The whole semester; one week at a time

Week 12 · 29 Nov


  • Prepare for next week’s pivot from design to implementation (we will be joined by guest critic Hilla Katki) at which point you’ll have finalized your conceptual direction and collected production-ready data.
  • Develop a prototype that fully specs out your final project’s UI and the visualization(s) within.
  • Create a p5 sketch that operates on your finalized (retrieved, cleaned, etc) dataset and demonstrates its contents and formatting.

Week 11 · 15 Nov


  • Develop three conceptually different visual/UI approaches for your chosen final project topic. Additionally, develop a proof-of-concept script that exercises your data source.
  • Presentations by Patrick & Joe
  • Reading #7: The Anti-Sublime Ideal in New Media
    • Post your response with the tag ‘R7 before the start of class

Week 9 · 1 Nov


  • Come up with ten potential directions for your final project and find candidate datasets for five of them. Bring the results of your research (i.e., your list of ideas and rough sketches) to class.
  • Incorporate feedback and continue refining your work on Exercise #4
  • Presentations by Rik & Doug
  • Reading #6: the introduction to Software Takes Command
    • Post your response with the tag ‘R6 before the start of class

Week 3 · 13 September

Next week

  • Try to attend Johanna Drucker’s lecture if you can make it (and better still, show up with a question tucked in your pocket).

Assignment (due 27 Sept)

  • Presentations by Aucher & Michael
  • Reading #3: the final chapters of Graphesis: “Interface and Interpretation” & “Designing Graphic Interpretation”
    • Post your response with the tag ‘R3 before the start of class

Week 2 · 6 September


  • Reading #2: the second chapter of Graphesis: “Interpreting Visualization”
    • Post your response with the tag ‘R2 before the start of class
  • Complete Exercise 1
    • push to github by 6pm

Week 1 · August 30

  • Assessment of student skills, levels, and interests
    • What do you want to learn in this class?
    • What sorts of data/information graphics work have you done previously?
    • Any coding experience?
    • Stats?
  • Introduction to course goals and expectations
  • Intro talk
  • Select Presentation topics
  • Exercise: Catalog & Classify
    • Create and publish a new post with your visualization type as its title. Assign it the tag “Catalog” in the gear menu.
    • Describe your chosen visualization type in terms of the kinds of values it represents (e.g., fractions, integers, percentages, etc.) and the sorts of comparisons it enables or discourages.
    • Explain what forms of ‘pre-processing’ need to occur between the raw data and the ink/pixels in the resultant chart.
    • Explain the ‘mapping’ by which numerical/categorical/etc values are converted into positions, sizes, colors, textures, etc.
    • Include 3 images apiece to demonstrate ‘good’ and ‘bad’ uses of this visualization type.
    • Consult the Markdown Guide to help you format your text & images.


  • Refine your Catalog entry based on the class discussion and see if you can find additional examples (with an emphasis on the ‘good’ uses of the form).
  • Read the first chapter of Graphesis. For every reading assignment, you will be expected to post a short (250–500 word) write-up summarizing what you took to be the ‘message’ of the piece, what you agreed or disagreed with, and what you’d be curious to hear your peers’ opinions about.
    • for this week's reading, you have an additional responsibility: pick one of the works cited in the chapter to investigate and collect some imagery and/or context. Include this in your write-up.
    • Be sure to add the tag "R1" to your post by clicking on the gear icon at the top of the screen.
  • Next week we'll have an in-class programming workshop. In preparation for that, please make sure you've got the following installed/set-up: