Datasheet for a dataset
A document, proposed in AI research (Gebru et al., 2018 onward), that ships with a dataset stating how it was collected, what it represents, its known gaps and biases, and its intended uses. Where a dataset you use came with a datasheet, it populates your provenance entry; its absence is itself a provenance gap.
Defined in 2 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in AI Governance: Applied Mastery.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A document, proposed in AI research (Gebru et al., 2018 onward), that ships with a dataset stating how it was collected, what it represents, its known gaps and biases, and its intended uses. Where a dataset you use came with a datasheet, it populates your provenance entry; its absence is itself a provenance gap.
A standardized document that travels with a dataset describing its motivation, composition, collection process, and recommended uses, providing the semantic and provenance context a structural schema alone cannot capture; covered in full in Module 4. (see Topic 4.8)
A structured documentation practice, proposed by Gebru et al. in 2018, describing a dataset's motivation, composition, collection process, labeling methodology, and recommended and discouraged uses, modeled on electronics industry component datasheets.
A structured document describing a dataset's origin, collection process, composition, and intended and inappropriate uses. Proposed by Gebru and colleagues (2018; Communications of the ACM, 2021). The data-side counterpart to a model card; your data provenance file is your datasheet. (see Topic 2.6)
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Training data governance: what may teach a model, decided before the model exists · Feeding the Machines, AI Data Governance: The Data Chair
- Data contracts: producer and consumer agree in writing, and builds break when they lie · The Catalog That Lives, AI Data Governance: The Data Chair
- The provenance file: your data map an auditor could follow · Data Reality, AI Governance: Applied Mastery
- Model cards and system cards for your own systems, written so an outsider could act on them · Evidence Engineering, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.