Assignment 1: Visualization Design

In this assignment, you will design a visualization for a small data set and provide a rigorous rationale for your design choices. You should in theory be ready to explain the contribution of every pixelin the display. You are free to use any graphics or charting tool you please - including drafting it by hand. However, you may find it most instructive to create the chart from scratch using a graphics API of your choice.

(See Resources for a list of visualization tools.)

Data Set: Antibiotics

After the World War II, antibiotics were considered as "wonder drugs", since they were an easy remedy for what had been intractable ailments. To learn which drug worked most effectively for which bacterial infection, performance of the three most popular antibiotics on 16 bacteria were gathered.

The values in the table represent the minimum inhibitory concentration (MIC), a measure of the effectiveness of the antibiotic, which represents the concentration of antibiotic required to prevent growth in vitro. The reaction of the bacteria to Gram staining is described by the covariate “gram staining”. Bacteria that are stained dark blue or violet are Gram-positive. Otherwise, they are Gram-negative.

Dataset: csv

Assignment

Your task is to design a static (i.e., single image) visualization that you believe effectively communicates the data and provide a short write-up (no more than 4 paragraphs) describing your design. While you must use the data set given, note that you are free to transform the data as you see fit. You are also free to incorporate external data as you see fit. Your chart image should be interpretable without recourse to your short write-up. Do not forget to include title, axis labels or legends as needed!

As different visualizations can emphasize different aspects of a data set, you should document what aspects of the data you are attempting to most effectively communicate. In short, what story are you trying to tell? Just as important, also note which aspects of the data might be obscured or down-played due to your visualization design.

In your write-up, you should provide a rigorous rationale for your design decisions. Document the visual encodings you used and why they are appropriate for the data. These decisions include the choice of visualization type, size, color, scale, and other visual elements, as well as the use of sorting or other data transformations. How do these decisions facilitate effective communication?

Grading

The assignment score is out of a maximum of 10 points. Historically, the median score on this assignment has been 8.5, which corresponds to an A-. We will determine scores by judging both the soundness of your design (e.g., in accordance with the expressiveness and effectiveness principles) and the quality of the write-up. We will also look for consideration of audience, message and intended task. Here are examples of aspects that may lead to point deductions:

• Use of misleading, unnecessary, or unmotivated graphic elements.
• Missing chart title, axis labels, or data transformation description.
• Missing or incomplete design rationale in write-up.
• Ineffective encodings for your stated goal (e.g., distracting colors, improper data transformation).

We will reward entries that go above and beyond the assignment requirements to produce effective graphics. Examples may include outstanding visual design, meaningful incorporation of external data to reveal important trends, demonstrating exceptional creativity, or effective annotations or other narrative devices.

Submission Details

This is an individual assignment. You may not work in groups. Your completed assignment is due on Mon 4/6, by 5pm. We will be discussing submissions in class, so be sure to avoid a late submission.

You must submit your assignment using Canvas. Please upload a single zip file named using the pattern "uwnetid_a1.zip" (replacing "uwnetid" with your UW network login - this is the same as your @uw email address, not a numeric id number). The zip archive should contain two files: a plain text file named "readme.txt" and a PNG or JPG image file of your visualization design. Please use the correct file extension for your image (either .png or .jpg) and be sure your image is sized for a reasonable viewing experience. Viewers should not have to zoom or scroll in order to effectively view your submission! The readme.txt file should contain your write-up, as described above. Please be sure to include your name and UW net id in your readme.

If you are on the waiting list for the class do not have access to the Canvas site, please email your submission to us (or request Canvas access) at cse512@cs.washington.edu.