www.csiro.au interoperability and architectures simon cox csiro exploration and mining 23 may 2006

www.csiro.au

Interoperability and architectures

Simon Cox

CSIRO Exploration and Mining

23 May 2006

NR Interoperability 2 of 71

Outline

Precedent – the SEE Grid demonstrator/use-case

WFS refresher

The Natural Resources puzzle

SOA model - publish-find-bind?

Registries are out-of-scope for this workshop

focus only on bind leg

“informational service interface profile”

www.csiro.au


Status quo: Different formats and standards

Data Structures

Proprietary Software

Versions of Software

User


The vision: Same format and standards

User

GML for Natural Resource Information

NRML

NRML

NRML


Standard informational service profiles

Business case revolves around:

Existence of multiple sources of same information types

Users want to replace or merge data sources, re-compose service chains, on demand at run time

Providers are willing to cooperate

regulatory push

market pull

Technical requirements

non-intrusive

discoverable

IPR protection, access and authentication control, accounting

orderly governance framework


The mechanism: OGC Web Feature Service

GML WFSServer

Data-source organised for custodian’s requirements

Community-specific GML application language

TigerGML, LandGML, GeoSciML, CSML, MarineXML, NRML etc

private public boundary

WFSClient

HTML


Standard transfer format allows multiple data sources

WFSClient

WFSServer

WFSServer

B

WFSServer

C


PIRSAWeb Feature Service (WFS)

Common Interface Binding – GML/XMML

GA Geochemistry

Feature Data Source

DOIRGeochemistry

FeatureData Source

DOIRWeb Feature Service (WFS)

GAWeb Feature Service (WFS)

Geoserver (Open Source)

PostGIS (Open Source)

OraclePostGIS (Open Source)

CLIENT APPLICATIONS

DATA ACCESS SERVICES

DATA SOURCES

WebMap Composer

GA Reports Application

PIRSA Geochemistry

FeatureData Source

Summary architecture


Data re-use

WFSClient

WFSServer

multiple views of same data

(features)

SOSClient

SOSServer

(observations)

WCSServer(coverages)

WCSClient


Combining with observation service

WFSClient

WFSServer

WFS/SOSClient/Server

(orchestration)

WFSClient

(simulation)

(mapping)

WFSClient (analysis &reporting)

SOSServer

Sensor

BPEL?


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 details


Report client

http://www.ga.gov.au/wfs/reader/wfsGeochemReaderHome.jsp

Many servers, one report

NR Interoperability 29 of 71 PIRSA DOIR GA

http://cgsrv3.arrc.csiro.au/seegrid/savedapps/filter

Many servers, one map

Mapping Client


Combine their data with your data


GML-based data can be …. Rendered into a

queryable map …

… formatted into a

report or ….

… read and used by any

WFS/GML enabled application

Pre-requisite: community-standard data model/encoding

One service – many uses


The Natural Resource Information Infrastructure puzzle (some pieces)

Data Bases /Systems

InformationProductsInformation

ProductsInformationProducts

XMLGML

document

StyleLayer

descriptor

“ARO”application

Web servicesWMSWFS

Schema.XSD

Processes

FeatureCatalogue UML

Abstract model

SensorSensor

Sensor


InformationProductsInformation

ProductsInformationProducts

SupportBusiness needsNRM planning &Investment decisions

Are createdby

Processes

That use

Data Bases /Systems

Are modelledby

UMLAbstract model

Are describedin

Information ProductTemplate (metadata)

FeatureCatalogue

That specifies

Is implementedby

Schema.XSD

“ARO”application

Sends request / query

Returns response

XMLGML

document

Is validatedby

Accesses

Accesses

Web servicesWMSWFS

Used todescribe

StyleLayer

descriptor

Is displayedwith

Are accessed through

SensorSensor

Sensor

Are fed by

Workshop Scope


Use-cases define requirements

Who are the users?

give them names!

What do they want?

tell a detailed story, sketch wireframes

“first X, then Y, visualized this way, allowing selection of Z”

Analyze the requests and data flow to determine the objects and features of interest

www.csiro.au

Domain modelling

Simon Cox


23 May 2006


Geographic Information Models

Viewpoints: Features, coverages and observations


How the world is seen: Fields vs. objects

mapped-objects“Feature” viewpoint

earth-observations“Coverage” viewpoint


1. Classic geometry-centric GIS approach

One shape per feature …

well suited to drawing maps

strictly an implementation strategy for portrayal

hides the (semantic) 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


2. Conceptual object model: features

Digital objects correspond with identifiable, typed, objects in the real world

mountain, road, specimen, event, tract, catchment, wetland, farm, IBRA, bore, reach, property, lease-area

Feature-type is characterised by a specific set of properties

Specimen

ID (name)

description

mass

processing details

sampling location

sampling time

related observation

material

…


Variation of a property across the domain of interest

For each element/position in a spatio-temporal domain, a value from the range can be determined

Discrete or continuous domain

Domain is often a grid

N.B. Arc/Info “coverage” == multi-geometry domain, attribute-table for each element

3. Spatial function: coverage

(x1,y1)

(x2,y2)


Feature properties

For “normal” features, the value of each property is constant on the feature

spatial values are just another property

multiple geometries possible, e.g. scale dependence, dimensionality

Some properties may vary across the feature

property value is described by a coverage

Specimen

ID (name)

description

mass

processing details

sampling location

sampling time

related observation

material

…


Cross-sections through information

Specimen Au (ppm) Cu-a (%) Cu-b (%) As (ppm) Sb (ppm)

ABC-123 1.23 3.45 4.23 0.5 0.34 A Row gives properties of one feature

A Column = variation of a single property across a domain (i.e. set of locations)

A Cell describes the value of a single property, often obtained by observation or measurement


4. Property-value estimate: Observation

An Observation is

an Event

time, location, responsible-party

whose result is an estimate of the value of some Property

= Determinand, Measurand, Analyte, Phenomenon

of its Feature-of-interest

e.g. tract, catchment, sampling-station, specimen

obtained using a specified Procedure

e.g. sensor, algorithm, model, process-chain, simulation


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


Feature-of-interest centric view

Specimen

ID (name)

description

material

mass

processing details

sampling location

sampling time

related observation

…

Properties

attributes

association rolenames


Observation model

Defines the terminology for linking items of interest in observational science


Observations and coverages

If the property value is not invariant across the feature-of-interest

varies by location, in time

the corresponding observation result should be a coverage

individual values must be tied to the location within the domain, so the result will be an array of e.g.

time-value

position-value

stationID-value …


Domain modelling

Primarily involves domain-specific specializations of the second-layer (wrt Observation model):

Features-of-interest

feature-type catalogue for the domain

Determinands/properties

property dictionary or ontology

Procedures

standard procedures

A common vocabulary for these domain types must be adopted by the community


Example: AWDIP model


Information service requests

Information services will be based around the domain feature- types

e.g. “please tell me about”:

all properties of that tract/catchment/well

i.e. the values of all associated observations

the history of salinity at that station

i.e. the salinity time-series/temporal coverage with the station as the FoI

the reliability of that salinity value

i.e. the procedure and sampling parameters for the observation


Several views of the same information

Specimen Au (ppm) Cu-a (%) Cu-b (%) As (ppm) Sb (ppm)

ABC-123 1.23 3.45 4.23 0.5 0.34

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 descriptionCoverage view

Assembled by:

Using suitable sampling regime on feature-of-interest

Aggregation of multiple Observation/result having same observedProperty

Used for:

Property variation

Pattern/anomaly/feature detection


Processing/value-adding chains

make homogeneous Observations according to a sampling regime

pixels, stations, clock-ticks

assemble results into a discrete Coverage

image, log, time-series

detect a Feature

anomaly, intelligence

Observations initiate chain leading to feature detection

make heterogeneous Observations on a pre-existing feature

patient, artefact, catchment

assemble results into description of set of Feature properties

Observations provide metadata on property values


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


Which viewpoint? What are you interested in?

… describing a discrete object ? - Feature

property set characterizes feature type

associated observations provide property metadata

… variation of property within domain ? - Coverage

domain = feature of interest

e.g. tract, swath, time-period

associated observations provide results to populate coverage

… data acquisition event/process/quality ? - Observation

explicit procedure, capture time


OGC Information Service interfaces

Web Map Service

Catalog Service

Web Feature Service

Web Coverage Service

Sensor Observation Service

Sensor Planning Service (tasking)

Sensor Alert Service (subscription)

Web Processing Service


Value-adding chain

Observation

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

www.csiro.au

Formalizing the model using UML as the conceptual schema language

Simon Cox


24 May 2006


Model of a specific feature-type

Specimen

ID (name)

description

material

mass

processing details

sampling location

sampling time

related observation

…

Static properties

attributes

association rolenames


GML serialization

<sa:SampledSpecimen gml:id="abc123">

<gml:description>Specimen collected in Dales Gorge, Karijini</gml:description>

<gml:name>Dales Gorge specimen #1</gml:name>

<sa:material>rock</sa:material>

<sa:mass uom="kg">1.21</sa:mass>

<sa:processingDetails xlink:href="urn:x-ogc:def:nil:OGC:unknown"/>

<sa:relatedObservation xlink:href="http://www.seegrid.csiro.au/observations/abc_123_o1"/>

<sa:samplingLocation>

<gml:Point gml:id="ot2p">

<gml:pos srsName="urn:x-ogc:def:crs:EPSG:6.3:62836405">

-22.0 136.0

</gml:pos>

</gml:Point>

</sa:samplingLocation>

<sa:samplingTime>

<gml:TimeInstant gml:id="ot1t">

<gml:timePosition>2005-01-11T17:22:25.00</gml:timePosition>

</gml:TimeInstant>

</sa:samplingTime>

</sa:SampledSpecimen>


UML – Class Diagrams

Information Structure

c.f E-R, plus

several distinct varieties of relationships

associations

association roles

association direction

inheritance

realization

aka interface

class attributes may have complex type


Sampling features hierarchy


UML extension mechanism - stereotypes

Specialized meta-elements(Class types)

<<FeatureType>>

<<Type>>

<<DataType>>

<<Enumeration>>

<<CodeList>>

<<Union>>

<<BasicType>>

(ISO 19103/19136 profile)


UML extension mechanism – constraints

OCL may be used to express additional constraints


UML extension mechanism – Tagged values

Formal annotations – typically implementation details

Also see package tagged values


UML/GML

ISO 19103 & ISO 19136 provide 2 things:

modelling pattern

based on General Feature Model

implemented as a profile of UML and usage patterns

which leads directly to an XML Schema

components

base classes

implementation of utility classes & data-types from ISO 19107, 19108, 19111, 19123


“GML Application Schema”

follows patterns

rolenames on associations

navigability & cardinality

etc

utilizes base classes and utility components

<<FeatureType>> → specializes gml:AbstractFeature

<<Type>> → specializes gml:AbstractGML

incl. gml:AbstractGeometry

GenericName → gml:CodeType

GM_Object → gml:AbstractGeometry

etc


Standard packaging – Hollow World

UML Template

Pre-loaded with the ISO 19100 series models and others for which canonical GML or GML-conformant implementations are available

ISO 19103 – basic data types

ISO 19107 – geometry & topology

ISO 19108 – temporal objects & reference systems

ISO 19111 – spatial position & coordinate reference systems

ISO 19115 – metadata (mostly dataset-oriented)

ISO 19136/GML

SweCommon, O&M, Sampling

Geo – solid geometry elements

Configuration file to map UML elements to their canonical XML Schema representation

various namespaces


Direct GML serialization

<?xml version="1.0" encoding="UTF-8"?>

<om:Observation gml:id="obsTest1"

xmlns:om="http://www.opengis.net/om"

xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

xmlns:xlink="http://www.w3.org/1999/xlink"

xmlns:gml="http://www.opengis.net/gml"

xsi:schemaLocation="http://www.opengis.net/om ../om.xsd">

<gml:description>Observation test instance</gml:description>

<gml:name>Observation test 1</gml:name>

<om:time>

<gml:TimeInstant gml:id="ot1t">

<gml:timePosition>2005-01-11T16:22:25.00</gml:timePosition>

</gml:TimeInstant>

</om:time>

<om:location xlink:href=" http://some.interested.org/stationS1"/>

<om:procedure xlink:href="urn:x-ogc:object:feature:Sensor:OGC:scales"/>

<om:observedProperty xlink:href="urn:x-ogc:def:phenomenon:OGC:mass"/>

<om:featureOfInterest xlink:href="http://some.interested.org/vegetables/instances/banana1"/>

<om:result xsi:type="gml:MeasureType" uom="urn:x-ogc:def:uom:OGC:kg">0.28</om:result>

</om:Observation>


Challenges

Non-invariant properties encoding “coverages” in the result

array of

time-value

position-value

stationID-value

Establishing standard catalogues/dictionaries: Properties/Phenomena

Procedures/Instruments

Record schemata

Patterns for specialization Assay-measurement

WQ-observation

Met-observation

www.csiro.au

Thank You


Name Simon Cox

Title Research Scientist

Phone +61 8 6436 8639

Email [email protected]

Web www.seegrid.csiro.au

Contact CSIRO

Phone 1300 363 400

+61 3 9545 2176

Email [email protected]

Web www.csiro.au

www.csiro.au interoperability and architectures simon cox csiro exploration and mining 23 may 2006

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