Documenting Data Quality: Considerations

By Data Management

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

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)
- See Process page for process step examples