Week 6: Data & Mapping Data

Data & Mapping Data

(Dear Data by Giorgia Lupi and Stefanie Posavec)

The password for these Figma files is pratt.

Debrief & Discussion

In a group of 2, discuss the following questions:

What did you discover by translating your source material into a system of rules, relationships, and behaviors?
Where did the process become difficult, surprising, or different from what you initially imagined?
How did loops, functions, repetition, variation, randomness, or other forms of logic shape what your system could do?
Did working with code lead you toward visual possibilities you might not have designed manually?
What feels unresolved or still full of potential in your system? If you continued developing it, where might you take it next?

Assignment

Due: Oct 6, 2026

Submit Assignment

This week, you will research data and look for a dataset that resonates with you. It could be related to your interests, a social issue, or something you find intriguing. Once you have your dataset, you can try creating a very simple mapping visualization using p5.js.

What structure does the data have? How can you map it to visual elements like position, size, color, or shape?
Use loops and object structures to efficiently handle and visualize the data.
Any specific challenges or insights did you encounter while working with the data?
Other observations or reflections about the data and your visualization process.
Can map help you translate data values into visual properties?
This is the beginning of our project 2: data sculpture. We will continue to refine and develop this project over the next few weeks.

Databases

NYC Open Data Thousands of datasets about everyday life in New York City.
Data Is Plural - A curated collection of unusual and interesting datasets.
CORGIS: The Collection of Really Great, Interesting, Situated Datasets - Small, approachable datasets on topics including coffee, Broadway, books, airlines, food, music, cars, and many others.
TidyTuesday - A weekly archive of real-world datasets collected for people to explore, visualize, and experiment with.
Google Dataset Search - Useful when you already have a topic in mind. Try searching for things like “sleep dataset,” “video game sales,” “NYC noise,” or anything else you are curious about.
Our World in Data - Accessible global data on topics such as population, technology, health, environment, work, inequality, food, and culture.
Kaggle Datasets - A very large collection of community-uploaded datasets covering almost every imaginable topic.
Data Commons - Useful for comparing statistical information about places, populations, economies, education, health, and other social indicators.
Data.gov - The U.S. government’s large open-data catalog, bringing together datasets from many federal agencies.
World Bank Data Catalog - International datasets related to countries, economies, development, infrastructure, education, labor, environment, and more.
CDC National Center for Health Statistics - Public datasets and surveys related to health, demographics, mortality, healthcare, and everyday behaviors in the United States.
UCI Machine Learning Repository - A long-running collection of relatively clean datasets.
Rdatasets - A searchable archive of datasets distributed with R packages. Useful for finding relatively compact datasets for experimentation.
Awesome Public Datasets - A large topic-organized directory pointing to open datasets from many different sources.

You are also welcome to find a dataset somewhere else entirely. These resources are starting points, not requirements.

Graduate Studio: Technology A [Class Notebook] (DES-720A-02)

Week 6

Data & Mapping Data

Debrief & Discussion

Assignment

Databases

Examples

Tutorials & Resources

Resources