gecafs-decision support systems

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GECAFS-Decision Support Systems. Questions,SCIENCEOutputs Hypotheses. Science-based Toolkit. DSS. Policies,Decision, DecisionsProcesses. SocietyPolicy MakersData, Processes Questions, Needs. DSS. Questions,SCIENCEOutputs Hypotheses. Science-based Toolkit. - PowerPoint PPT Presentation

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GECAFS-DecisionSupport Systems

DSS

Questions, SCIENCE OutputsHypotheses

Science-based Toolkit

Society Policy Makers Data,Processes

Questions,Needs

Policies, Decision,Decisions Processes

DSS

DSS

Questions, SCIENCE OutputsHypotheses

Science-based Toolkit

DSS

Society Policy Makers Data,Processes

Questions,Needs

Policies, Decision,Decisions Processes

DSS

Questions, SCIENCE OutputsHypotheses

Science-based Toolkit

Society Policy Makers Data,Processes

Questions,Needs

Policies, Decision,Decisions Processes

DSS

Questions, SCIENCE OutputsHypotheses

Science-based Toolkit

Society Policy Makers Data,Processes

Questions,Needs

Policies, Decision,Decisions Processes

DSS

Initial Ideas/Designs for Decision Support Systems: QnD in the GECAFS project

Greg KikerAgricultural and Biological Engineering Dept.

P.O. Box 110570Gainesville, FL 32611-0570

Phone: (352) 392-1864 ext 291Email: gkiker@ufl.edu

QnD Model and Multi-Criteria Decision Analysis (MCDA)

• QnD is a configurable decision support/scenario exploration program

• Currently we are working to combine QnD results with more available commercial MCDA software

• QnD + MCDA should allow both exploration of time-based, “tactical” management versus more policy-oriented, “strategic” trade-off analysis

• QnD™ – “Questions and Decisions™” or “Quick n Dirty”

• A fully integrated Graphic User Interface (GUI) with a flexible model engine

• One model - Many ecosystems– Java code / XML inputs / Open Source code

– “Uses Mainstream Technology”

• Java-based deployment in web browsers

• “Fast Deployment” (weeks/months)

• Spatial simulation with GIS linkage

• Multiple time steps

• Multiple maps/graphs/files for output variables

QnD Model: What is it?

subComponent

subProcess

“Simulation Engine” “Game View” User/Player’s point of contact

Communicates information

“Widgets”: Maps, Charts, Warning Lights, Text, Sliders, Icons, Buttons

User choices – management settings, simulate fast or slow time step, reset

Developer’s point of contact

Creates information

Objects: Components, Processes and Data

Calculation for selected time step

QnD Model: Main Sections

subComponent

subProcess

“Simulation Engine”

“Game View” Actors

QnD Java Source Code

GameDriver.java ModelCreator.java

PrimaryGameFrame.java

Players: Interact mostly with the game view.

• Explore management responses, adaptive opportunities, trade-offs for different scenarios.

• Provide reality checks

• Have some interest in the engine structure in their area of interest

• Provide ideas and directions for further iterations

Developers: Interact mostly with the engine.

• Design and implement engine/game view through XML files.

• Provide formal calibration/validations

• Implement ideas and directions of Players

• Have some interest in the model code

Coders: Interact mostly with the QnD source code.

• Develop java code to expand engine and game view utility

• Create new programming code for ideas from Players and Developers…

QnD: How Do You Use It?

• We have developed a Development ↔ Iteration methodology

• Exploring management/policy options under various scenarios– Explore management reactions/strategies– Teaching/Classroom/Learning sessions– Use expert opinion, “other” model results/relationships

• Use as a traditional model– Integrate field-measured results– Create predictions under various conditions

• Talk about the system, goals, desires

• Explore current management options

• Gather initial maps/data

• Brainstorm about desired management options, relevant information and socio-economic realities

Genesis Session

Prototype QnD Game View and Simulation Engine

• Rough estimate of components, processes and data

• Simple information

• Deployed in limited circulation for calibration/reality checks

Iterative Sessions 1…n

• Refine goals, objectives• Explore current and possible management options• Calibrate/Validate engine performance• Revise Game View for relevant management information • Make changes concerning management options, relevant information and socio-economic factors

Deployed QnD Model

• Player/Developer reviewed components, processes and data

• More relevant information

• Brainstorm about desired management options, relevant information and socio-economic realities

QnD: Development Methodology

2. ASSIMILATING:What can we do?

What are the themes whichConstitute potential areas

For improvement or transformation?

4. ACCOMMMODATING:What does it mean?

How do we use our modelsystem to establish debateamongst stakeholders, to

decide what is feasible, andto achieve the change?

1. DIVERGING:What is there?

Build as rich a picture as possible of the problem

situation, through conversation.

3. CONVERGING:What is important?

What system of human activitiesdo we need to design to achievethe transformation we believe

could lead to improvement of the situation?

Abstract world Real world

Soft systems considerations represented in terms of Kolb’s Knowledge Forms (after Bawden et al., 1984).

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