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Www.csiro.au How do you want that data? Spatial information models and web interfaces Simon Cox CSIRO Exploration and Mining 7 September 2005.

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Presentation on theme: "Www.csiro.au How do you want that data? Spatial information models and web interfaces Simon Cox CSIRO Exploration and Mining 7 September 2005."— Presentation transcript:

1 www.csiro.au How do you want that data? Spatial information models and web interfaces Simon Cox CSIRO Exploration and Mining 7 September 2005

2 Datamodels and interfaces Outline Geospatial datamodels OGC interfaces

3 Datamodels and interfaces Fields vs. objects classic geology “Feature” viewpoint classic earth-observations “Coverage” viewpoint

4 Datamodels and interfaces 1.Classic geometry-centric GIS approach One shape per feature … Really an implementation strategy, downplaying the business object Tenement Points, lines and polygons are primary objects  Annotated with a set of attributes, often a row of scalar values  layer name => semantics

5 Datamodels and interfaces 2. Conceptual object model: features Digital objects correspond with identifiable, typed, objects in the real world  mountain, road, specimen, event, tract Feature-type characterised by a specific set of properties  each property is constant on the feature  spatial values are just another property  multiple geometries possible, e.g. scale dependence for single feature Properties include associations between complex objects  i.e. the value of a property may be a complex object  association-role == property

6 Datamodels and interfaces 3. Spatial function: coverage (x 1,y 1 ) (x 2,y 2 ) Variation of a property across the domain of interest  For each element in a spatio-temporal domain, a value from the range can be determined  c.f. features, where each property is constant Discrete or continuous domain  Domain is often a grid  Arc/Info “coverage” == multi-geometry domain, attribute-table for each element

7 Datamodels and interfaces Cross-sections through information 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 locations)

8 Datamodels and interfaces 4. Data capture: the observation model Description of observation event provides data acquisition “metadata”  map from feature to property-estimate  supports quality/confidence assessment, data processing

9 Datamodels and interfaces Cross-sections through information 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 locations) A Cell reflects the result of a single observation

10 Datamodels and interfaces Section view Sometimes they appear together Properties Map view  Survey  Continuous logs  Intervals  Horizons  Point observations Position is 1-D  arc-length from collar  Collar (Point Property)  Shape (Curve Property)  Samples

11 Datamodels and interfaces Several views of the same information SpecimenAu (ppm) Cu-a (%)Cu-b (%)As (ppm)Sb (ppm) ABC-1231.233.454.230.50.34 Result/Observation view Used for:  Quality/confidence assessment  Result calibration  Database insertion and update Feature view Assembled by:  Aggregation of multiple Observation/result having same featureOfInterest Used for:  Object description Coverage view Assembled by:  Aggregation of multiple Observation/result having same observedProperty Used for:  Property variation  Pattern/anomaly/feature detection

12 Datamodels and interfaces OGC Information Service interfaces Web Map Service Catalog Service Web Feature Service Web Coverage Service Sensor Observation Service Web Processing Service

13 Datamodels and interfaces Open Geospatial Consortium - Web Feature Service GML WFS Server Data-source organised for custodian’s requirements Community-specific GML application language  TigerGML, LandGML, O&M, XMML, CGI-GML, ADX, GPML, CSML, MarineXML etc private  public boundary WFS Client HTML

14 Datamodels and interfaces Web Feature Service - operations GetCapabilities DescribeFeatureType  response:  GML schema for feature-type GetFeature  request parameters:  Feature type  Property value  response:  Collection of feature instances of requested type i.e. operation signature matches Feature-property information model

15 Datamodels and interfaces Web Coverage Service - operations GetCapabilities DescribeCoverage  response:  domainSet – spatial and temporal domains  rangeSet – component axis descriptions (though merely text strings …) GetCoverage  request parameters:  domain subset  range subset – selected axes i.e. operation signature matches Coverage/domain-Coverage/range information model

16 Datamodels and interfaces Sensor Observation Service - operations GetCapabilities DescribeFeatureOfInterest DescribeSensor GetFeatureOfInterest GetFeatureOfInterestTime GetObservation GetResult … i.e. operation signature strongly based on Observation information model

17 Datamodels and interfaces Several views of the same information SpecimenAu (ppm) Cu-a (%)Cu-b (%)As (ppm)Sb (ppm) ABC-1231.233.454.230.50.34

18 Datamodels and interfaces Data re-use WFS Client WFS Server multiple views of same data (features) SOS Client SOS Server (observations) WCS Server (coverages) WCS Client

19 Datamodels and interfaces Combining with observation service WFS Client WFS Server WFS/SOS Client/ Server (orchestration) WFS Client (simulation) (mapping) WFS Client (analysis & reporting) SOS Server Sensor BPEL?

20 Datamodels and interfaces Standard transfer format allows multiple data sources WFS Client WFS Server WFS Server B WFS Server C

21 Datamodels and interfaces PIRSA DOIR GA http://cgsrv3.arrc.csiro.au/seegrid/savedapps/filter Three servers, one map Mapping client

22 Datamodels and interfaces Value-adding chain Observation/result  estimate of value of a property for a single specimen/station/location  data-capture, with metadata concerning procedure, operator, etc Coverage  compilation of values of a single property across the domain of interest  data prepared for analysis/pattern detection Feature  object having geometry & values of several different properties  1. classified object, snapshot for transport  geological map elements  2. object created by human activity, artefact of investigation  borehole, mine, specimen

23 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

24 Datamodels and interfaces What about points, lines and polygons? Many people experienced with digital spatial data management systems make the conversion to "points, lines and polygons" automatically. This is a geometry-centric abstraction, which may not be strongly related to the business viewpoint, which concerns the conceptual significance of the data. Most features have a geometry, so it may be convenient to sort and manage features with properties of the same geometry-type together - e.g. this allows indexing to be optimised. The geometry-centric approach is best thought of as an implementation viewpoint.

25 Datamodels and interfaces Service implemented as a set of operations  “REST” - request-response message pairs  carried over http Fine-grained  ~1-1000 features GetFeature request  feature type  properties of interest – projection clause  filter condition – selection clause Web Feature Service WFS - Standard interface to geospatial data


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