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Documenting Data Quality: Considerations

Describing your data, like managing quality, is a cross-cutting element of the USGS Science Data Lifecycle.

<< Back to Manage Quality

Things to consider when documenting data quality:

  • Record the results of periodic data quality assessments
  • Staff skill requirements and training records
  • Citations for methods and standard processes used
  • Data validation procedures
  • Data screening methods
  • Data flags and quality-indicators
  • Document the 'uncertainty' of your data values - this is especially important for derived and model-based data
  • Use the data quality information section within the metadata record for the data FGDC Standard - Data Quality Information)