About

All Data Are Local: Introduction to Data Literacy

This two-day block course is part of PLAY 1 / Data Literacy in Data Design + Art.

Instructor

Dr. sc. Moritz Mähr teaches the course. He is a research associate in digital history at the University of Bern, and he lectures in history at UniDistance.ch. He also works on research analytics at ETH Zurich.

His work joins digital history, science and technology studies, and open research infrastructure. He builds reproducible methods and interoperable infrastructures, and he applies the FAIR and CARE principles to research data. He teaches source criticism for the age of AI, critical AI literacy, and research data management.

This course comes out of that practice. It treats a dataset as a made object with a history, not as a neutral record.

Write to with questions about the content. ORCID: 0000-0002-1367-1618.

Format

The course gives 12 hours of contact time, as two days of six sessions of 60 minutes. Day 1 runs on 5 October 2026 and Day 2 on 12 October 2026.

The main text is Yanni Alexander Loukissas, All Data Are Local (2019). The statistics resource is Introduction to Modern Statistics (2e) (2024).

Teaching approach

The course uses a flipped structure.

In class: critical data literacy, close reading, discussion, application, and feedback.

Between the two days: basic statistics and standard data displays through self-study.

The course treats data as material for knowledge and design. It asks students to look behind a table or chart and study the conditions that produced it.

Scope

This is not a complete statistics, programming, database, or data-law course. It provides a foundation for later work in data analysis, information design, visualization, coding, and data-based art.

The central principle is:

To understand a dataset, we must also understand its setting.

Reuse

The course content is available under CC BY 4.0. You can copy it, change it, and teach it, if you give credit. The reuse guide explains how to adapt the site for your own course.

Cite the course as described in CITATION.cff.

Corrections

Report a broken link, a wrong page number, or an unclear instruction through GitHub Issues.

Back to top