working with more complex datasets, multiple dimensions, and more interactivity.
Choose your data source from NYC Open Data. Some examples include:
Decide what dimensions you’re interested in and represent them any way you want, i.e., find your own “story in the data.” Ensure you have at least four data components, per our discussion in lecture. Produce three flat sketches of different layers or related dimensions found in your chosen dataset. Build one of your representations in code.
As a first step, you'll want to take a deep dive into the data. How is it structured and what structure do you need to create your visualization? This might be a bit of a messy process, as the data is likely not structured exactly as you need it. Do you need to extract or calculate additional data to better tell your story?
In parallel, work on visual iterations. Consider Bertin's visual variables, as well as information hierarchy and states of your code sketch.
Post your three flat sketches and one code sketch to your homepage. Also, bring print out copies of your three flat sketches to class for pin-up crits.