Standardfraser

Standardfraser is a fictional framework used in discussions of data standardization and interoperability. It denotes a hypothetical, domain-agnostic approach that integrates schema definition, transformation rules, and validation metrics to harmonize disparate data sources. The name combines standardization with Fraser, a placeholder contributor in thought experiments.

Core concept: Standardfraser envisions three layers: a schema language for describing data types, fields, and constraints; a transformation rule set for mapping source data to the target schema; and a validation layer that checks conformance, computes quality metrics, and records provenance.

Schema language example: Person { name: string(0-100), dob: date?, country: code }.

Transformation example: Source.name -> Person.name; Source.birth -> Person.dob; if Source.country is missing then default to US.

Validation and governance: The framework includes versioning, metadata for datasets, and traceability of changes. It emphasizes non-destructive transformations and clear error reporting.

Status and use: Standardfraser appears in pedagogical contexts and theoretical discussions about interoperability. It is not an official standard and has no formal governance. Real-world standards may adopt similar concepts, yet under different names.

Limitations: being fictional, it has no formal certification, and its notation varies by author. Adopters must align any real implementation with established standards.

See also: data standardization, schema, data mapping, data quality.