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Mark data with quality control flags

Best Practice: 

As part of any review or quality assurance of data, potential problems can be categorized systematically. For example data can be labeled as 0 for unexamined, -1 for potential problems and 1 for "good data." Some research communities have developed standard protocols; check with others in your discipline to determine if standards for data flagging already exist.

The marine community has many examples of quality control flags that can be found on the web. There does not yet seem to be standards across the marine or terrestrial communities.

Description Rationale: 

Data quality should be able to be assessed by potential data users so that any problems are identified early in a project.


Some marine examples - Several standards and cross walk between standards at
solar radiation data http://solardat.uoregon.edu/QualityControlFlags.html

Eric Lind
Robert Stevenson