DE11&DE12: 4 Questions, 5 Visualizations

For Design Exercise 11 and 12, we ask you to pick 4 “questions” or “stories” to tell from the ATUS data (that you’ve been working with for the past few weeks). For one of these stories, you will submit an “alternate” design (hence, 5 visualizations).

For Design Exercise 11, you turn in a “draft” - saying what questions/stories you intend to make visualizations for, and drafts of those visualizations. For Design Exercise 12, you turn in a set of “final” visualizations, with rationales.

The Core of the Assignment

The idea of these assignments is for you to identify 4 stories you want to tell from the ATUS data set (provided at ATUS Data for 765-24). I am using the term “story” as a synonym for “question to answer from the data” - although the implication that a story is a rich answer hopefully holds.

You should choose 4 “good” stories. Questions that have interesting answers, are supported in the data, are multi-variate, and in general, lead to visualizations that allow you to show off your ability to tell stories with visualizations.

You should not use one of the questions given (to you by the course staff) in the earlier phases of the assignment.

The assignment rewards diversity in the set of questions.

You should create 4 high quality visualizations that tell these stories. The designs should stand alone - with sufficient titles, labels, and captions so that the viewer can understand and appreciate the visualization without having to read the rationale.

For one of these stories, you will create a second “alternate” design.

You are encouraged to augment the ATUS data beyond what we provide in the files (ATUS Data for 765-24). The data sources provide many more columns (e.g., more detail time categories). Alternatively you might find other interesting facts to connect (e.g., county-level income distributions).

The focus of your questions should be on the ATUS data set, and its main focus (how people spend their time). For example, you might get more detailed income information so you can examine how people spend their time in places with different median income levels. However, exploring the geographic distribution of income levels would be getting away from the spirit of the assignment.

Design Exercise 11

For Design Exercise 11: Drafts (due Fri, Nov 15) you will turn in your list of “questions”, and rough drafts of (some of) your visualizations. This exercise is mainly to serve as a checkpoint - and to force you to think about the questions and your designs before the last minute.

We will ask you:

1. To provide a list of the 4 questions you intend to make visualizations for.
2. To provide drafts for 2 of the visualizations that you intend to create. They should be good enough that someone can provide meaningful feedback.
3. If you are not a CLO student, you will be asked to provide a rationale for why you think your questions will be good for the assignment.

We cannot promise to provide feedback on DE11 before DE12 is due.

CLO students will have Design Discussion 3: DE11 Questions and Drafts (due Mon, Nov 11) to work together to refine their question lists, and critique each others’ drafts. Non-CLO students will be asked to justify their question lists.

DE11 is due Friday November 15, but we will not penalize assignments turned in by Monday, November 18th. Assignments turned in after the 18th will not receive credit.

Design Exercise 12

For Design Exercise 12: Final Designs (due Fri, Nov 22) you will turn in 5 visualizations (4 different “stories” and 1 alternate design for one of the stories). Each visualization will have a “rationale” explaining its design, why you think it is effective, and what you expect the viewer to see. For the alternate design, you should compare it to the other design for the same question.

The visualizations should stand alone. The viewer should not need to read the rationale to understand the story or appreciate the design. Good titles and captions can help with this.

The alternate design should be an alternate for one of the “primary” visualizations. The primary one should be your choice for the one that is “better” - but the alternate should still be good (in terms of effectively telling the main story). In the past, students would turn in bad alternates to make the primary design look good.

In addition to uploading 5 visualizations and rationales, you will be asked to provide answers to the following questions:

1. Describe one place in your visualizations (pick on of the 5) where you made a particularly good choice in how you addressed the challenges of scale. Explain the scalability solution that you chose, and why you think it works well.
2. Describe one place in your visualizations (pick on of the 5) where you made a particularly good choice in how color is used. Explain how your choice was informed by what you learned about color in class.
3. Did you augment the data, or use the files provided by the class at ATUS Data for 765-24? If you augmented the data, explain what data you added and how - this may be describing that you obtained your own version with additional columns from one of the sources of the ATUS data. It’s OK if your answer is simply “No”.
4. Provide attribution for anything you feel should be credited to others. If you found a question somewhere, or were inspired by someone else’s design, please say so.
5. If you were not part of the CLO, you will provide 2(*) critiques from previous designs (CLO students will provide critiques within their group on an earlier schedule).

If you are not part of the CLO, you will be asked to provide critiques for visualizations provided last year. For the first one, we include both the design and an alternate: your critique should compare the two, and discuss why you think one is more effective than the other (or at least weigh the pros and cons).

• Design 1 Design 1A - reading
• Design 2 - golf

CLO students will have Design Discussion 4: DE12 Drafts and Critiques (due Mon, Nov 18) to work together to provide feedback to each other about their designs. Non-CLO students will be required to critique 2 visualizations that we provide.

All students will complete the anonymous survey Class Survey 12: Design Challenge 2 Anonymous Post-Mortem (due Mon, Nov 25). This should be completed AFTER you have completed the assignment (the cutoff is set for 48 hours after the Monday no-cost-extension deadline).

Notes on Evaluation

Here, we give some advance warning on how we plan to evaluate your final visualizations as a hint for how to think about the assignment. The situation of the assignment is a bit contrived: usually, you don’t get to choose the story you want to tell with the data.

From DE6…

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.

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.

The Design Exercise Rubrics 04,05,06,07 described how we graded the first design challenge. While the details might change, this time will be similar.

Aspects of the Answers

Design Exercise Rubrics 04,05,06,07 (Design Exercise 6) gives a list of criteria for visualizations.

1. Question: Does the visualization ask a good question? (Does it have a story to tell)
2. Answer: Does the visualization answer the question effectively? (Does it tell the story well)
3. Design: Were good choices made in order to make the visualization effective?
4. Details: Were the details done well to support the effectiveness of the visualization? This includes titles, captions, labels, visual presentation, etc.
5. Rationale: Does the rationale support the choices made and explain how they connect to principles? The visualization should stand alone

The categories are not strict, for example: the effectiveness (2) of a visualization depends on (1,3,4); the use of color might be a detail, or it might be a major piece of the design (3 or 4); a callout might be a detail (4), or it might be a central design element (3); a really surprising and interesting question (1) might only require a simple design to be effective (2,3).

Not every visualization will excel at all 4 areas (all visualizations should aim to have great rationales). For the first 4, you can make up in some areas by excelling in others. (that doesn’t mean you have to - it is possible to have a solution that excels at everything).

Styles of Visualizations for an Assignment Like This

As mentioned in class, there are some different styles of solutions. This isn’t to say that one is better than another, but they have different challenges and ways to excel. Some types of solutions are harder to make than others, so the standards may be different

1. Standard Design (SD) - A standard design uses a standard chart type for data (and task) that fits it well. Standard designs excel through their use of good design choices (e.g., data selection, scalability strategy) and details to tell their stories well. Details are extremely important - if you’re going to make a standard design, make it well.
   • A special case of this we call Default Design (DD) - this is a category of solutions where there is an obvious “standard answer.” Even with a default design, it is feasible to excel even with a default design through attention to detail.
2. Adapted Design (AD) - Uses a standard design, but in a non-standard way. These designs often make interesting (but still valid) choices in how the data is fit to the design in order to tell a story in an interesting manner.
3. Compound Design (CD) - Uses a combination of simple (usually standard) chart types put together into a single, coherence visualization. Compound designs excel through the choice of the charts so that they work together to tell the story, and the visual details in making the charts work together.
4. Non-Standard Design (ND) - Uses a design that is unlike a basic chart type. These designs require more creativity to invent, and often require care to check their effectiveness. Such designs can excel through their creativity.