Course Description

All Data Are Local: Introduction to Data Literacy

This course introduces data literacy for Data Design + Art. It starts from a simple idea: data are not given. People make data through observation, selection, classification, measurement, storage, and design.

The main text is Yanni Alexander Loukissas’s All Data Are Local (2019). We use the Introduction and Chapters 1 and 2 on Day 1. We use Chapters 6 and 7 on Day 2. The course asks three questions throughout:

Between the two course days, students study selected sections of Introduction to Modern Statistics (2e) (2024). These sections provide basic statistical language for observations, variables, samples, distributions, and common charts. Day 2 starts with a short multiple-choice quiz on this material.

Students also bring their own dataset. They use it to connect statistical description with critical data practice.

Learning outcomes

After the course, students can:

  • distinguish a dataset from its data setting;
  • explain how observations and categories become data;
  • identify the origin, purpose, limits, and missing context of a dataset;
  • use basic statistical terms to describe a dataset;
  • explain how place, institutions, tools, and interfaces shape data;
  • describe a dataset in a clear, critical, and responsible way.

Next steps

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