datasetfocused
Datasetfocused is a term used to describe an approach to data science and machine learning that treats datasets as first-class artifacts and central drivers of development and evaluation. In a datasetfocused paradigm, the quality, documentation, provenance, and governance of data are prioritized alongside models and algorithms.
Core ideas include rigorous dataset versioning, provenance tracking, and standardized metadata; emphasis on data quality and
Practices include maintaining dataset registries or catalogs, applying data version control, using datasheets for datasets and
Advantages of a datasetfocused approach include improved reproducibility, auditability, governance, and accountability; easier collaboration and reuse;
Challenges include data privacy and licensing, scale and governance overhead, and the need for standardized metadata
In practice, organizations adopting dataset-focused workflows begin with rigorous data collection and labeling, maintain clear metadata,
See also: Datasheets for Datasets, Model Cards, data catalogs, and data versioning.