There are a multitude of organisations in Australia and New Zealand pursuing spatial data supply chain initiatives. There is little to no co-ordination of these developments, leading to duplication of effort, wasted investment and missed opportunities. This presentation presents the results of the CRC-SI “Alignment Study”; an inventory of these initiatives, gaps and overlaps and research opportunities that arise.
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Spatial data supply chains in Australia and New Zealand
1. SPATIAL DATA SUPPLY CHAINS
IN AUSTRALIA & NEW ZEALAND
Overlaps, Gaps and
Opportunities
Maurits van der Vlugt
Spatial Information Strategist
2. OVERVIEW
Problem Statement (“Why this Project?”)
Spatial Data Supply Chains (“Why do you
Care?”)
Project Approach (“How did we do it?”)
Outcomes (“What did we find?”)
Next Steps (“What now?”)
4. CRITICAL ENABLER
Spatial Data Supply
Chains (SDSC)
Multi Source
Consistent, Reliable
Automated, Flexible,
Distributed
E.g. PSMA’s G-NAF,
BoM’s GeoFabric
Source: CRC-SI
5.
6. WHAT MAKES A GOOD SDSC?
Single Point of Truth;
Continuously updatable from multiple
sources;
“Supply Views”;
Version Management;
Automated Update and Distribution;
Automated Input (sensors or VGI).
7. HOWEVER…
Myriad of initiatives
In relative isolation
Re-inventing wheels
Duplicating Effort
Can we improve this?
8. SDSC ALIGNMENT STUDY
Identify SDSC initiatives in ANZ
Comparative Analysis
Gaps and Overlaps
Re-usable components?
Joint R&D and investment opportunities?
9. APPROACH
1. Quick Scan of 2. Alignment 3. Collaborative
relevant Study Demo Project
initiatives
• Review ANZ • Validation of • Public-Private
Initiatives Ph1 outcomes • Working
• Analysis • SDSC demonstrator
Framework Reference • Contributions to
• Review & Architecture standards
Analyse • Detailed processes
• Scientific Analysis • IP development
Literature • Recommendati
Review ons for
• Identify Alignment and
Strategic Collaboration
Partners & • Input to
Opportunities Research
• Proposal for Ph Agenda
2 • Proposal for
Demo Projects
10. OUTCOMES
37 Project approached, 32 Responses
Largely Government
Only 7 Automate entire supply chain
50% in pre-production stages
Only 6 out of 32 having a full, long term
sustainable governance framework in place
11. # of
Business DriverDRIVERS
BUSINESS Projects
(N=32)
Maintain a consistent, authoritative
dataset to support evidence based 10
decision making
Meet statutory obligations 9
Improve data access & sharing across
8
organisations
Improve efficiency & reduce
5
duplication
Publish data for scientific research 4
Improve value & service to
3
12. # of
Audience Projects
(N=32)
Government agencies 25
Public organisations and business
14
groups
Scientific Community 10
General Public 6
14. SYSTEM MATURITY
In production, with
2 Governance Framework
6
In production
8
Prototype/trial
Under development
10
6 Other
15. ‘BEST OF BREED’ PROJECTS
Automated
Publish
Maintain
Extract
Mature
In production
16. SHORTLIST FOR PH2 ANALYSIS
LINZ Data Service
Maori Land Geographic Information
System
PSMA Systems
SISS - Spatial Information Services
Stack
SLIP Enabler
The Australian Hydrological
Geospatial Fabric (Geofabric)
VSDL - Victorian Spatial Data
Library
17. CONCLUSIONS
Status of SDSC:
Infancy
Supply Driven
Developed in Isolation
Capability Gaps
Automation
Maturity
Standards
Plenty of Opportunity for Collaboration
re-use of components
Joint investment and R&D
18. NEXT STEPS
Integrate QLD & NSW in
Ph 1 Analysis
Ph 2 : from early 2012
Detailed analysis of shortlisted
projects
Reference Architecture
R&D Agenda
Scope collaborative demo
project
19. THANK YOU – QUESTIONS?
Acknowledgements
CRC-SI (Kylie Armstrong, Mary Sue Severn)
Project Participants
More Information
Http://www.crcsi.com.au/Research/Program-3/SDI-Alignment-Study
Maurits.vandervlugt@mercuryps.com.au
Hinweis der Redaktion
Give examples (road DB):Jurisdictions collect & maintain road dataSubmit updated road data set every 6 months to central custodian. With agreed metadata and attribute schemas, in GML format. Central Custodian validates complianceDataset and metadata converted into common schema and DB format for maintenance DBData is integrated with national dataset, coordinate transformation and attribute harmonisation to ensure national consistency. Production DB (optimised for maintenance) is continually maintained, versioned and replicated to delivery DB (optimised for delivery, may be outside Firewall)'On demand' generation of regional roadmaps, road datasets with specific attributes for intelligent transport monitoring, and 4WD track mapsroad datasets clipped for regions & converted to shapefiles. Downloadable via secure FTP. 4WD tracks published as Web Service.Logistics company subscribes and regularly downloads national road dataset for route planning
will have a single point of truth where relevant data elements can be cached, or value added data can be maintained;are continuously updatable from multiple sources;support the supply of the same information in many different forms or “supply views” (format and structure) to support the many tools that are used,support multiple versions of these products to support traceability and transparency, have automated update and distribution, andenable automated input from e.g. sensors or volunteered geographic information (VGI).
So: what is the state of SDSCs in Australia/New Zealand?
<10% service & Value oriented, rest mainly ‘supply push’It is noteworthy that the primary business drivers seem internal or institutional drivers, while a ‘pull’ driver such as improving value to stakeholders comes second last.
The strong focus on a government audience (25 of 32 projects) is consistent with the identified business drivers.By Gov’t agencies, for Gov’t agencies
This question addresses the key technical capabilities underpinning SDSCs, as listed in section 3.2.Not entirely surprisingly, almost all projects have a Single Point of Truth data store, and facilitate Continuous Updates. Other key ingredients of spatial data supply chains are less frequently present, while sensor- and VGI input capabilities exist in only one third of the projects.
As noted before (Section 4.3.5), mature, automated spatial data supply chains are still in their infancy in Australia and New Zealand. Only a minority of steps in the reviewed supply chains are fully automated (10-20%), and only 7 projects (semi-) automate the entire supply chain.Among the reviewed projects, the capability for automated publishing and integration are the least developed, markedly less than the other supply chain steps.