Singledataset

Singledataset is a data collection concept referring to a dataset produced by a single source or single study. It emphasizes uniform provenance and a coherent collection process, as opposed to datasets assembled from multiple origins.

Characteristics include a traceable data lineage, consistent collection instruments and protocols, a stable schema, and documentation of the collection period and context. The scope is usually well-defined, with explicit inclusion criteria and a fixed set of features.

Applications include benchmarking, method validation, and reproducible research where the goal is to study a phenomenon within a specific context. Benefits include clarity of provenance, easier data quality assessment, and straightforward versioning. However, limitations include potential bias from the originating source, limited generalizability, and vulnerability to source-specific errors or biases.

Managing a singledataset involves recording metadata, documenting collection methods, and enforcing licensing and access controls. Data quality checks and lineage tracking help maintain transparency for downstream users. Singledatasets are often contrasted with multi-source or integrated datasets, which merge data from several origins to broaden scope.

See also: data provenance, dataset bias, reproducibility, benchmarking, data quality.