Design Challenge 1: Four Stories

Overview

In this assignment, you’ll pick one data set to make visualizations from. Then, you will make 4 visualizations – each telling a different “story” about the data. Then you will also make a 5th visualization that re-tells one of the stories from the first 4. The idea here is that you should explore the different kinds of visualizations you might make from this data, and the different questions/tasks that you might want to show someone, and to see how you can match the picture.

We will provide you with the data set. There are 3 choices (data sets listed at Design Challenge 1 – Datasets)- you can pick one (but you must pick one).

We would like to emphasize the use of “end-user” tools (such as Tableau). In fact, we will require you to at least try Tableau. We discourage you from doing any programming from this assignment. You may use any tools that you like to create the visualizations – subject to the constraint that you are required to hand in PDFs, and to document your process.

You will hand in real visualizations with the real data. If you find that you aren’t able to exactly implement your design (e.g. you can’t figure out how to convince excel to use the colors that you want), feel free to “cheat” a little (e.g., save the picture and open it in Photoshop and paint over it), but part of the idea is to try to make pictures with real data (so don’t just sketch – unless you are doing precise measurements). If you’re really stumped on implementation, you can put a note in your caption “the red dots were supposed to be blue” – but try not to leave too much to the imagination of the viewer.

We will grade your visualizations based on criteria detailed below. Generally, we care that you identify interesting things to show in the data (stories) and choose visualizations that effectively show those things.

Part of this assignment will be peer critique. You will turn things in without your name on it (so we can do critique anonymously). We will then give everyone a few designs from other class members to write critiques of. You will be graded on your critiques (but your critiques will not be used in grading the visualization).

Using Tableau is part of this assignment, although you don’t need to use it for your final turnin. There is pedagogical value in seeing Tableau as it is a nice embodiment of some of the “theory” we discuss in class.

Due Dates

1. Data Set Selection (Weds – Sept 18) – Check/No Check: did you pick a data set? Did you look at it at least a little?
2. Rough Drafts / Tableau Tests (Weds – Sept 25) – Check/No Check: Have you made at least some initial visualizations? Have you tried Tableau?
3. Design Turnins (Weds – Oct 2) – Graded: Turn in your four stories / five designs. Your documentation is also due.
4. Peer Review (Fri – Oct 11) – Graded: Turn in your critiques of the designs we have assigned you.

Detailed explanations below.

Stories and Visualizations

Try not to pick questions that can be answered with a single statistic – but something where the visualization adds value. The richer and more complex the task the story (or sets of stories) that the visualization tells makes it more interesting (and challenging), and gives you more opportunities to make a particularly cool “story”.

We’ve picked the data sets (but you get to choose amongst them). You get to pick the stories to tell. Think about stories that someone would care about. Stories that would be interesting.

A visualization should have a purpose – something that it helps the viewer see. This is the “story” that it tells. Visualizations that simply present the data (without something in mind) are not the goal here. “This visualization lets us see the distribution of grades in the class” is not as interesting (for this assignment) as “this visualization shows the correlation between how multi-variate a visualization is and the grade, letting us see that that mutli-variate visualizations are pretty much necessary for a good grade”.

Data Sets

The data sets you may use are described on (a page that will be coming soon). You must use one of the data sets that we provide. You may process the data or “augment it” (get some other data that helps interpret the data – for example you may find a table that helps you translate from three letter airport codes to city name or GPS coordinates).

Criteria

We care that you have a diverse set of stories: your visualizations show different aspects of the data.

For each visualization / story, we will check for:

1. Is the question/story interesting and clear?
2. Is it multi-variate?
3. Is the design effective? (is it well adapted to the story/task?)
4. Do the details represent good choices?
5. Is the design appropriate for the data?
6. Is the rationale properly stated (in the documentation)
7. Is the design complete (it has enough of a caption that it stands alone)?

For the “alternate” design, we will also check for:

1. Does it really tell the same question/story as the base?
2. Is it really different from the base?

The best designs for this assignment are multivariate and specifically adapted to the task/story. They may use a standard design (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. 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)

Generally, we look for diversity in designs. If all five 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.

How to Make Visualizations

You may use any tools that you like to create the visualizations – subject to the constraint that you are required to hand in PDFs, and to document your process. We ask that you try Tableau. It is fine to use Excel or Tableau or JMP or some other “tool.” We discourage you from programming to make your visualizations.

If you are going to make standard designs, you probably should use standard tools.

You may want to use some tools to “explore” the data initially, and then different tools to make the specific visualizations that you want. (although, good exploration tools are often sufficient for the kinds of visualizations students generally make for this kind of assignment)

We require you to at least look at Tableau (see below). You do not need to use it for your “final” designs.

We encourage you to use this assignment as an opportunity to explore different tools.

Note: you are turning in static visualizations as PDFs. You may use interactive tools to make them, but you need the visualizations need to “tell the story” as a static picture.

You may “edit” the visualizations that come from the tools (but please document this). For example, you might make a picture in Tableau, and then load that into PhotoShop or Power Point in order to add captions or adjust colors.

You may find you want to do some data wrangling, data cleaning, or analysis before visualization. Try not to make this the main part of the assignment. Many of the data sets are “clean” enough that you can use them directly in Tableau. If you need to do some programming for this part, it’s OK – be sure to describe what you did, and turn in the programs that you wrote.

Tableau

Tableau is a commercial data visualization and exploration system. It is an interesting and popular tool in its own right. For class it is particularly interesting because it makes many of the concepts (encodings, data abstractions, standard design selection based on data types, …) explicit. It also embodies many of the principles we will learn about (such as good color choices). Therefore, we really want you to at least try it.

It is also convenient for doing the initial exploration of the data so you can find interesting things to make visualization of.

Information on how to get access to Tableau for class in on a Canvas page.

We ask that everyone at least try to use Tableau to look at their data. We do not require that you use Tableau for the “final” visualizations that you turn in.

What to turn in for the deadlines

There are 4 separate “assignments” to turn in (one for each deadline). You are required to do all of them.

You receive a letter grade for the whole design challenge.

Deadline 1: Data Set Selection (September 18)

For this assignment, there will be a Canvas type-in box. You must tell us:

1. Which data set you have selected
2. Tell us a few facts about the data set to show us that you’ve at least looked at the data. This might be telling us about the abstract types of the data, or it might be some initial observations of the data.

We are mainly checking that you have started the assignment (and not waiting until right before the deadline). This portion will be graded check/no check. We may reduce your grade if you fail to complete this (especially if your final grade is at a borderline).

The list of data sets is Design Challenge 1 – Datasets.

If you want to go to the Tableau tutorial before deciding which data set to use, we will allow you to turn this part of the assignment in on Friday, September 20th without penalty. We won’t actually check if people come to the tutorial, so everyone can consider this their deadline.

Turn this in on Canvas: link

Deadline 2: Rough Draft / Tableau Tests (September 25)

For this assignment, we want to make sure you’ve at least tried Tableau, and have at least started to make visualizations.

You must upload a picture that you made with Tableau.

We are simply checking that you’ve done this. And it’s really on the “honor system” (we aren’t going to check too carefully). But, given the timing of the assignment, you probably want to have at least tried Tableau (even if you are deciding to use something else), and you should have made some rough draft visualizations (since you need to be converging on your final designs).

This portion will be graded check/no check. As long as you turn something in, we’ll assume your assignment is going well. If you don’t turn something in we may reduce your grade.

Turn this in on Canvas: link

Deadline 3: Designs (October 2)

This assignment is the “main” handin: you will turn in your designs and the documentation.

It is important that you turn this in as 6 separate PDFs, named as we need them. We need to send your designs out for peer review, so we need things in a specific format.

For your 4 stories/designs, please number them 1.pdf, 2.pdf, 3.pdf, 4.pdf. Please order your designs such that 1.pdf is the design that has an alternate (which will be in a separate pdf) Make sure that they are a single page and do not have your name on them. Each one should have a sufficient caption and labels that a viewer can figure them out. See the grading criteria for more discussion.

For your alternate design: please name the file “1a.pdf” (since it is an alternate of design 1 in 1.pdf) so we know which design it is the alternate for. Follow all the other rules for it being a stand alone PDF.

The 6th document (name it “description.pdf”) is a written description of the assignment. It should describe:

1. What tools you used to create the visualizations. If you did any programming, explain what the program does (e.g., “I wrote a Python script to transform the data by aggregating by state. This made it easier to make the graphs I wanted in Excel.”). (this can be a 1-2 sentences, but you might have separate descriptions for each visualization). Also tell us what libraries you used.
2. For each visualization (including the alternate), explain what the story you were trying to convey is, and why you think the design that you chose is appropriate. See the grading criteria. (this doesn’t need to be too extensive 1-3 sentences per visualization is usually sufficient)
3. For the alternate design, discuss which of the 2 different designs you think is most effective at conveying the story. (1-3 sentences)

Note: you should turn in exactly 6 PDF files, five of which should not have you name on them. All of these will be turned in via Canvas (which allows you to hand in PDFs),

The deadline is strict: if we do not receive your designs on time, we will not be able to send them out for peer review. You may receive some partial credit, but there will be a penalty.

This portion will be graded on an A-F scale. This grade will make up 80% of your overall DC1 grade.

Turn this in on Canvas: link

Deadline 4: Peer Critique (October 11)

Warning: the mechanics of how we will do this are still being worked out.

We will send you a few (probably 3) designs made by others to critique. We will ask you to write a critique of each. Brief is OK (a few short paragraphs), but it should have “critique” form as discussed in class. For each, you should try to critique its overall effectiveness by considering the design decisions made. (you shouldn’t limit yourself to a single design aspect).

It is our intent to send your critiques back to the visualization author.

You will be graded on the quality of your critiques on an A-F scale. This will be part of your overall Design Challenge Grade.

Note: The peer reviews are due on Friday (not Wednesday) since we need time to get you designs to review.

New For This Year

1. We are giving you a smaller set of choices for the data set. We are asking you to pick one that we know is sufficiently interesting and challenging. This should mean you can spend less time deciding what dataset may be good for the assignment and more time making visualizations.
2. We are making peer review be a more explicit part of the assignment. We will ask you to critique a few designs made by classmates.
3. We require you to at least try Tableau.
4. We are more explicit about the documentation requirements.