OpenRefine for the Humanities

This lesson introduces OpenRefine as a tool for exploring, cleaning, transforming, and enriching tabular data commonly used in humanities and cultural heritage research. Using a subset of the Metropolitan Museum of Art Open Access dataset, learners gain hands-on experience with importing data, identifying and correcting data quality issues, creating facets and filters, using GREL expressions, transforming and restructuring data, clustering similar values, reconciling records with external authority sources, and exporting reproducible data-cleaning workflows.

Designed for beginners with little or no prior technical experience, the lesson follows a practical, example-driven approach that emphasizes exploratory data analysis, transparent data cleaning, and reproducible research practices. It is specifically aimed at scholars in the humanities and cultural studies as well as professionals working in Galleries, Libraries, Archives, and Museums (GLAM).

A rendered version of the lesson can be found here.