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Www.csiro.au Observations, Features, Coverages, SOS Simon Cox CSIRO Exploration and Mining 9 September 2006.

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Presentation on theme: "Www.csiro.au Observations, Features, Coverages, SOS Simon Cox CSIRO Exploration and Mining 9 September 2006."— Presentation transcript:

1 www.csiro.au Observations, Features, Coverages, SOS Simon Cox CSIRO Exploration and Mining 9 September 2006

2 2 of 27 Observations, Features and Coverages ISO/OGC Feature Model Features have properties A feature-type is characterized by a specific set of properties

3 3 of 27 Observations, Features and Coverages ISO 19101, 19109 General Feature Model Properties include  attributes  associations between objects  value of a property may be a complex object  operations Metaclass diagram

4 4 of 27 Observations, Features and Coverages Conceptual object model: features Digital objects correspond with identifiable, typed, objects in the real world  mountain, road, specimen, event, tract, catchment, wetland, farm, bore, reach, property, license-area, station Feature-type is characterised by a specific set of properties Specimen  ID (name)  description  mass  processing details  sampling location  sampling time  related observation  material ……

5 5 of 27 Observations, Features and Coverages Assignment of property values Each property value is either i.asserted  name, owner, price, boundary (cadastral feature types) ii.estimated  colour, mass, shape (natural feature types)  i.e. error in the value is of interest

6 6 of 27 Observations, Features and Coverages Observations and Features An estimated value is determined through observation i.e. by application of an observation procedure

7 7 of 27 Observations, Features and Coverages Observation model – Value-capture-centric view An Observation is an Event whose result is an estimate of the value of some Property of the Feature-of-interest, obtained using a specified Procedure

8 8 of 27 Observations, Features and Coverages Feature of interest may be any feature type from any domain-model … observations provide values for properties whose values are not asserted i.e. the application-domain supplies the feature types

9 9 of 27 Observations, Features and Coverages Some feature types only exist to support observations

10 10 of 27 Observations, Features and Coverages Observation model Generic Observation has dynamically typed result

11 11 of 27 Observations, Features and Coverages Observation specializations Override result type

12 12 of 27 Observations, Features and Coverages More on property values Each property value is either  constant on the feature instance  e.g. name, identifier  non-constant  colour of a Scene or Swath varies with position  shape of a Glacier varies with time  temperature at a Station varies with time  rock density varies along a Borehole Variable values may be described as a Coverage over some axis of the feature

13 13 of 27 Observations, Features and Coverages Observations and coverages If the property value is not constant across the feature-of- interest  varies by location, in time the corresponding observation result is a coverage individual samples must be tied to the location within the domain, so result is set of e.g.  time-value  position-value  (stationID-value ?) Time-series observations are a particularly common use-case

14 14 of 27 Observations, Features and Coverages Discrete coverage model

15 15 of 27 Observations, Features and Coverages Observation specializations Override result type Primary use-case for “CommonObservation” matches “CoverageObservation”  N.B. CommonObservation is an implementation

16 16 of 27 Observations, Features and Coverages Observations support property assignment These must match if the observation is coherent with the feature property N.B. Each “Phenomenon” definition reifies a (Feature) property definition

17 17 of 27 Observations, Features and Coverages Invariant property values: cross-sections through collections SpecimenAu (ppm) Cu-a (%)Cu-b (%)As (ppm)Sb (ppm) ABC-1231.233.454.230.50.34 A Row gives properties of one feature A Column = variation of a single property across a domain (i.e. set of features) A Cell describes the value of a single property on a feature, often obtained by observation or measurement

18 18 of 27 Observations, Features and Coverages Features, Coverages & Observations (1) Observations and Features  An observation provides an estimate of a property value for the feature-of-interest Features and Coverages (1)  The values of the same property from a set of features constitutes a discrete coverage over a domain defined by the set of features Observations and Coverages (1)  A set of observations of the same property on different features provides an estimate of the range-values of a discrete coverage whose domain is defined by the set of features-of-interest  feature-of-interest is lots of little features – property value constant on each one

19 19 of 27 Observations, Features and Coverages Variable property values Some property values are not constant  colour of a Scene or Swath varies with position  shape of a Glacier varies with time  temperature at a Station varies with time  rock density varies along a Borehole

20 20 of 27 Observations, Features and Coverages Features, Coverages & Observations (2) Observations and Features  An observation provides an estimate of a property value for the feature-of-interest Features and Coverages (2)  The value of a property that varies on a feature defines a coverage whose domain is the feature  if this is sampled at discrete times/positions on the feature, the property value may be described as a discrete coverage Observations and Coverages (2)  An observation of a property sampled at different times/positions on a feature-of-interest estimates a discrete coverage whose domain is the Observation feature-of-interest  feature-of-interest is one big feature – property value varies within it

21 21 of 27 Observations, Features and Coverages Observations support property assignment

22 22 of 27 Observations, Features and Coverages premises: O&M is the high-level information model SOS is the primary information-access interface SOS can serve: an Observation (Feature)  getObservation == “getFeature” (WFS/Obs) operation a feature of interest (Feature)  getFeatureOfInterest == getFeature (WFS) operation or Observation/result (often a time-series == discrete Coverage)  getResult == “getCoverage” (WCS) operation or Sensor == Observation/procedure (SensorML document)  describeSensor == “getFeature” (WFS) or “getRecord” (CSW) operation Sensor service optional – probably required for dynamic sensor use-cases

23 23 of 27 Observations, Features and Coverages SOS vs WFS, WCS, CS/W? WFS/ Obs getFeature, type=Observation WCS getCoverage getCoverage (result) Sensor Registry getRecord SOS getObservation getResult describeSensor getFeatureOfInterest WFS getFeature SOS interface is effectively a composition of (specialised) WFS+WCS+CS/W operations e.g. SOS::getResult == “convenience” interface for WCS

24 www.csiro.au Thank You CSIRO Exploration and Mining NameSimon Cox TitleResearch Scientist Phone+61 8 6436 8639 EmailSimon.Cox@csiro.au Webwww.seegrid.csiro.au Contact CSIRO Phone1300 363 400 +61 3 9545 2176 Emailenquiries@csiro.au Webwww.csiro.au


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