AI Vocabulary · 08 Rules & Responsibility
What is Data Card?
A short, structured document that says where a dataset comes from, what is in it and what it should be used for.
A data card documents a dataset the way a model card documents a model. It records the sources, how the data was collected and labelled, what it contains, what it was tested for and which uses it suits. Google introduced Data Cards in 2022 after building more than 20 of them for real datasets.
The idea goes back to Datasheets for Datasets, proposed by Timnit Gebru and co-authors in 2018. Borrowing from electronics, where every component ships with a datasheet, they suggested questions on motivation, composition, collection, preprocessing, uses, distribution and maintenance. Since August 2025 the EU requires providers of general-purpose AI models to publish a summary of their training content on a fixed template.
Why it matters for you
A data card is the cheapest due diligence for data you buy and data you build. It also prepares you for questions from customers, investors and regulators.
Own it
For every dataset you use for fine-tuning, search or testing, write one page: source, rights, date, contents, known gaps and intended use. Ask vendors for the same.
Where it comes from
Data Cards: Purposeful and Transparent Dataset Documentation by Pushkarna, Zaldivar and Kjartansson (Google, 2022), building on Datasheets for Datasets by Gebru and co-authors.
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