DE06: One Data Set, Four Stories (Census Data Edition)

Design Exercise 6 asks that you make 4 visualizations, each telling a different story, from the Census Data data set. This assignment extends DE05: Stories from Data (EDA).

This assignment asks that you create 4 different visualizations from the Census Data data set. Each one should tell a different story. Part of the point of the exercise is to show how different visualizations tell different stories from the same data. And part of the assignment is about identifying those stories to tell in data, and telling them effectively in visualizations.

Hopefully, you will notice that the goals here are very similar to DE05: Stories from Data (EDA). Indeed, we encourage you to use your results for that previous assignment as the first two of your stories here. With a week of extra thinking and learning (and feedback if you turned them in on time), you might want to improve them.

Unlike DE05: Stories from Data (EDA) we are not asking you to show your exploratory process. We are only asking for your “final” visualizations and their rationales.

The assignment

You need to identify four (different) stories in the Census Data data set, and create (four different) visualizations that tell each one. Your visualizations should tell their respective stories effectively (and not be as effective at the other stories).

You will provide the visualizations, and a description (of the story) and the rationale for why you made the visualization (explanations of the choices you made). In principle, this shouldn’t be necessary - the story should jump out from the visualization (with some help from its title and caption), and the choices that lead to its effectiveness would be clear. In practice, play it safe and tell us why you think things work. Sometimes the data or design doesn’t quite cooperate.

You must turn in static pictures. You can turn in images (PNGs or JPGs) or single page PDFs. You may use whatever tools you like to produce these pictures. For example, you might make charts using screen capture in Tableau and add captions and annotations in PowerPoint.

The ground rules from DE5 apply - but they are common sense (static, single pages; be faithful to the data, but not obsessive; etc.).

Criteria

For each visualization / story, we will check for:

• Is the question/story interesting and clear?
• Is it multi-variate?
• Is the design effective? (is it well adapted to the story/task?)
• Do the details represent good choices?
• Is the design appropriate for the data/story?
• Is the rationale properly stated (in the documentation)
• Is the design complete (it has enough of a caption/labels that it stands alone)?
• Does the design address scalability issues in a meaningful way?

The best designs for this assignment are multivariate and specifically adapted to the task/story. They may use a standard design (e.g., stacked bar chart), but use good choices in the details (e.g., the ordering of the bars or the colors) to make the “answer to the question” easy to see. They use a good strategy for dealing with the scale of the data. We look for signs of students making explicit good choices to make what they want the viewer to see easy to see. (you can explain your choices in the documentation)

We will look for diversity in the stories that you choose to tell with the visualizations.

Generally, we look for diversity in designs. If all of your visualizations are bar charts, that’s often a bad sign. Of course, if it really is the case that you have found four questions that are each best answered with various bar charts, that’s less of an issue. But in general, you may want to pick stories that are told with a variety of designs. You may also choose different strategies for scalability (you probably don’t want to show a mark per county for all counties in all of your visualizations).

To emphasize: what we are looking for are what explicit choices you made to emphasize your “story.” A “data dump” (just making a chart of some of the variables) is not likely to get you a good score. If you make explicit decisions - selecting subsets or data, highlighting particular points, arranging designs that emphasize certain aspects, etc. - this will be rewarded.

More information on how we will grade this is available at Design Exercise Rubrics 04,05,06,07. The DE5-6 Codes: Feedback can give you a sense of the kinds of things we look for (and is practically a tutorial in what to try to do).

Turning things in

As usual, we will turn in the assignment as a Canvas Survey Design Exercise 06: One Dataset - Four Stories (New Deadline) (due Fri, Oct 18). We recommend you prepare your answers (4 pictures, each with a description/rationale) before uploading things to the survey.

You need to upload 4 images.

The deadline for turning in the assignment is strict. You must turn it in on Friday, October 18th. On Saturday, October 19th, we will send your designs to your classmates so they can critique it as part of De07: Critiquing Census Data Stories.

If you don’t turn in at least two (of the 4) visualizations by the deadline, we will won’t be able to send your designs for critique. This means we will need to provide some other visualization to be critiqued. If we have to do this, we will deduct 1 letter grade for each visualization we need to provide. This means if you turn in your assignment late, we will still grade it - but if you earn an A, you will receive a C.

Be sure to give yourself ample time to upload and check your uploads in Canvas. If there isn’t a valid visualization for us to send for critique, you will be penalized. Canvas does have a habit of being flaky around deadlines… (see Canvas Caveats - this does not let you avoid the penalty for late assignments).