Create an Original Data Visualization


  Date: 2024-07-31
  Author: Nathan Pieplow
  License: CC BY-NC-SA
  Domain: Persuading with Data
  Subdomain: Visualizing Data
  Type of Resource: Assignment

This assignment sequence asks students to sketch, draft, workshop, and revise an original data visualization using data they find themselves online.

Keywords:  Rhetoric of Data Visualization    Visual Rhetoric  

MLA Citation: Pieplow, Nathan. ‘Create an Original Data Visualization’ (assignment sequence). Data Advocacy 4 All, University of Colorado. 31 July 2024


Introduction for Instructors

This assignment sequence asks students to sketch, draft, workshop, and revise an original data visualization using data they find themselves online. It is designed to form part of the Individual Data Advocacy Project assignment sequence, but could be adapted as a standalone assignment.

Before they begin this assignment sequence, students should have located a dataset that they want to visualize, and they should have seen the Introduction to Data Visualization videos and the How to Create a Data Visualization slide deck.

Below are the student-facing instructions for the three component assignments.

Assignment 1: Create Sketches for Your Visualization

Each of you will be creating an original data visualization as part of your individual data advocacy project. For next class, draw at least 10 sketches for what your data visualization might look like.

I recommend using paper and pencil and then uploading a photo, but you can do digital drawings with a stylus instead. Remember, sketches are disposable. If you’re spending a lot of time making them look pretty, you’re doing it wrong. A sketch is just a quick outline of a visual idea. Sketching requires you to have a basic understanding of what your data will look like, but it doesn’t have to be accurate at all.

The purpose of asking you to create 10 sketches is to get you to think beyond the simple line chart or bar chart, into some other ways to present your data that will clearly highlight the relationships you want to show. See slide 29 of the How to Create a Data Visualization slide deck for examples of data visualization sketches.

Assignment 2: First Draft of Original Data Visualization

For this assignment, take one of the 10 sketches you did (or create a new one if you like) and render it as an accurate and professional-looking data visualization that you can insert into your individual data advocacy project to make your argument more convincing and easier to understand. If it isn’t perfect, don’t worry – this is a first draft. But do your best to make it as nice as you can.

You can create your visualization in any platform you like. However, if you don’t have a lot of experience with making visualizations, then I recommend one of the following methods, the first two of which are covered in the How to Create a Data Visualization slide deck.

  • If you’re creating a pretty standard chart type (bar chart, pie chart, line graph, etc.) then you can use Microsoft Excel, Google Sheets, or any other standard software that makes visualizations. But if you use Excel or similar software, don’t just accept the default settings. Instead, customize the viz to minimize clutter and use annotations and color to highlight the main story.
  • If you’re creating a more creative chart type, or if you just want full control over the look of your viz, you can create your viz by hand in Microsoft PowerPoint, Google Slides, or fancy image software such as Illustrator or Inkscape. One way is to start with a chart created in Excel or other software, screenshot it, import it into PowerPoint or Slides, trace over it using the drawing tools, and then delete the screenshot, leaving your own graphic that you can customize however you like. Another method is to hand-draw the viz from scratch using the drawing tools, and then use the “Format Shape” and “Arrange” options to precisely control the dimensions and arrangement of each element on the slide. Once you’ve got a slide looking like you want it, you can export it to PDF format.
  • If you want to create an interactive viz – one where labels or explanations pop up when you mouse over different areas, or one that lets users see how the visualization changes as you move sliders or choose options from dropdown menus – then I recommend using Tableau Public. Tableau definitely has a bit of a learning curve, but by watching some online tutorials, you should be able to figure out how to do what you want.
  • If you want to create a map, I recommend either Mapbox or Tableau Public. Remember, maps require datasets that have columns for geographic locations – either latitude and longitude, or the names of geographic places or regions (countries, states, counties, etc.). Give one of these methods a shot and let me know if you run into trouble.

Assignment 3: Write Workshopping Comments on Your Groupmates’ Data Visualization Drafts

On each draft, I want you to write at least six comments, at least three of which should be suggestions for improvement. When critiquing data visualizations, remember the six key principles of data visualization:

  • See the story in the data: Can you immediately understand the viz when you look at it? Are the most important things also the most visually obvious? How could the viz be made easier to understand?
    • Ask yourself: If I only looked at this for three seconds, what would I see? Would I come away with the main idea? If not, the story might not be obvious enough.
  • Use the right graphical elements: Did the author choose the right chart type? Are they using color, position, size, image, and/or text wisely?
  • No decoration without design: Do any elements of the visualization give us more to look at without giving us more to learn?
  • Compare apples to apples: If multiple datasets are being plotted on the same axes, are those datasets actually comparable?
  • Understand reader expectations: Does the visualization adhere to standard conventions such as time flowing left to right, up meaning more, red=hot and cold=blue? Or does it defy expectations? If it does something unexpected, does it give the reader enough visual cues to eliminate confusion?
  • Choose your frame of reference wisely: What is/are the frame(s) of reference and are they appropriate? Remember, axes don’t always have to start at zero – but if you don’t start your axis at zero, you need to have a good reason for that.

Also check for the four ways to make a visualization compelling:

  • Ruthlessly eliminate the unnecessary: Do you see ANY element of the visualization that could be taken out?
  • Apply labels, not legends: Does the visualization put the names of things right next to the things? If not, how could it do that?
  • Color the story: Does the visualization use color (or the lack of color) in a way that highlights the main takeaway?
  • Use your words: Do the title, subtitle, and labels of the visualization clearly convey its main takeaways? Does the visualization cite a data source?