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Spatial Data Infrastructure Frameworks to Support Decision Making for Sustainable Development Decision Making for Sustainable Development Mary-Ellen Feeney.

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Presentation on theme: "Spatial Data Infrastructure Frameworks to Support Decision Making for Sustainable Development Decision Making for Sustainable Development Mary-Ellen Feeney."— Presentation transcript:

1 Spatial Data Infrastructure Frameworks to Support Decision Making for Sustainable Development Decision Making for Sustainable Development Mary-Ellen Feeney Abbas Rajabifard Ian Williamson Department of Geomatics, University of Melbourne, Australia

2 Overview 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

3 Decision Making for Sustainable Development Decision Support Systems (multicriteria data  information  decision alternatives) Changing Humankind-land relationships Sustainable Development Objectives Multicriteria Decision-Making (social, economic, environmental …) Spatial Data Spatial Data Infrastructures

4 Decision Making for Sustainable Development Economy Ecology Society Ecology Economy Society From Bellamy 2000

5 The SDI concept & Decision Making The principle objective for developing SDI is to achieve better outcomes from spatially related economic, social and environmental decision-making.

6 Components of SDI People Access Network Policy Standards Data Dynamic

7 Components of SDI People Access Network Policy Standards Data Dynamic

8 How do SDIs support Decision 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?

9 The Nature of Decision Making? Decision SpaceSolution Space Spatial DataInformation 2 Processing 3 1

10 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 …

11 Decision Support Systems (DSS) tools for obtaining, analysing & presenting information modeling & simulation tools multi-criteria modeling for selecting from a set of defined alternatives Expert systems for rule-based decision making in defined situations Life-cycle analysis & green design tools.

12 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

13 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

14 DSS & SDI : CONTEXT Why What How When Relevance and Significance ?

15 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

16 DSS & SDI : CONTEXT How 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)

17 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

18 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

19 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:

20 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 Regional (Sub-State) year + (period after which partnerships reviewed) Developing SDI using a Process Model:

21 Integrated Information Management System - NSW & QLD Developing 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

22 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

23 Acknowledgements These 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

24 International Symposium on SDI November, 2001 University of Melbourne, Australia

25 Symposium 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 Registration Deadline: October 31


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