mike botts – august 2008 1 supporting qa/qc for ocean observations using sensor web enablement...

Mike Botts – August 2008 1

Supporting QA/QC for Ocean Observations using

Sensor Web Enablement (SWE)and

SensorML

August 2008

Mike Botts (UAH), Tony Cook (UAH), Janet Fredericks (WHOI), Julie Bosch (NCDDC)


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

– QC Process Description

• Defined as SensorML Process

• Included as part of lineage of Observation (see below)

• 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


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


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 sensor profiles for Oceans Community

• 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


What does an SOS provide?

Buoy Data at TAMU

• getCapabilities:

– http://sos-ws.tamu.edu/tethys/madis?request=GetCapabilities&version=1.0&service=SOS

• getObservation:

– http://sos-ws.tamu.edu/tethys/madis?request=GetObservation&version=1.0&service=SOS&offe

ring=44029&format=text/xml;%20subtype=%22om/1.0%22&observables=http://marinemetadat

a.org/cf%23sea_surface_temperature,http://marinemetadata.org/cf%23air_pressure_at_sea_le

vel,http://marinemetadata.org/cf%23air_temperature&time=2008-08-22T12:00:00Z/2008-08-23

T12:00:00Z

• describeSensor:

– http://vastserver.nsstc.uah.edu/vast/cdip?service=SOS&version=1.0&request=DescribeSensor

&procedure=urn:CDIP:process:CDIP_144


SensorML Supports description of Lineage for an Observation

Observationwith flags

SensorMLWorkhorse

Within an Observation, SensorML can describe how that Observation came to be using the “procedure” property;

Let’s explore the pieces of this graph in the following slides

SensorML:QC Process

SensorML:ADCP System

SOS serving processed wave data


Waves Lineage

• Janet’s Slide


Sensor Description


SensorMLWorkhorse

The lineage can include the description of the sensor itself (click on yellow box to see example);

Notice the Quality measures within capabilities and the listing of events in history

All or part of the output of this sensor system can serve as input to the QC process chain

SensorML:QC Process




QC Test Descriptions


SensorMLWorkhorse

Individual QC tests can make up the components of the QC Process chain (click on yellow boxes to see examples);

These could include, for instance, range test, threshold test, spike test, etc.

Julie Bosch’s list

SensorML:QC Process




QC Process Chain Description


SensorMLWorkhorse

The QC Process can be described as a separate process chain from the sensor itself ;

SensorML:QC Process




The complete ADCP Observation Lineage


SensorMLWorkhorse

The sensor and QC process description makes up the lineage of the Observation;

The output of this process should be reflected in the components of the observation

SensorML:QC Process




The ADCP Observation


SensorMLWorkhorse

The Observation components should reflect the output from the complete processing chain but include the encoding as well (could be ascii, binary, or a particular simple MIME type)

The “procedure” property of the Observation should point to the lineage process.

SensorML:QC Process



procedure


The ADCP SOS


SensorMLWorkhorse

The Observation can then be served from a Sensor Observation Service (SOS)

The capabilities document of the SOS should reflect the data components of the Observation

SensorML:QC Process




Conclusions

• SensorML and SWE can support QA/QC in several ways

– Quality capabilities of sensors

– Quality specifications for individual data components in observations and

sensor output

– SensorML description of individual QC tests and process chain

– Lineage specification of observation

• The use of SWE Common data components throughout SWE

specifications provides many benefits

– Robustness – uom, semantics, constraints, quality specification

– Consistency of property and data component descriptions for encodings and

services

– Reflection of common data components within inputs, outputs, and parameters

of processes and the components of an observation

mike botts – august 2008 1 supporting qa/qc for ocean observations using sensor web enablement...

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