Project One: Dear Data

Published

September 8, 2025

Objectives

  • Get some hands on experience working with data
  • Get you thinking creatively about visualization before you get too familiar with standard techniques

Prerequisites

  1. Create the git repository for your practical by accepting the assignment from GitHub Classroom. This will create a new repository for you with a bare bones npm package already set up for you.

  2. Clone the repository to you computer with git clone (get the name of the repository from GitHub). See the git basics guide if you are new to this

Dear Data

Dear Data was a year long exchange of hand drawn visualizations documenting weekly occurrences. Read about the project at http://www.dear-data.com/theproject/. Then visit the archive of all of the postcards that they produced over the year. Pick at least three representative weeks that look interesting and study them. Look at the keys and try to read the visualization. Then visit the “read more” link and read about their process and thoughts about the week. You can also check out Dear Data Two, another pair of vis folks who decided to do their own year of visualization postcards. Their aesthetic is definitely different and a bit more technical, which can probably be attributed to their backgrounds.

You are going to produce your own personal dataset and draw a custom visualization that reflects it.

Data Collection

  • The theme of the data collection will be quantified self. The quantified self movement is all about reflective self knowledge gained through tracking data about your daily activities.
  • The data you collect should be multivariate (i.e., have more than one piece of information per observation). For example, if you were tracking your your eating habits, you wouldn’t just record the time you ate, you might record the time, how long you were eating, what you ate, where you ate, who you ate with, what the weather was like, etc…. Note that the time of the observation is always a “freebie” data variable, but don’t feel you need to use it if you can tell a more interesting story without it.
  • You should collect data for five solid days (a full 120 hours).
  • You should have a minimum of 20 observations.
  • How you collect the data is up to you. Georgia and Stephanie found using their phones to be the most convenient, but they were thinking in terms of recording information every day for a year. You could use a piece of paper folded up in your pocket. You are welcome to use tracking technology (fitbit, apple watch, gps,…), but don’t let yourself get restricted to what they collect (i.e., use them to augment your data collection, not replace it).

The Visualization

You should now pick some encodings for each of your variables (hopefully you already know what your variables are). Do not feel constrained to any style of visualization you have seen before. As you can see from the couple of postcards shared by Stephanie and Giorgia, the encodings can be almost anything. The only important thing is that someone could extract the data back out of the visualization.

Along those lines, you will need to provide a key. The key should tell the reader everything she or he needs to be able to interpret your drawing.

The visualization and the key should fit on one side of a card (which I will provide). You can divide the space between the key and the visualization however you like, provided they both fit and can be read. You are welcome to use any implement you like (pencil, pen, marker, colored pencils, paint brush, ruler, protractor, etc…). The only requirement is that it be hand drawn. Also, if you use more than one color, the color should be used to convey information.

Do not stress about your drawing skills. This is not a technical drawing class. As you can see, the Dear Data postcards are not finished works of art. Your goal is to convey information through imagery.

Do make drafts. Your final visualization will be far better if you start by making several rough sketches to see if your idea works than it will if you sit down with ruler and protractor and sweat over a single iteration. (Along those lines, while length and size are fine encodings, I am not expecting precision. A perfect, hand-drawn bar chart that I can accurately pull values off with a ruler is not what I am looking for.)

I will expect to see at minimum one draft.

Deliverables

You will be submitting everything to Gradescope using the repository you cloned at the beginning. I also expect you to turn in the physical copy of your visualization at the start of class on the due date.

The main visualization that you turn in should be on the provided card. As I said above, both the visualization and the key should fit on one side of a card. I will be looking for all of the variables to be encoded in some way that I can figure out (roughly) what the observations were (as I said, I do not expect to be able to accurately recover quantitative data). The key should be clear about how the information is encoded. Your encodings should be unambiguous. In other words, while I may not be able to tell if you ate at 1:00 vs 1:30, I should be able to tell the difference between Ross and Atwater (for example).

In the packet submitted to Gradescope, I will expect:

  • a digital copy of visualization a shot taken with your phone (or someone else’s phone) is fine
  • pictures of your drafts in the drafts folder there should be at least one
  • the drafts/drafts.md file should be filled in with information about each of your drafts
  • the questions in the reflections.md file filled in to tell me about your process. This will include one insight you gained while creating/looking at you visualization. Ideally, this should be something you learned about yourself (or the subject of your visualization) that you didn’t know before you created the drawing. Failing that, describe an insight that you hope a viewer would have looking at your visualization.

When you are ready, - commit your work to the repository (see the git basics guide if you are unfamiliar with this process) - push the work to github - submit the repository on Gradescope (see the Gradescope submission guide)