Croissant (metadata format)
metadata format for datasets in machine learning
Croissant is a metadata format design to support sharing of datasets for machine learning applications. It is a platform-agnostic schema used to standardize metadata in data repositories like Hugging Face, kaggle, Dataverse and OpenML.
Structure
Croissant builds upon schema.org, uses primarily JSON-LD, and divides metadata in four "layers": Dataset Metadata, Resource, Structure and Semantic:
The Dataset Metadata layer constrains which schema.org properties should be used, including additional properties, linking together the resources (files) of the dataset with general metadata, like licensing and citation information.
The Resource layer describes the individual files and sets of those using two new classes, FileObject and FileSet. A FileSet may be a collection of related images.
The Structure layer specifies how the files are organized in the dataset. A RecordSet class describes how resources are present, configurations that may very a lot between modality. This specification facilitates interoperability of the datasets.
Finally, the Semantic layer adds information for practical reuse of the dataset, such as splits for train, test and validation subsets.
It also provides a default extension for metadata related to responsible AI.
The use of a standard machine-readable structure increases, for example, the discoverability of datasets in search engines such as Google Dataset Search.
History
Croissant was shared in arXiv in March 2024 and published in the proceedings of NeurIPS 2024.
This brief starts where responsible research should: with the source description of “Croissant (metadata format)” as metadata format for datasets in machine learning. Everything that follows is an evidence route, not borrowed authority.
Why this record matters
The subject matters to the general reference register because the source frames it as metadata format for datasets in machine learning. Its deeper value depends on whether names, dates, institutions and citations support that framing.
Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Jun 3, 2026. The linked authority identifier is Q136659610. None of the 0 selected statements returned an explicit reference. The first chronological checks are 2024.
A concise general-reference account can conceal disagreements about scope, terminology or the weight assigned to individual sources. The source lead contains qualifying language; that uncertainty should survive quotation, summary and reuse. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.
How to read it
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Three-step research path
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- Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.
Questions for further research
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This entry incorporates text from “Croissant (metadata format)” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.