded file into the OpenRefine directory.
Go to your newly created OpenRefine directory.
Launch OpenRefine by entering ./refine into the terminal within the OpenRefine directory.
If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.