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| Version | User | Scope of changes |
|---|---|---|
| Oct 7 2009, 3:50 PM EDT (current) | vikrantsharma1 | 192 words added |
| Oct 7 2009, 3:49 PM EDT | vikrantsharma1 |
Changes
Key: Additions Deletions
To optimize quality assurance, AirVision opens up the process between data collection and final reporting through an open modular approach. Open Data Processors can be scheduled and triggered by the Task Manager to automate quality assurance while also controlling the points of data access and display, such as AIRNow and web presentation.
The Automatic Data Validation Processor Module.(ADVP) assigns a quality grade (1-10) for each data point based initially on instrument/data logger flags, but allows you to generate rules that affect the quality code. The ADVP can be triggered to run automatically after data collection to grade each data point, and the quality grade can be used to prevent suspect or bad data from being published to the web or shared with other organizations.
The grades can also be used to focus quality assurance efforts on the most suspect data points Data can be compared against other parameters at the same site, different sites (spatial testing), or historical composite values for that particular parameter and/or site (e.g., comparing this hour’s value compare to the same hour and day of the week over the previous five years). ADVP functions also include persistency checks.
The Automatic Data Validation Processor Module.(ADVP) assigns a quality grade (1-10) for each data point based initially on instrument/data logger flags, but allows you to generate rules that affect the quality code. The ADVP can be triggered to run automatically after data collection to grade each data point, and the quality grade can be used to prevent suspect or bad data from being published to the web or shared with other organizations.
The grades can also be used to focus quality assurance efforts on the most suspect data points Data can be compared against other parameters at the same site, different sites (spatial testing), or historical composite values for that particular parameter and/or site (e.g., comparing this hour’s value compare to the same hour and day of the week over the previous five years). ADVP functions also include persistency checks.
