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GECAFS-Decision Support Systems. Questions, SCIENCE Outputs Hypotheses. Science-based Toolkit. DSS. Policies, Decision, Decisions Processes. Society Policy Makers Data, Processes Questions, Needs. DSS. Questions, SCIENCE Outputs Hypotheses. Science-based Toolkit.

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slide2
Questions, SCIENCE Outputs

Hypotheses

Science-based Toolkit

DSS

Policies, Decision,

Decisions Processes

Society Policy Makers Data,

Processes

Questions,

Needs

DSS

slide3
Questions, SCIENCE Outputs

Hypotheses

Science-based Toolkit

DSS

slide4
Policies, Decision,

Decisions Processes

Society Policy Makers Data,

Processes

Questions,

Needs

DSS

slide5
Questions, SCIENCE Outputs

Hypotheses

Science-based Toolkit

Policies, Decision,

Decisions Processes

Society Policy Makers Data,

Processes

Questions,

Needs

DSS

slide6
Questions, SCIENCE Outputs

Hypotheses

Science-based Toolkit

DSS

Policies, Decision,

Decisions Processes

Society Policy Makers Data,

Processes

Questions,

Needs

DSS

initial ideas designs for decision support systems qnd in the gecafs project

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

Greg KikerAgricultural and Biological Engineering Dept.P.O. Box 110570Gainesville, FL 32611-0570Phone: (352) 392-1864 ext 291Email: [email protected]

qnd model and multi criteria decision analysis mcda
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 model what is it
QnD Model: What is it?
  • 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 main sections
subComponent

subProcess

QnD Model: Main Sections

“Simulation Engine”

“Game View”

  • Developer’s point of contact
  • Creates information
  • Objects: Components, Processes and Data
  • Calculation for selected time step
  • 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
slide11
Actors
  • 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

subComponent

GameDriver.java

ModelCreator.java

  • 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…

PrimaryGameFrame.java

subProcess

“Game View”

“Simulation Engine”

QnD Java Source Code

qnd how do you use it
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
qnd development methodology
Genesis Session

Prototype QnD Game View and Simulation Engine

  • 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
  • Rough estimate of components, processes and data
  • Simple information
  • Deployed in limited circulation for calibration/reality checks

Iterative Sessions 1…n

Deployed QnD Model

  • 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
  • Player/Developer reviewed components, processes and data
  • More relevant information
  • Brainstorm about desired management options, relevant information and socio-economic realities
QnD: Development Methodology
slide14
2. ASSIMILATING:

What can we do?

What are the themes which

Constitute potential areas

For improvement or

transformation?

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 activities

do we need to design to achieve

the transformation we believe

could lead to improvement

of the situation?

4. ACCOMMMODATING:

What does it mean?

How do we use our model

system to establish debate

amongst stakeholders, to

decide what is feasible, and

to achieve the change?

Abstract world

Real world

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

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