Instructions

Over the course of the term, we've made a number of different visualizations during lectures. While the primary goal of the lectures was not to create a polished, publishable visualization, it's a bad idea to consider what changes it would take to prepare a visualization for publication and sharing. In this activity, you will take an existing lecture demo from some time during this term and change, augment, and add content to make it ready for a web audience. Here are some factors to consider:

• Your audience is the general Internet population. We want these visualizations to go viral on Twitter or r/dataisbeautiful.
• Follow best principles with regards to visual channels, use of color, space, etc.
• Add visual elements and annotations when necessary to help users understand what is going on.
• Add interactivity to deepen the experience and address missing user needs (e.g. seeing point details).
• Add non-visualization elements like supporting text and data tables to improve the user experience.
• If your group disapproves of the visualization as a whole for the data, come up with something better!

Please follow this procedure:

Step 1 - 12 minutes - [GROUP] Pick visualization and critique

1. As a group, look at each of the visualization choices and choose one to improve.
2. Together, take a look at the visualization and critique it based on the common pattern we have used in past critiques (included at the bottom). Identify between 3 and 5 specific areas that are in need of improvement (e.g. deepening interactivity, improving a visual channel, adding supporting contents).
3. Rank those areas in order of importance using any method you'd like

Step 2 - 10 minutes - [INDIV] Sketch improvements

1. Now, working individually, begin making either one sketch of an improved visualization or a series of idea sketches for each improvement area. Keep them low fidelity and focus on the specific critique items to which you are responding.
2. Refer back to the visualization and your critique.
3. Keep polishing your ideas until your group reconvenes.

Step 3 - 15 minutes - [GROUP] Final design

1. As a group, go around and discuss each person's sketches. Keep it to 1 minute per sketch.
2. Working together, create a consensus design sketch. You will need to pick a group member to record your final idea and present it to the class, but everyone should sketch as they go.
3. We will reconvene at the end to check out everyone's improved visualizations.

Your visualization options

• Scatterplot matrix - A matrix of scatterplots that attempt to show the relationship between average game rating, number of users who rated, the time a game takes on the Board Game Geek web site dataset. Brushing interactions allow the user to isolate across cells, and color is used to highlight how many brushes "match" a point.
• P&P relationship diagrams - This node-link diagram shows phrase-level relationships between words in the novel Pride and Prejudice. Attention was paid in the lecture to graph layout algorithms and trying to improve clarity in the swarm of text elements.
• Color hexagons - These hexagons present the surface of a color cube of color name data. We initially surveyed individuals for color names so as to show how few names exist for dramatically different colors. Mouseovers help to show color names.
• Color spray wheel - We augmented a visualization of the color survey name data with an animated intro and a data table. Linked highlights try to help users see patterns among the color names.

Critique Guide

Design critique can take any number of forms. Some outline pros and cons, or identify particular visual elements and break them down. Others start with the data and discuss the construction of the visualization from the ground up. In your group, feel free to set up whatever norms you prefer for design criticism.

Here are some questions to help guide your critique:

• What kind of data is the visualization presenting?
• What is the purpose of this visualization? How has the designer tailored this visualization to meet particular user information needs or goals?
• Does this visualization require training/study to work, or is it immediately effective?
• How are the data encoded into visual form? Does the author use specific visual channels (in)effectively to represent certain dimensions?
• What design trade-offs are present in the visualization? Are they emphasizing some part of the data at the expense of something else?
• How is interaction employed in this visualization? Are there any trade-offs that come from introducing interactions? Are the interactions helpful?
• Do you feel that this visualization is successful? What elements help make it effective, and what hurt its effectiveness?
• What’s missing from the visualization that would improve it? Is any element of the visualization misleading or at risk of misinterpretation?
• How would you do things differently if you were to re-design it?