spatial data infrastructure frameworks to support decision making for sustainable development...
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Spatial Data Infrastructure Spatial Data Infrastructure Frameworks to Support Frameworks to Support
Decision Making for Sustainable Decision Making for Sustainable DevelopmentDevelopment
Mary-Ellen FeeneyAbbas Rajabifard
Ian Williamson
Department of Geomatics,University of Melbourne, Australia
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OverviewOverview
• Decision making for Sustainable Development
• SDI Concept and Decision making
• Brief Introduction to the concept of DSS
• The DSS & SDI context
• Impacts for Developing SDIs to support DSS
• Exploratory Case Studies of different SDI
Models for DSS support - regional Australia
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Decision Making for Sustainable Decision Making for Sustainable DevelopmentDevelopment
Decision Support Systems (multicriteria datainformationdecision alternatives)
Changing Humankind-land relationships
Sustainable Development Objectives
Multicriteria Decision-Making(social, economic, environmental …)
Spatial Data
Spatial Data Infrastructures
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Decision Making for Sustainable Decision Making for Sustainable DevelopmentDevelopment
Economy
EcologySociety
Ecology
Economy
Society
From Bellamy 2000
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The SDI concept & Decision MakingThe SDI concept & Decision Making
The principle objective for developing SDI is
to achieve better outcomes from spatially
related economic, social and environmental
decision-making.
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Components of SDI
PeoplePeople
Access Network
Policy
Standards
DataData
Dynamic
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Components of SDI
PeoplePeople
Access Network
Policy
Standards
DataData
Dynamic
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How do SDIs support Decision How do SDIs support Decision Making?Making?
• Through facilitating the provision of standardised, interoperable datasets and information that are accessible, useable, exchangeable
• But, are data and information enough to support decision making?
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The Nature of Decision Making?The Nature of Decision Making?
Decision Space Solution Space
Spatial Data Information
2
Processing
3
1
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Decision Support Systems (DSS)
• Generally computer-based information systems
• Support decision-making activities in the
exercise of judgement
• Do not actually make the decision
• Characterised by integrated modeling and
analysis facilities, including …
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Decision Support Systems (DSS)
• tools for obtaining, analysing & presenting information
• modeling & simulation tools
• multi-criteria modeling for selecting from a set ofdefined alternatives
• Expert systems for rule-based decision making in defined situations
• Life-cycle analysis & green design tools.
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Decision Support Systems
• Aid rather than replace decision makers
• Can restrict or expand decision options
• May facilitate user-directed change
• Can be for specific decision environments/ generic tool
• Generally combinations of ‘SYSTEM’ tools
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Decision Support Systems vs Tools = complexity ie. = complexity ie.
• number of criteria;
• incorporate preferences & values;
• number of decision-makers
decision-making model;
• support existing data & ‘gaps in data’;
• generation of alternative (prioritised) solutions
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DSS & SDI : CONTEXT
• Why• What• How • When
Relevance and Significance ?
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DSS & SDI : CONTEXT
• Capability to validate data quality,
• Process data quantity quickly & effectively &
• Model new and more variable decision making
Why
What•Questions are we trying to answer
- sustainable development objectives
• Data do we require to answer them
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DSS & SDI : CONTEXTHow• To ask the necessary Questions
• To model data to achieve satisfactory answers
• To better manage spatial information towards Sustainable Development Objectives
When
• Need to incorporate time-frames into decision making processes
e.g.. multiple stages, time-frames for criteria
• Need for temporal data modeling developments (time series data analyses)
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Developing SDIs to support DSS ...•understanding of other’s data needs/resources
•awareness of data availability, quality & limitations
•Improved data by publishing & standards coordination.
•Increased confidence in data use - consistency
•Precipitant for collaborative data-sharing agreements.
data availability, collection, storage, access,
•users with differing expertise in the GI use
•incentives to integrate social, environmental, economic & spatial data
• transfer of R&D to stakeholders
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Classification of Different SDI Models
1. motivation for development
2. expected outcomes
3. management
4. participants
5. measures of progress
6. political/administrative function
7. time frame-committment
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Herbert River Information Centre- QLD
1. Sharing/modification existing datasets, collection of
key additional datasets
2. integrated databases of region
3. unincorporated partnerships between 11 agencies
4. private & public sector (3 tiers)
5. Completion of the Mapping Project on time
6. Regional (Sub-State)
7. fixed project period - 3 years
Developing SDI using a Product Model:
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Herbert River Information Centre- QLD
1. Resource that supports spatial decision-making &
planning for natural resource management
2. Resource Information Centre- GIS facilities, consultation,
project management, data access & coordination
3. HRIC Management - Independednt of partners,
4. 6 partners - private & public sector (3 tiers)
5. Financial & Objective Sustainability - 3 years-10
6. Regional (Sub-State)
7. 10 year + (period after which partnerships reviewed)
Developing SDI using a Process Model:
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Integrated Information Management System - NSW & QLDDeveloping SDI using a Process Model:
1. Facilitate discovery & use of resources for Catchment
Management Decision-making
2. Information Management Systems incorporating access
to data & Modeling Systems
3. University & Government Partners, Govt. Funding
4. 3 partners - 2 State public sector, University QLD
5. Establishment, Prototype testing & Feedback
6. Regional (Sub-State) particularly Catchment-oriented
7. Dependent on Community & Agency Uptake
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Conclusions
Process Models for SDI development:
• offer access networks to data
• forums of consultation (web-based or service centres)
• DSS to support the application & modification of data
Product Models for SDI development:
• improved data availability, coordinated collection, cross-
agency data collaboration
• integrated data products with defined quality &
maintenance time-frames
in decision support for sustainable development...
vs
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AcknowledgementsThese findings are from exploratory case studies in ongoing PhD
research. They provide a broad-brush review of initiatives central to
State SDI developments in Australia. They result from pilot-work in
selecting & testing criteria for the comparison of SDI & DSS
developments that is undergoing continuing development &
refinement.
•Land Victoria of the Victorian Government•Land & Property Information Centre of NSW
•Department of Technology & Management NSW•Australian Research Council
•Spatial Data Infrastructure Research Group, Department of Geomatics, University of Melbourne
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International Symposium on SDIInternational Symposium on SDI
19-20 November, 2001
University of Melbourne, Australia
http://www.sli.unimelb.edu.au/SDI
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Symposium PurposeSymposium Purpose
• To explore the institutional and technical issues influencing the development of SDIs.
• To examine and debate the directions of development of SDIs in the future.
Web-site http://www.sli.unimelb.edu.au/SDI
Email [email protected]
Registration Deadline: October 31