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Automated Data Quality Control (QC)

Clarity runs many checks to keep your data trustworthy. One of them is Automated Quality Control (QC), which runs before any data is served or displayed. This article explains how QC flags work and how to use the resulting assessment to filter out bad measurements.


QC flags

QC flags highlight measurements that may not be trustworthy. Clarity maintains a library of flags built from its understanding of air pollution, sensing principles, and known sensor failure modes. A flag is applied automatically to a measured value whenever a specific condition is met, so you can manage flagged values and keep only valid data in your analysis and public sharing.

Each flag in the library is described by these fields:

FieldDescription
IDThe unique identifier of the flag.
NameA short description of the flag.
SeverityHow the measurement should be regarded. Right now there's one level, Invalid. More may be added in future (for example, Suspect).
Applied ifThe rule the metric value is checked against.
Life Cycle StageWhether the flag is Live or Deprecated. If a rule changes or improves, the original flag is deprecated and a new flag — possibly with the same name — is made live.
Date Made LiveWhen the flag was first introduced.
Date DeprecatedWhen the flag was deprecated.
Applies toThe metrics the flag is applied to when its "Applied if" rule is satisfied.

How flags become a QC Assessment

Every measured value is assumed Valid unless Clarity's automated system flags it. A single value can carry several flags (for example, QC.I.OOB.001 and QC.I.OOB.002), and those flags can have different severities.

To reconcile them, each value gets one overall QC Assessment, set by the most severe flag applied to it (for example, Valid or Invalid).

For aggregated values like hourly or daily averages, the system applies every flag present during the aggregation period, then sets the aggregated value's QC Assessment from the most severe of those flags.


Using the QC Assessment

The QC Assessment tells you how to handle a measurement for different purposes. Here's Clarity's recommended handling, and how the Dashboard itself treats each assessment:

QC AssessmentAnalysis & reportingDashboard & internal visualizationOpenMap, open API & public access
Valid✅ Include✅ Include✅ Include
Invalid❌ Do not include✅ Include (visually marked, with the option to remove it)❌ Do not include

What's next


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