mlsanityData to 7 Oct 2026

Datasheets for Datasets

arXiv 1803.09010 ↗First posted 23 Mar 2018cs.DB cs.AI cs.LGcited by 1,371

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Cited by 51 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every component, no matter how simple or complex, is accompanied with a datasheet that describes its operating characteristics, test results, recommended uses, and other information. By analogy, we propose that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses, and so on. Datasheets for datasets will facilitate better communication between dataset creators and dataset consumers, and encourage the machine learning community to prioritize transparency and accountability.

Key facts. Cited by 1,371 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Mar 2018.

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Citing papers per year: 2020: 1; 2021: 139; 2022: 196; 2023: 227; 2024: 254; 2025: 180; 2026: 374.

1,371 papers.

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