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quality

Data quality and quality control methods should be part of the data information file

Tags: assure, flag, quality

Documentation and metadata associated with a data file should be checked to make sure what is described is actually found in the data file.

Data sets that are to be integrated should be compatible and comparable.

Prepare and document a plan for assuring the quality of your data, so that you and others can trust they are accurate.

Whether compiled or entered from paper records, new digital data should be double-checked for accuracy to avoid input errors.

Quality control is highly dependent on the data collection methodology, but there are some general practices that can be applied

Use statistical and visual methods for determining potentially erroneous data points

In a data file, when actual measurements could not be obtained, estimated values should be identified.

Provide versions of data products with defined identifiers to enable discovery and use

Items to consider when versioning data products:

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