Decide what to map: identify a data set that you’d like to map. Add a post to Tumblr by Friday night that includes the following:

• A description of the data
• The source of the data, with a link.
• Is this data points, shapes, or lines?
• What geographic information do you need to map this?
• What do you need to do to combine data with geographic information?

Example:

The Bureau of Labor Statistics publishes annual data on workplace fatalities, by state. I’d like to create a map that shows the fatality rate per working adult, using state by state employment data available from the St Louis Fed. This will be a map of shapes (the outline of each state) so I’ll need to merge a US State shapefile with the fatality rate data.

Or:

The NYC Department of education recently released data on high school sports budgets. I’d like to create a map that shows where schools have substantial budgets. This will be a map of points (the location of each school). The DOE publishes a separate data set that includes lat/lon for each school so I’ll need to merge that data with the sports budgets data using “School Name” as the common field.

Tag that post “map assignment”

Make another map: Once you’ve written up your Tumblr post, take a stab at actually making the map.

Your map is due Tuesday at 3PM. Use the “Share” link to get a URL for your map and add it to the class assignments document.

Storyboard

With your partner, add a storyboard.md document to your existing pitch gist. Use that to start a very rough draft of your community profile. I haven’t given you a lot of examples, but one way to think about this might be, What would the wikipedia article about this community look like? Take a look at the Wikipedia entry on Bushwick for instance. It goes on far (far) longer than you need to, but the tone is about right. There’s a lot of baggage in choosing to lead with “Bushwick is a rapidly gentrifying…neighborhood” – but you know this community, you can decide what to start with.

Start to scope out a draft. Describe the parts you already know and the parts you’re struggling with. Start to put some images in place, or stick some placeholders in.

Your storyboard is due Tuesday at 3PM.

Readings

Steele and Illinsky, Designing Data Visualizations Chapter 4: Choose Appropriate Visual Encodings (in Library);
Cairo: The Functional Art, Reading part 2: pages 118-129, on Cleveland & McGill’s perceptual accuracy

eRes Page: http://cunygsj.docutek.com/eres/coursepage.aspx?cid=166 Course pwd: dataviz15