Data Carpentry @ UW Madison

August 27 - 28, 2018

8:30am - 4:30pm

Instructors: Trisha Adamus, Karl Broman, Maria Kamenetsky, Christina Koch

Helpers: Cameron Cook, Erin Jonatis

Registration is required and will be available just below, starting at 5:00pm on Monday, 6 August 2018. Make sure to read all details below before registering and to choose appropriately between UW-Madison’s Data Carpentry and Software Carpentry workshops.

General Information

This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data. The workshop is for any researcher who has data they want to analyze, and no prior computational experience is required.

For researchers who have already been programming and seek to expand their capabilities, our UW-Madison Software Carpentry workshop (August 29-30) will likely be more appropriate. These two workshops are NOT intended to be taken back-to-back, and you can learn about future workshops at UW-Madison by joining the mailing list of UW-Madison’s Advanced Computing Initiative.

What is Data Carpentry? Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. 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 UW-Madison-affiliated students, faculty, staff, and other researchers.

Where: Orchard Room, Discovery Building, 330 N. Orchard St., Madison, WI, 53715. Get directions with OpenStreetMap or Google Maps.

When: August 27 - 28, 2018. 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 contactaci@lists.wisc.edu for more information.


Surveys

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

Pre-workshop Survey

Post-workshop Survey


Schedule

Day 1 (Mon, Aug 27)

Before starting Pre-workshop survey
8:30 - 9:00am Software set-up help
9:00 - 9:15am Introduction
9:15 - 10:30am Data organization in spreadsheets
10:30 - 10:45am Break
10:45am - 12:00pmOpenRefine for data cleaning
12:00 - 1:00pmLunch
1:00 - 2:30pmData management with SQL
2:30 - 2:45pmBreak
2:45 - 4:30pmData management with SQL
4:30 - 4:45pm Wrap-Up
4:45pm END

Day 2 (Tues, Aug 28)

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 [R script]
12:00 - 1:00 Lunch Break
1:00 - 2:30 Data Visualization with ggplot2 [R script]
2:30 - 2:45 Coffee
2:45 - 3:15 Reproducible reports with R Markdown
3:15 - 4:00 Capstone project [Solutions: Rmd | html]
4:00 - 4:15 Wrap up and fill out the post-workshop survey (see above)
4:30 - 5:30pm Social Get-Together (optional)
END

Syllabus

Open Refine

  • Introduction to OpenRefine
  • Importing data
  • Basic functions
  • Advanced Functions
  • Reference...

Programming in R

  • Working with vectors and data frames
  • Reading and plotting data
  • Creating and using functions
  • Loops and conditionals
  • Using R from the command line
  • Reference...

Setup

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

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

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.

macOS

Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

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.

SQLite

SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons. We will use the DB Browser for SQLite program, which is available for all major platforms. This is the program you should install before the workshop.

OpenRefine

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.

Windows

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 google-refine.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.

Mac

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.

Linux

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.