Transcript DSS
GECAFS-Decision Support Systems DSS Questions, Hypotheses SCIENCE DSS Policies, Decisions Society Science-based Toolkit Decision, Processes Policy Makers Questions, Needs Outputs Data, Processes DSS Questions, Hypotheses SCIENCE Outputs Science-based Toolkit DSS Policies, Decisions Society Decision, Processes Policy Makers Questions, Needs Data, Processes DSS Questions, Hypotheses SCIENCE Outputs Science-based Toolkit Policies, Decisions Society Decision, Processes Policy Makers Questions, Needs Data, Processes DSS Questions, Hypotheses SCIENCE DSS Policies, Decisions Society Science-based Toolkit Decision, Processes Policy Makers Questions, Needs Outputs Data, Processes Initial Ideas/Designs for Decision Support Systems: QnD in the GECAFS project Greg Kiker Agricultural and Biological Engineering Dept. P.O. Box 110570 Gainesville, FL 32611-0570 Phone: (352) 392-1864 ext 291 Email: [email protected] 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™ – “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 “Simulation Engine” “Game View” Developer’s point of contact User/Player’s point of contact Creates information Communicates information Objects: Components, Processes and Data “Widgets”: Maps, Charts, Warning Lights, Text, Sliders, Icons, Buttons Calculation for selected time step User choices – management settings, simulate fast or slow time step, reset subComponent subProcess “Game View” 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 “Simulation Engine” • Provide ideas and directions for further iterations subComponent Developers: Interact mostly with the engine. • Design and implement engine/game view through XML files. • Provide formal calibration/validations subProcess • Implement ideas and directions of Players • Have some interest in the model code QnD Java Source Code GameDriver.java ModelCreator.java Coders: Interact mostly with the QnD source code. • Develop java code to expand engine and game view utility PrimaryGameFrame.java • 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 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 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: 4. ACCOMMMODATING: What is important? What does it mean? What system of human activities do we need to design to achieve the transformation we believe could lead to improvement of the situation? 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).