Welcome to Communicating with Data!
Hello! I’m Sara Stoudt, and I’m teaching “Communicating with Data” at Smith College this fall. The class has no pre-requisites, so I have students (almost 70 of them!) from a variety of majors from history, to biology, to statistical and data sciences. The goal is to be able to tell data stories to a broad audience through data visualization and precise yet accessible writing.
This semester, since we are all participating remotely, we are especially thinking about accessibility considerations in terms of data visualization. Who do we exclude when we communicate data on a screen? We’ll consider how our choices reflect our assumptions about our audience, and how we can be intentional about making sure we are communicating technical results in a more digestible format.
Learning to communicate with data is also about being heard. This newsletter is a way to give students the opportunity to share what they are learning and what they are creating in the class with a broader audience. I’ll also contribute tips from a pedagogical point of view for those readers interested in bringing elements of data communication into their own classrooms.
Here is Emily Grantham to introduce what we’ve been up to so far.
The first two weeks of Communicating with Data were all about introductions -- an introduction to what our goals as a class would be, an introduction to the platforms which make charting data possible, and an introduction to the world of data storytelling. First, we learned about data and plot basics. Reviewing data distribution vocabulary and chart types, we discussed “genres of storytelling” and how each choice we make in plotting information can impact the way the reader understands the data.
After becoming accustomed to some of the concepts that guide data visualization decisions, we moved on to practice creating our own data visualizations. Through a series of labs that had us recreate real world plots (like this one), we got comfortable with the building blocks of making charts on Datawrapper and manipulating data in Google Sheets. Working with both platforms in small groups, we learned how to wrangle data in pivot tables to make it compatible with Datawrapper’s plotting capabilities. Check out this recreation by Jacqueline, Salwa, Ratie, and Elaine.
The final task we worked on in these first couple weeks was creating our first Dear Data -- a project where you collect and visualize data from your own life. For this first assignment, we each individually collected data on our schedules, charting things like how much time we spend on different activities, when we feel the most and least energetic, and how much of our day is spent using technology. We used a “design sprint” framework to brainstorm in small groups how to get our data from notebook to canvas.
These activities marked the beginning of a semester of learning to make data more accessible and impactful through real world, user-friendly practice.
Here is Jack Brando to tell us what is coming next.
This week, students will look up from their schedules and look outside to the ever changing fall weather for their next Dear Data. Through the power of communication, students will learn strategies for giving and receiving peer feedback, as well as using this feedback to make their new Dear Data approaches even better!
Simultaneously, students will begin collecting visualizations for their first solo project, the “Mood Board.” This personalized projects will allow students to explore certain aspects of data which they enjoy and articulate what attracts them to certain visualizations.
Stay tuned for more exciting content from the Communicating with Data team!