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

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

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

Decision Making for Sustainable Decision Making for Sustainable DevelopmentDevelopment

Economy

EcologySociety

Ecology

Economy

Society

From Bellamy 2000

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.

Components of SDI

PeoplePeople

Access Network

Policy

Standards

DataData

Dynamic

Components of SDI

PeoplePeople

Access Network

Policy

Standards

DataData

Dynamic

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?

The Nature of Decision Making?The Nature of Decision Making?

Decision Space Solution Space

Spatial Data Information

2

Processing

3

1

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 …

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.

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

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

DSS & SDI : CONTEXT

• Why• What• How • When

Relevance and Significance ?

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

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)

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

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

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:

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:

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

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

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

International Symposium on SDIInternational Symposium on SDI

19-20 November, 2001

University of Melbourne, Australia

http://www.sli.unimelb.edu.au/SDI

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 sdi@sunrise.sli.unimelb.edu.au

Registration Deadline: October 31