Week 7 (2/4 March)

2 March (synchronous Zoom session)

General discussion of "Cartography"

Working with RStudio as a mapping environment

Explore: RStudio I : R Markdown Notebooks 1

Thought questions: what can the above geovisualization of the dataset help us understand about the audience of "Cartography"? What are the limits of using data visualization for understanding diversity? How does it include the audience in the performance?

Homework:

Read: Where do NYUAD Faculty Obtain their Degrees? (Parwani et al)

5 Ways Data Visualizations Lie (Fortney)

Re-read: What is Data Visualization and why is it important?

Blog 3 (due 9 March)

In this blog writing, you will be thinking about data visualization and cultural performance together and will be assessing to what extent the former can speak to the latter.

Using notebook #4 you will create point-to-point visualizations of a dataset that bear a resemblance to the visualization of airline networks. The production team of Cartography has provided us with datasets created by the audiences during three cities where the performances of the work took place: Abu Dhabi, Philadelphia and Cleveland. These cities have 5, 3 and 1 datatsets, respectively.

I have prepared those datasets for you in the class drive folder Data > Archive Cartography CSV. In preparing these files, I removed the first row, since it was the sample given by the actors (but there might be other repeated ones). I have also broken down individual trajectories (sometimes, 2 or 3 or 4 stops) into a series of single trips, giving them each a unique ID. I made sure that all places were geocoded. I have also prepared an aggregate of the NYUAD performances. These are all shared with the web as CSVs, meaning that you can grab the URL from the Sheet and plug it into the code.

I would like for you (1) to visualize at least two of the datasets (2) one network visualization and (3) to discuss and interpret what these visualizations can help us understand about the audience self-reported movement. There are many combinations of datasets you might use: two different performances in Abu Dhabi, the composite of Abu Dhabi vs Philadelphia, Cleveland vs Abu Dhabi, etc.

Individual stories are definitely eclipsed by their transformation into data points, but is there a story you can tell based on the data provided here?

Here are some potential guiding questions (you do not need to answer all of them):

• Why do you think the production chose to incorporate audience data into the performance?

• With your two visualizations, discuss the differences in audience trends. Include detail shots to places on the visual that you pay particular attention to in your writing. What can you tell about larger patterns in migration stories in the audience-specific data? Are they consistent? specific?

• What are the limits of using data visualization for understanding diversity?

• What might you do to such a map that tell more about the individual data points? How would you collect that data ethically?

• How do the numbers of attendees potentially affect the visualization? How does the way I prepared the dataset affect the visualization and your interpretation of it?

• Are the silences in the map data?

• Does the performance of Cartography "bind information to location?" If so, how? Can you relate it to other themes in the course?

• If you could change the visualization to show some other aspect of the data, what would it be?

• After viewing the maps and networks, what questions do you have for the Cartography team about the performances?

Your posting should be (750-1000 words) long and include at least 2 maps and 1 network. You may also include close ups or annotated images to draw attention to patterns you see.

Feel free to cite any point of the performance or the press articles about "Cartography" in your posting. The creators of Cartography will be reading your writing and meeting with us after the break!

4 March (synchronous lab)

Explore: RStudio II : R Markdown Notebooks 2 and data from performances of Cartography.

Working with the data from "Cartography".

Make sure you have signed up for small group discussions here.

Work on your blog. No quick writing this week.