Exchanging observations and measurements: a generic model and encoding Simon Cox Research Scientist 22 May 2007.

Slides:



Advertisements
Similar presentations
Geoscience Information Network Stephen M Richard Arizona Geological Survey National Geothermal Data System.
Advertisements

Water Quality data transfer
Architectures for Data Access Services Practical considerations for design of discoverable, reusable interoperable data sources.
Observations, Features, Coverages, SOS Simon Cox CSIRO Exploration and Mining 9 September 2006.
Information Modelling MOLES Metadata Objects for Linking Environmental Sciences S. Ventouras Rutherford Appleton Laboratory.
1 OGC Web Services Kai Lin San Diego Supercomputer Center
Using the Assay Data Exchange standard with WFS to build a complete minerals exploration data-transfer chain Simon CoxA.Dent, S.Girvan, R.Atkinson.
Community semantics and interoperability: the ISO/TC 211 framework and the “Hollow World” Simon Cox CSIRO Exploration and Mining 6 September.
AN ORGANISATION FOR A NATIONAL EARTH SCIENCE INFRASTRUCTURE PROGRAM Information modelling – tools Simon Cox.
UNCERTML - DESCRIBING AND COMMUNICATING UNCERTAINTY Matthew Williams
Sensitivities in rock mass properties A DEM insight Cédric Lambert (*) & John Read (**) (*) University of Canterbury, New Zealand (**) CSIRO - Earth Science.
A standard information transfer model scopes the ontologies required for observations Simon Cox, Laurent Lefort TDWG, Fremantle,
January 5, Feature Tracking in VR for Cumulus Cloud Life-Cycle Studies E. J. Griffith, F. H. Post, M. Koutek, T. Heus and H. J. J. Jonker 11 th.
Pacific Island Countries GIS/RS User Conference 2010, Suva, November 2010 Sensor Web Enablement for the Pacific Vulnerability and adaptation of coastal.
Copyright © 2006, Open Geospatial Consortium, Inc., All Rights Reserved. The OGC and Emergency Services: GML for Location Transport & Formats & Mapping.
Exercise set 3: Basic cross sections
AN ORGANISATION FOR A NATIONAL EARTH SCIENCE INFRASTRUCTURE PROGRAM Information modelling – standards context Simon Cox.
The role of registries within a spatial data infrastructure Simon CoxRob Atkinson Research ScientistSpatial Architect 16 April 2008.
N 2401/N 2402 New Work Item Proposal - Observation and Sampling schema Simon Cox Research Scientist 28 May 2008.
Preparation of Geological Data Standards of Turkey Based on INSPIRE Directives A joint project completed by General Directorate of Geographical Information.
Interoperability A simple case for standards Kim Finney JCADM – Rome 2007.
Domain Modelling and Implementation Standards context Simon Cox Research Scientist Sydney - December, 3 rd 2010.
 1  Outline  stages and topics in simulation  generation of random variates.
Mike Botts – August Supporting QA/QC for Ocean Observations using Sensor Web Enablement (SWE) and SensorML August 2008 Mike Botts (UAH), Tony Cook.
Mike Botts – January Supporting QA/QC in Sensor Web Enablement (SWE) and SensorML February 2008 Mike Botts Principal Research.
® The sampled feature of hydrologic observation Hydrology Domain Working Group at the OGC/TC Meeting, Austin, 2012, Mar Irina Dornblut, Global Runoff.
Interoperability and architectures Simon Cox CSIRO Exploration and Mining 23 May 2006.
Mapping between SOS standard specifications and INSPIRE legislation. Relationship between SOS and D2.9 Matthes Rieke, Dr. Albert Remke (m.rieke,
Geology, mining, groundwater, landscape and soils The ‘Earth Science’ domains Bruce Simons Spatial Information Modelling Community of Practice workshop,
IntroductionToSensorML Alexandre Robin – October 2006.
How do you want that data? Spatial information models and web interfaces Simon Cox CSIRO Exploration and Mining 7 September 2005.
Information Viewpoints and Geoscience Service Architectures Simon Cox Research Scientist 13 December 2007.
® Sponsored by GroundWater ML 2 IE (GW2IE) GroundWater ML 2 IE (GW2IE) Progress Report 95th OGC Technical Committee Boulder, Colorado USA Bruce Simons.
What is Information Modelling (and why do we need it in NEII…)? Dominic Lowe, Bureau of Meteorology, 29 October 2013.
Metadata Models in Survey Computing Some Results of MetaNet – WG 2 METIS 2004, Geneva W. Grossmann University of Vienna.
Designing GML application schemas for Observations and Measurements Simon Cox CSIRO Exploration and Mining 22 March 2006.
OM-JSON Simon Cox | Research Scientist | Environmental Information Infrastructures 21 st September 2015 LAND AND WATER, DATA61 a JSON implementation of.
® GRDC Hydrologic Metadata - core concepts - 5 th, WMO/OGC Hydrology DWG New York, CCNY, August 11 – 15, 2014 Irina Dornblut, GRDC of WMO at BfG Copyright.
Exploiting the Observations and Measurements Standard for interoperability in the Earth Sciences and beyond Lesley Wyborn Simon Cox.
Observations and sampling: common patterns Simon Cox CSIRO Exploration and Mining 7 March 2007.
Semantically-Enabled Science Data Integration (SESDI) and The Virtual Solar-Terrestrial Observatory (VSTO) Semantically-enabled (large-scale) Scientific.
1 Enviromatics Environmental sampling Environmental sampling Вонр. проф. д-р Александар Маркоски Технички факултет – Битола 2008 год.
XMML – a standards-conformant XML language for geology features Simon Cox CSIRO Exploration & Mining
GeoSciML- a geoscience specific GML application to support interchange of geoscience information CGI Interoperability Working Group Presented by Stephen.
Harmonisation of Grid and Geospatial Services Standards in the Earth and Environmental Sciences Simon Cox 1, Lesley Wyborn 2, Andrew Woolf.
Managing different views of data Simon Cox CSIRO Exploration and Mining 29 November 2006.
The CGI: Advancing International Geoscience Data Interoperability John Broome - CGI Council - Earth Sciences Sector, Natural Resources Canada.
Web Services and Geologic Data Interchange Simon Cox CSIRO Exploration & Mining
Page 1 CSISS Center for Spatial Information Science and Systems Access HDF-EOS data with OGC Web Coverage Service - Earth Observation Application Profile.
E2E Spatial Infrastructures The South Esk Hydrological Sensor Web Andrew Terhorst Project Lead: Real-Time Water Information Systems 6 December 2010 Water.
Standards-based methodology for developing a geoscience markup language Simon Cox Research Scientist 9 August 2008.
© 2006, Open Geospatial Consortium, Inc. The OGC Sensor Web Enablement framework Simon CoxMike Botts CSIRO Exploration & MiningNational Space Science &
Observations & Measurements & SWE in Inspire OGC Hydro DWG Workshop – Reading – Sylvain Grellet Office International de l’Eau.
WIGOS Data model – standards introduction.
Dominic Lowe, British Atmospheric Data Centre, STFC OGC TC, Boulder.
Grids and Beyond: netCDF-CF and ISO/OGC Features and Coverages Ethan Davis, John Caron, Ben Domenico UCAR/Unidata AMS IIPS, 23 January 2008.
® Using (testing?) the HY_Features model, 95th OGC Technical Committee Boulder, Colorado USA Rob Atkinson 3 June 2015 Copyright © 2015 Open Geospatial.
Exchanging observations and measurements: applications of a generic model and encoding Simon Cox CSIRO Exploration and Mining 15 December.
® Hosted and Sponsored by Observed Observable Properties - from HY_Features perspective - OGC Hydrology Domain Working Group 3 rd Meeting, Reading, UK,
Leverage and Delegation in Developing an Information Model for Geology Simon Cox Research Scientist 14 December 2007.
Leverage and Delegation in Developing an Information Model for Geology Simon Cox Research Scientist 14 December 2007.
NOAA IOOS SOS Implementations in 2008 Jeff de La Beaujardière, PhD NOAA IOOS Program DIF Sr Systems Architect.
Tutorial 1 Description of a Weather Station using SensorML Alexandre Robin
® Sponsored by SOS 2.0 Profile For Hydrology 90th OGC Technical Committee Washington, DC Michael Utech 26 March 2014 Copyright © 2014 Open Geospatial Consortium.
OGC TC Washington – HydroDWG meeting – Inspire O&M & SWE requirements - profile BRGM – S.Grellet 52N – S.Jirka.
Implementing distributed geoscience information systems using Open GIS Web Services Simon Cox CSIRO Exploration & Mining
U.S. Department of the Interior U.S. Geological Survey WaterML Presentation to FGDC SWG Nate Booth January 30, 2013.
® OGC Sensor Web Enablement Dr Andrew Woolf STFC e-Science Centre Rutherford Appleton Laboratory, UK.
Updated version of TGs - O&M and SWE for INSPIRE (D2
Simon Cox Research Scientist 16 April 2008
Presentation transcript:

Exchanging observations and measurements: a generic model and encoding Simon Cox Research Scientist 22 May 2007

CSIRO OGC Interface composition patterns Science relies on observations Provides evidence & validation Involves sampling This paper is about a domain-independent terminology and information-model Fast overview, much more detail available …

CSIRO OGC Interface composition patterns Examples The 7th banana weighed 270gm on the kitchen scales this morning The attitude of the foliation at outcrop 321 of the Leederville Formation was 63/085, measured using a Brunton on Specimen H69 was identified on by Amy Bachrach as Eucalyptus Caesia The image of Camp Iota was obtained by Aster in 2003 Sample WMC997t collected at Empire Dam on was found to have 5.6 g/T Au as measured by ICPMS at ABC Labs on The X-Z Geobarometer determined that the ore-body was at depth 3.5 km at 1.75 Ga The simulation run on indicated that the pressure in the hanging-wall at 618 Ma was reduced 4 MPa

CSIRO OGC Interface composition patterns What is “an Observation” Observation act involves a procedure applied at a specific time (Fowler & Odell, 1997ish) The result of an observation is an estimate of some property The observation domain is a feature of interest at some time [0..*] locations may be of interest, associated with the procedure and feature of interest

CSIRO OGC Interface composition patterns Observed property Length, mass, temperature, shape location, event-time, orientation colour, chemical concentration count/frequency, presence species or kind (classification) Expressed using a reference system or scale Scale may also be ordinal or categorical May require a complex structure “Sensible”, but not necessarily physical …

CSIRO OGC Interface composition patterns Feature-of-interest The observed property is associated with something Location does not have properties, the substance or object at a location does Observed property must be logically consistent with the feature-of-interest E.g. rock-density, pixel-colour, city-population, ocean-surface- temperature … i.e. the Observation “target”

CSIRO OGC Interface composition patterns Procedure Instruments & Sensors Respond to a stimulus from local physics or chemistry Intention may concern local or remote source Sample may be in situ or re-located

CSIRO OGC Interface composition patterns Generic pattern for observation metadata An Observation is an action whose result is an estimate of the value of some Property of the Feature-of-interest, obtained using a specified Procedure Feature-of-interest concept reconciles remote and in-situ observations

CSIRO OGC Interface composition patterns When is this viewpoint interesting? Primarily if the data-acquisition metadata is of concern

CSIRO OGC Interface composition patterns Specialize by result-type

CSIRO OGC Interface composition patterns Procedures are usually process chains Procedure often includes data processing, to transform “raw” data to semantically meaningful values Voltage  orientation count  radiance  NDVI Position + orientation  scene-location Mercury meniscus level  temperature Shape/colour/behaviour  species assignment This requires consideration of “sensor”-models and calibrations

CSIRO OGC Interface composition patterns Advanced procedures Modelling, simulation, classification are procedures “raw” data == modeling constraints (sensor-outputs=process-inputs) “processed” data == simulation results (outputs) “interpreted” data == classification results (outputs) SensorML provides a model and syntax for describing process-chains

CSIRO OGC Interface composition patterns Domain profile feature of interest Feature-type is taken from a domain-model (e.g. Geology) observed property Belongs to feature-of-interest-type procedure Standard procedures, suitable for the property-type

CSIRO OGC Interface composition patterns Conceptual object model: features Digital object corresponding with identifiable, typed, object 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 …

CSIRO OGC Interface composition patterns Geology domain model – (e.g. GeoSciML) Borehole  collar location  shape  collar diameter  length  operator  logs  related observations  … Fault  shape  surface trace  displacement  age  … Ore-body  commodity  deposit type  host formation  shape  resource estimate  … type(featureOfInterest) = any of these classes observedProperty = any of these properties Geologic Unit  classification  shape  sampling frame  age  dominant lithology  … License area  issuer  holder  interestedParty  shape(t)  right(t)  …

CSIRO OGC Interface composition patterns Some properties vary within a feature 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 Function on some axis of the feature Corresponding Observation/result is a Function if spatio-temporal also known as coverage or map

CSIRO OGC Interface composition patterns Proximate vs ultimate feature-of-interest The ultimate (project) thing of interest may not be directly or fully accessible 1.Sensed property is a proxy e.g. want land-cover, observe colour Post-processing required FoI may change during processing – e.g. “scene”  “tract” 2.Proximate feature of interest embodies a sample design Rock-specimen samples an ore-body or geologic unit Well samples an aquifer Profile samples an ocean/atmosphere column Cross-section samples a rock-unit Some standard designs are common

CSIRO OGC Interface composition patterns Sampling Features model

CSIRO OGC Interface composition patterns Sampling Manifolds Provide bounds-for sub- sampling, but not details of decomposition

CSIRO OGC Interface composition patterns Specimen Specimens are SamplingFeatures used for ex-situ observation and analysis

CSIRO OGC Interface composition patterns Examples The 7th banana weighed 270gm on the kitchen scales this morning The attitude of the foliation at outcrop 321 of the Leederville Formation was 63/085, measured using a Brunton on Specimen H69 was identified on by Amy Bachrach as Eucalyptus Caesia The image of Camp Iota was obtained by Aster in 2003 Sample WMC997t collected at Empire Dam on was found to have 5.6 g/T Au as measured by ICPMS at ABC Labs on The X-Z Geobarometer determined that the ore-body was at depth 3.5 km at 1.75 Ga The simulation run on indicated a pressure reduction of 4 MPa at 600 Ma

CSIRO OGC Interface composition patterns Development and validation of O&M Developed in the context of XMML Geochemistry/Assay data OGC Sensor Web Enablement – environmental and remote sensing Subsequently applied in Water resources/water quality (WQDP, AWDIP, WRON) Oceans & Atmospheres (UK CLRC, UK Met Office) Natural resources (NRML) Taxonomic data (TDWG) Geology field data (GeoSciML) I could have put dozens of logos down here

CSIRO OGC Interface composition patterns Status OGC Best Practice paper, r4 – 2006 RFC OGC RWG  Adopted Specification – late 2007? ISO Standard – ? Adopted as a key aspect of GeoSciML

Thank you Exploration & Mining Simon Cox Research Scientist Phone: Web: Contact Us Phone: or Web:

CSIRO OGC Interface composition patterns “Cross-sections” through collections SpecimenAu (ppm) Cu-a (%)Cu-b (%)As (ppm)Sb (ppm) ABC A Row gives properties of one feature A Column = variation of a single property across a domain (i.e. set of locations)

CSIRO OGC Interface composition patterns Assignment of property values For each property of a feature, the 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

CSIRO OGC Interface composition patterns Observations, features and coverages Feature summary Property-value evidence Multiple observations one feature, different properties: feature summary evidence A property-value may be a coverage Same property on multiple samples is a another kind of coverage Multiple observations different features, one property: coverage evidence

CSIRO OGC Interface composition patterns SOS getObservation getResult describeSensor getFeatureOfInterest Accessing data using the “Observation” viewpoint WFS/ Obs getFeature, type=Observation WCS getCoverage getCoverage (result) Sensor Register getRecordById WFS getFeature e.g. SOS::getResult == “convenience” interface for WCS

CSIRO OGC Interface composition patterns WFS/ SFS Accessing data using the “Sampling Feature Service” viewpoint WFS getFeature WCS getCoverage getCoverage (property value) SOS getObservation Common data source getFeature (sampling Feature) getFeature (coverage property value) getFeature (relatedObservation) getCoverage (result) Sensor Register getRecordById (procedure) getFeature (featureOfInterest) getObservation (relatedObs) getResult (property value)

CSIRO OGC Interface composition patterns WFS Accessing data using the “Domain Feature” viewpoint WCS getCoverage (property value) getFeature SOS getResult (property value) The “George Percivall preferred™” viewpoint #1 – observations are property-value-providers for features ??

CSIRO OGC Interface composition patterns WCS Accessing data using the “just the data” viewpoint WFS getFeature/geometry (domain exent) getCoverage SOS getResult (lots of ‘em) (range values) The “George Percivall preferred™” viewpoint #2 – observations are range-value-providers for coverages

CSIRO OGC Interface composition patterns Conclusions Different viewpoints of same information for different purposes Summary vs. analysis Some values are determined by observation Sometimes the description of the estimation process is necessary Transformation between views important Management of observation evidence can be integrated (Bryan Lawrence issues) For rich data processing, rich data models are needed Explicit or implicit Data models (types, features) are important constraints on service specification

Thank you Exploration & Mining Simon Cox Research Scientist Phone: Web: Contact Us Phone: or Web: