Variable Value Timestamps and Quality

Device variables are data tables which can have both timestamps and quality codes attached to them. The origin of timestamps and quality codes can vary depending on the source of the data:

  • Physical Devices: Many physical devices, particularly those adhering to the OPC DA and UA standards, are capable of assigning quality codes and timestamps to the data as the data is generated. This is the primary source Iotellect uses when attaching timestamps and quality to a variable value.

  • Device Drivers: In cases where devices do not provide timestamp or quality information, the Iotellect device driver connected with the physical device will assign appropriate quality codes and timestamps based on communication status and the time data was received.

  • Iotellect Core: The core of Iotellect may also assign quality codes and timestamps in cases where the device driver did not provide a timestamp or quality code. For example, if a device is offline or a driver encounters an exception during communication, the core system will save the data with an appropriate quality code and timestamp.

Accessing Timestamps and Quality Codes

Iotellect's expression language provides access to timestamps and quality information through both standard references and data table processing functions.

Example retrieval using Iotellect’s expression language:

// To get the quality code via standard reference:
{users.admin.devices.exampleDevice:exampleVariable#quality}

// To get the quality code via function:
getQuality({users.admin.devices.exampleDevice:exampleVariable})

// To get timestamp via standard reference:
{users.admin.devices.exampleDevice:exampleVariable#timestamp}

// To get timestamp via function:
getTimestamp({users.admin.devices.exampleDevice:exampleVariable})

These expression examples extract metadata tied to exampleVariable, allowing further processing based on time-bound logic or integrity checks.

Applications of Timestamps and Quality Codes

Timestamps and quality values offer several benefits:

  • Data Validation and Filtering: By evaluating the quality codes, unreliable or invalid data points can be identified for further processing or filtered out.

  • Alerting and Anomaly Detection: Changes in quality codes can serve as triggers for alerts or notifications, activating responses to potential issues with data sources or communication channels.

  • Data Visualization: Visualizations can incorporate quality codes and timestamps to provide a more comprehensive representation of data trends and potential uncertainties. See Building Chart Datasets to get started.

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