Скачать презентацию Ollie Raymond 6 November 2006 Dale Percival Lesley Скачать презентацию Ollie Raymond 6 November 2006 Dale Percival Lesley

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Ollie Raymond 6 November 2006 Dale Percival Lesley Wyborn Ollie Raymond 6 November 2006 Dale Percival Lesley Wyborn

Special acknowledgements • Irina Bastrakova • Aaron Sedgman • Nick Ardlie Special acknowledgements • Irina Bastrakova • Aaron Sedgman • Nick Ardlie

Don’t you hate it when… § You can’t exchange geological data with your project Don’t you hate it when… § You can’t exchange geological data with your project partners because you use different systems? § You didn’t realise that the shapefile you downloaded last year has been superseded by an updated version? § You know there’s useful information out there, but you can’t find it? § You waste valuable time downloading and converting datasets § You cannot add real-time data from other sources to your information systems? § You keep emailing and burning CDs to publish your data to clients who need it urgently? § YOU NEED A WEB-DELIVERED DATA STANDARD!

Currently in Australia… Databases and digital maps with local data structures TAS QLD VIC Currently in Australia… Databases and digital maps with local data structures TAS QLD VIC NSW Online GIS FTP WA GA Data sources Convert data Proprietary formats No ability to view another state’s data in web client Joe Public Local data structures Shapefile GSWA data Convert proprietary format Government Universities Shapefile GA data Minerals industry Arc. IMS Arc Export GA data NT SA Download data Mapserver Mapinfo NTGS data Rationalise attribute data structure Resource management Petroleum industry Environment FTP Mapinfo GA data Web services

Rationalising data structures WA Age Description NT Rationalising data structures WA Age Description NT

Key Driver: Minerals Exploration Action Agenda Industry input highlighted § problems in gaining access Key Driver: Minerals Exploration Action Agenda Industry input highlighted § problems in gaining access to precompetitive geoscience information § described existing information as commonly incomplete and fragmented across eight government agencies, each with its own information management systems and structures § noted that the disparate systems lead to inefficiencies causing higher costs, reduced effectiveness and increased risk incurred by the industry and its service providers

Key Driver: Minerals Exploration Action Agenda Key Initiative § Australian Government, State and Territory Key Driver: Minerals Exploration Action Agenda Key Initiative § Australian Government, State and Territory geoscience agencies, professional associations and industry to cooperatively develop and implement nation-wide protocols, standards and systems that provide internet-based access to, and effective storage and archiving of, industry and government exploration-related data

A short history of some geological data standards… In USA and Canada… North American A short history of some geological data standards… In USA and Canada… North American Data Model (1996 -present) - a comprehensive geological model - conceptual, theoretical, difficult to implement In Australia… GGIPAC data modelling committee - National Geological Data Model (NGDM v. 1, 2004) - logical model, more structured than NADM - not comprehensive, never fully implemented

A short history of some geological data standards… Internationally… IUGS Commission for the Management A short history of some geological data standards… Internationally… IUGS Commission for the Management and Application of Geoscience Information (CGI) 2003 – Edinburgh § Data Model Collaboration Working Group (DMWG) formed § 15 countries initially represented 2004 – Perth, Florence § set up teams to model geological units, materials, structures & boreholes § demonstrated a boreholes WFS testbed at IGC 32 Florence 2005 - Ottawa § Geo. Sci. ML beta version § specified Testbed 2 for sharing geologic map data § GA joins DMWG – October 05 § Geo. Sci. ML 1. 0 - January 06

A short history of some geological data standards… IUGS Commission for the Management and A short history of some geological data standards… IUGS Commission for the Management and Application of Geoscience Information (CGI) May 2006 - Orleans § Geo. Sci. ML 1. 1 revisions; clarified Testbed 2 use cases September 2006 – Liege/Brussels § public release of Geo. Sci. ML 1. 1 § demonstrated Testbed 2 at IAMG conference § commenced work on Geo. Sci. ML 2. 0 GGIPAC have now adopted the Geo. Sci. ML international model as the Australian geological data standard Australian input to the Geo. Sci. ML working groups is being coordinated by Bruce Simons (GSV), Ollie Raymond and Lesley Wyborn (GA)

Geo. Sci. ML Working Group § Canada: Eric Boisvert, Boyan Brodaric (GSC) § UK: Geo. Sci. ML Working Group § Canada: Eric Boisvert, Boyan Brodaric (GSC) § UK: Tim Duffy, Marcus Sen, John Laxton (BGS) § USA: Bruce Johnson (USGS), Steve Richard (Arizona) § France: Jean-Jacques Serrano, Dominique Janjou, Christian Bellier, Francois Robida (BRGM) § Sweden: Lars Stolen, Jonas Holmberg, Thomas Lindberg (SGU) § Australia: Simon Cox (CSIRO), Bruce Simons, Alistair Ritchie (Geo. Science Victoria) Ollie Raymond, Lesley Wyborn, Dale Percival (Geoscience Australia) Geo. Sci. ML ‘Champions’ Ian Jackson (UK), John Broome (Canada), Kristine Asch (Germany)

What is Geo. Sci. ML? 1. Geological Data Model § § § scientifically robust What is Geo. Sci. ML? 1. Geological Data Model § § § scientifically robust structured attribute data based on existing models UML schema version 1. 1 Geologic units § lithological units Earth Materials § rocks Structures § contacts, faults Vocabularies § lookup tables, authority tables

What is Geo. Sci. ML? 1. Geological Data Model Current work § § § What is Geo. Sci. ML? 1. Geological Data Model Current work § § § version 2. 0 fixing issues highlighted by the testbed implementation geological units § more unit types § regolith earth materials § amendments to attributes § fossils, minerals structures and fabrics vocabularies Opportunities for Australian leadership

Mapping your GA data to Geo. Sci. ML GEODX. STRATNAMES. TOPMINAGENAME GEODX. STRATNAMES. BASEMAXAGENAME Mapping your GA data to Geo. Sci. ML GEODX. STRATNAMES. TOPMINAGENAME GEODX. STRATNAMES. BASEMAXAGENAME Describe a geological unit in Geo. Sci. ML GEODX. STRATLITHS. LITHOLOGY SDE. CDI_VICSTRATS. FORMTYPE GEODX. RANKSYNONYMS. RANKNAME

Mapping your GA data to standard vocabularies Cainozoic? Late? Early? Archaean? Palaeozoic? Bolindian? Eastonian? Mapping your GA data to standard vocabularies Cainozoic? Late? Early? Archaean? Palaeozoic? Bolindian? Eastonian? Gisbornian?

What is Geo. Sci. ML? 2. GML encoding § extension of XML § builds What is Geo. Sci. ML? 2. GML encoding § extension of XML § builds on GML (Geographic Markup Language), XMML, and other standard schema

What is Geo. Sci. ML? GML Links to other modelling (Geography Markup Language) languages What is Geo. Sci. ML? GML Links to other modelling (Geography Markup Language) languages O&M (Observations & Measurements) XMML Boreholes Geo. Sci. ML (Geoscience Markup Language)

Geo. Sci. ML Testbed 2 architecture Databases, digital maps with local data structures Map Geo. Sci. ML Testbed 2 architecture Databases, digital maps with local data structures Map local data structures to Geo. Sci. ML data structure Ionic Geo. Sci. ML Sweden Arc. IMS Cocoon Geo. Sci. ML USA Mapserver Cocoon Geo. Sci. ML Arc. IMS Cocoon Geo. Sci. ML UK Geoserver Geo. Sci. ML GA Geoserver Geo. Sci. ML Mapserver Geo. Sci. ML Display, query, download France Canada Data sources BRGM client (Ionic) GSC client (Phoenix) Web services Desktop client (eg: Gaia) GA client (IMF) Web clients

Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web client in Canada Vancouver, CA Keyworth, UK Ottawa, CA Uppsala, SV Orleans, FR Reston, VA Tuscon, AZ Canberra, AU CLIENT SERVERS

Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web client in Canada Vancouver, CA Keyworth, UK Ottawa, CA Uppsala, SV Orleans, FR Reston, VA Tuscon, AZ Canberra, AU Geo. Sci. ML

Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a web client in France

Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a desktop Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a desktop client

Geo. Sci. ML Testbed 2 Web services use cases Use case 1: § § Geo. Sci. ML Testbed 2 Web services use cases Use case 1: § § load a web service display a map, query a single feature return attributes in Geo. Sci. ML Use case 2: § § query several map features download features in Geo. Sci. ML format Use case 3: § reclassify (colour) map features based on Geo. Sci. ML attributes

Geo. Sci. ML Testbed 2 Live testbed demonstrations… Geo. Sci. ML Testbed 2 Live testbed demonstrations…

Geo. Sci. ML Testbed 2 – Use Case 1 ▪ Display a map and Geo. Sci. ML Testbed 2 – Use Case 1 ▪ Display a map and query a feature

Geo. Sci. ML Testbed 2 – Use Case 1 ▪ Harmonising data across borders Geo. Sci. ML Testbed 2 – Use Case 1 ▪ Harmonising data across borders • data format is the same across borders

Geo. Sci. ML Testbed 2 ▪ Harmonising data across borders The data format will Geo. Sci. ML Testbed 2 ▪ Harmonising data across borders The data format will be the same across borders Unfortunately Geo. Sci. ML cannot edgematch your data • attribute data format is the same across borders

Geo. Sci. ML Testbed 2 – Use Case 2 ▪ Download data in Geo. Geo. Sci. ML Testbed 2 – Use Case 2 ▪ Download data in Geo. Sci. ML format § select an area § download Geo. Sci. ML to local PC

Geo. Sci. ML Testbed 2 – Use Case 3 ▪ Display a map coloured Geo. Sci. ML Testbed 2 – Use Case 3 ▪ Display a map coloured according to an attribute

Geo. Sci. ML Testbed 2 – Use Case 3 ▪ Reclassify maps on the Geo. Sci. ML Testbed 2 – Use Case 3 ▪ Reclassify maps on the fly

Geo. Sci. ML Testbed 2 ▪ Geo. Sci. ML presented in various formats Geo. Sci. ML Testbed 2 ▪ Geo. Sci. ML presented in various formats

Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a desktop Geo. Sci. ML Testbed 2 ▪ Accessing Geo. Sci. ML data using a desktop client For example: Gaia

Geo. Sci. ML Testbed 2 ▪ Geoscience Australia web client - IMF Geo. Sci. ML Testbed 2 ▪ Geoscience Australia web client - IMF

A goal for Australia… from this Databases and digital maps with local data structures A goal for Australia… from this Databases and digital maps with local data structures TAS QLD VIC NSW Online GIS FTP WA GA Data sources Convert data Proprietary formats No ability to view another state’s data in web client Joe Public Local data structures Shapefile GSWA data Convert proprietary format Government Universities Shapefile GA data Minerals industry Arc. IMS Arc Export GA data NT SA Download data Mapserver Mapinfo NTGS data Rationalise attribute data structure Resource management Petroleum industry Environment FTP Mapinfo GA data Web services

… to this Databases, digital maps with local data structures Map local data structures … to this Databases, digital maps with local data structures Map local data structures to Geo. Sci. ML Display, query, download TAS QLD Joe Public Ionic Geo. Sci. ML GA client (IMF) VIC Universities Arc. IMS Geo. Sci. ML State survey clients (Arc. IMS) NSW NT SA Geoserver Geo. Sci. ML Mapserver Geo. Sci. ML Minerals industry Resource management Desktop clients (Gaia, Arc. Map) WA Petroleum industry Environment GA Data sources Government Web services Web clients

Where does this Test bed fit into GA’s 2004 -2009 IM strategic plan? Machine Where does this Test bed fit into GA’s 2004 -2009 IM strategic plan? Machine to Machine Interfaces Human Interfaces Figure 4: IM Strategic Goals (GA IMSP 2004 -2009, p 12)

How do you cross the golden line to the machine to machine world? As How do you cross the golden line to the machine to machine world? As per the Geo. Sci. ML test bed, the critical steps are to: A) move to a 3 -tier architecture: § 1) Content Layer (Data, Information Knowledge) § 2) Middle Layer which interfaces the two § 3) Applications Layer (programs) B) Separate your content from its portrayal C) Recognise common elements across GA § (eg Ollie is Rocks and Dirt) D) Look internationally for relevant standards

Making the plethora of GA Content Layers machine readable We have over 17 data Making the plethora of GA Content Layers machine readable We have over 17 data themes with over 300 individual data sets We currently are ‘SPOTting’ four themes this FY How can we accelerate this process? By recognising the common elements across the organisation (ie Ollie is rocks and dirt) In particular, separate geometry from content

International Year of Planet Earth 10 Scientific themes SOURCE: http: //www. yearofplanetearth. org/downloads. htm International Year of Planet Earth 10 Scientific themes SOURCE: http: //www. yearofplanetearth. org/downloads. htm

CONTENT TECHNICAL Separating content from geometry We made these geometries interoperable (Dale, Aaron, Nick) CONTENT TECHNICAL Separating content from geometry We made these geometries interoperable (Dale, Aaron, Nick) 1) lines as geological boundaries (ID) § Abstract pattern is a 1 D profile which applies also to boreholes, pipelines, roads 2) polygons as geological map units (2 D) § Abstract pattern is a 2 D polygon which applies to tenements, landslides, surveys We made these ‘Earth Materials’ interoperable (Ollie, Lesley, Irina) 1) Geological units (including stratigraphy, granites) 2) Rock Types 3) Ages of units and we did it at an international level

And we are becoming mainstream…………… And we are becoming mainstream……………

GA Interoperability Teams working towards international content standards Fluid Inclusions (2002) § Terry Mernagh GA Interoperability Teams working towards international content standards Fluid Inclusions (2002) § Terry Mernagh (Minerals) Thermodynamics (2002) § Evgeniy Bastrakov (Minerals) Geodesy (2004) § Danny Galbraith (GEMD) Gazetteer (2005) § Lynette Sebo (GEMD) Earth Materials, Geological Units and Structures (Geo. Sci. ML) (2005) § Ollie Raymond (Minerals), Irina Bastrakova (CIMA) Karol Czarnota, Richard Blewett (Minerals) Landslides (2006) § Monica Osuchowski (GEMD) Geochronology (2006) § Keith Sircombe (Minerals) Geochemistry including instrument metadata (2006) § David Champion, Anthony Budd (Minerals), Dianne Edwards, Tamara Buckler (PMD) Seismic Velocities (2006) § Peter Petkovic (PMD), Bruce Goleby (Minerals), Clive Collins (GEMD)

Where Can I learn more? SEE Grid Week 27 Nov - 1 December Mon Where Can I learn more? SEE Grid Week 27 Nov - 1 December Mon 27 November: Spatial Information CRC = GEMD, Minerals, PMD § Emerging approaches to SDIs (GIS delivery in a distributed environment) Tues 28 November: OSDM seminar on Standards = PL’s & GL’s § What busy managers need to know about the rapidly emerging standards game Wed 29 November: AUKEGGS = PMD, Minerals, GEMD § Interoperability of Marine Geospatial Data (including binary data and Marine. ML) Wed 29 November: Australian Geol Surveys = Minerals, PMD, GEMD § Strategic Issues for Building, Managing and Delivering 3 D models Thurs 30 November – Fri 1 December: SEE Grid lll = everyone!!! § Computational Modelling and Decision Support in the Solid Earth and Environmental Community More info on http: //www. seegrid. csiro. au

Questions? For further information on Geo. Sci. ML: https: //www. seegrid. csiro. au/twiki/bin/view/CGIModel/Geo. Sci. Questions? For further information on Geo. Sci. ML: https: //www. seegrid. csiro. au/twiki/bin/view/CGIModel/Geo. Sci. ML or contact Ollie Raymond (x. 9575)