Document a data dictionary before importing
Define fields, units, missing values and validation rules so an import remains understandable and verifiable.
Read the practical method →GOV.UK · Data Quality Framework
Practical framework for defining, measuring, communicating and improving data quality for a specific use.
Resource identity and purpose checked against the source on . This check does not verify all service conditions or individual data records.
Use this resource for a specific task.
Data and artificial intelligence · United Kingdom · international
Open the original resourceWhen it helps
Choose quality dimensions that affect your decision and document defects at their source.
How to start
Identify the data a decision actually depends on. For each defect, specify business impact, the expected rule, an owner and a repeatable measure before starting a cleanup.
Limits to keep in mind
The framework comes from the UK government. Quality methods do not establish the accuracy of every observation.
Check before using
Three points to record with the decision.
- 01
Purpose the data must fit.
- 02
Quality rule and reproducible measure.
- 03
Unresolved defects and owner.
A method and complementary resources.
Source and verification
GOV.UK · Data Quality Framework — primary source. Link checked . The checklist is editorial guidance; link availability does not guarantee completeness or suitability.
Read the editorial method · Report a correction with its source