Mike Botts – January 2008 1

Supporting QA/QC inSensor Web Enablement (SWE)

and SensorML

February 2008

Mike Botts

mike.botts@uah.edu

Principal Research Scientist

University of Alabama in Huntsville

Mike Botts – January 2008 2

Why is SensorML Important?

• Importance:

– Discovery of sensors and processes / plug-n-play sensors – SensorML is

the means by which sensors and processes make themselves and their

capabilities known; describes inputs, outputs and taskable parameters

– Observation lineage – SensorML provides history of measurement and

processing of observations; supports quality knowledge of observations

– On-demand processing – SensorML supports on-demand derivation of

higher-level information (e.g. geolocation or products) without a priori

knowledge of the sensor system

– Intelligent, autonomous sensor network – SensorML enables the

development of taskable, adaptable sensor networks, and enables higher-level

problem solving anticipated from the Semantic Web

Helping the World to CommunicateGeographically

Where can QA/QC be supported?Where can QA/QC be supported?

• Sensor Descriptions (SensorML-SWE Common)

– Discovery

• Capabilities

– Detector Parameters

• Error curves, latency

• Accuracy of parameters and output values

• Observations (O&M-Swe Common)

– QA/QC expressions for the values

• e.g. accuracy, confidence levels, etc

• either constants or themselves as output values

– Lineage of the Observation (procedure property)

• SensorML System and ProcessChains

Mike Botts – January 2008 4

SensorML Descriptions for Discoverybased on QA/QC capabilities and characteristics

Mike Botts – January 2008 5

QA/QC metadata suitable for discoveryof sensors and processes

Find all remote sensor systems measuring in the visible spectral range with

ground resolution less than 20m.

Key is to define terms for QA/QC characteristics

Mike Botts – January 2008 6

QA/QC in Detectors, Actuators, and Sensor Systems

• Detector and Actuator parameters support some QA/QC

– Sensitivity, latency, error curves, etc

– Need to make certain that any additional QA/QC parameters are

supported in models

• Any SWE Common values can have QA/QC properties

– Accuracy, Confidence, etc.

– Useful for defining quality and confidence of

• Outputs of sensors

• Observation values in O&M

– quality values can be constant or defined as output of sensors and

processes

Mike Botts – January 2008 7

SensorML Supports description of Lineage for an Observation

Observation

SensorML

Within an Observation, SensorML can describe how that Observation

came to be using the “procedure” property

Key is to make sure each process component provides necessary QA/QC

measurement

Mike Botts – January 2008 8

On-demand processing of sensor data

Observation

SensorML processes can be executed on-demand to generate Observations

from low-level sensor data (without a priori knowledge of sensor system)

SensorML

Need to understand how to support error propagation within each Process

and to enable combining these errors into composite indicators