@@ -138,7 +138,6 @@ The following procedures are implemented to ascertain data quality in the databa
Check constraints for numeric values: Wherever possible numeric values are checked on insertion for their plausibility (e.g.areas, discharges, inhabitants) to be within a meaningful range, usually \> 0 and smaller a maximum value. The catchment area of a river must be larger than 0 km² and smaller than 7000000 km² (size of the Amazon river basin). CONSTRAINT check_catchment_area_range CHECK ( catchment_area_km2 \> 0 AND catchment_area_km2 \< 7000000 )
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-<details>
<summary>Example2</summary>
Values are checked based on values in other columns: If a measurement is marked as below an analytical limit, the value of the limit must be given in the corresponding column. If a measurement is marked as below the analytical limit of detection (LOD), the LOD must be given in the corresponding column.CONSTRAINT check_lod_available CHECK ((lod \> 0 AND value_below_lod IS TRUE) OR (value_below_lod IS NOT TRUE))
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@@ -153,7 +152,9 @@ The following procedures are implemented to ascertain data quality in the databa
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<summary>Example</summary>
The Accreditation status of measurements are managed by a boolean column with controlled vocabulary used according to the following schema:
The Accreditation status of measurements are managed by a boolean
column with controlled vocabulary used according to the following
schema:
-**yes, fully**: true
-**no, but the values are of high reliability**: false
