Quality

Some Data Connectors like the OPC-UA support measurement quality. The quality tells about the validity of the measurement value. The possible values are:

• Good: Good quality means that the measurement is trustworthy. If the Data Connector does not support quality, all measurements have good quality on default.

• Uncertain: Uncertain quality means that the measurement is partly untrustworthy. This can occur if a measurement value is outside a valid range, is initializing, is overwritten manually or not updated within a desired time range.

• Bad: Bad quality means that the measurement is untrustworthy, for example if a connection is down.

When aggregating measurements, quality information is included in the aggregation. The general rules regarding quality are:

• Good: All measurement involved in generating the output measurement has good quality and no measurements have null values.

Aggregation window with all good values.

• Uncertain: If either of the measurements involved in calculating the output value is either uncertain or contains null values, the output is set to uncertain. However, no input measurements have bad quality.

Aggregation windows that produce Uncertain quality output.

• Bad: One or more of the measurements involved in calculating the output value is bad, resulting in a bad output value as well. If all input values are null, the output is bad as well.

Aggregation windows that produce Bad quality output.

If no data exists in a given calculation interval, or if all input values are null, an aggregated value cannot be calculated. The output measurement is set to null with bad quality.