Define the decision and method requirements before assessing a dataset. Check representativeness for the actual product, process, geography and time.
,Review source quality, measurement/estimate basis, missing stages, uncertainty and conflicting records. A complete dataset can still be unsuitable for the intended comparison.
,Record which uses are supported and what information would improve readiness. Avoid turning an information-quality rating into a green score.
The data-quality assessment draft will organise your answers, including your project, record or worksheet reference and responsible recorder and record date. It will identify missing entries; completion does not independently verify the stated claim or outcome.
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