Project Overview
Status Summary
ISA Data Status
Network Status
Analysis Status
Project History
PIMS Project Definition
Define your project scope, objectives, and context.
Project Information
System Scope
Current Status
PIMS Detailed Stakeholder Analysis
Comprehensive stakeholder mapping and influence analysis.
Stakeholder Identification
Identify All Stakeholders Relevant To Your Marine
Add New Stakeholder
Stakeholder Register
Stakeholder Power Interest Grid
Visualize Stakeholders Based On Their Powerinfluen
Power Interest Grid Classification
- High Power High Interest Key Players Engage Closely And Make Greatest Efforts To Satisfy
- High Power Low Interest Keep Satisfied Keep Satisfied But Avoid Excessive Communication
- Low Power High Interest Keep Informed Keep Informed And Talk To Regarding Their Interests
- Low Power Low Interest Monitor Monitor With Minimum Effort
Grid Summary
Clicked Stakeholder
Stakeholder Engagement Strategy
Plan How To Engage With Each Stakeholder Group Bas
Define Engagement Activities
Engagement Activities Log
Stakeholder Communication And Impact Management
Plan And Track Communications With Stakeholders To
Add Communication Item
Communications Log
Stakeholder Analysis Summary
Stakeholder Statistics
Engagement Coverage
Stakeholder Types Distribution
Sector Distribution
Export Stakeholder Data
Download Stakeholder Information For Reporting And
PIMS Resource Management
Document and manage project resources and budget.
Resource management to be implemented
Risk management to be implemented
PIMS Data Management
Plan and manage project data collection and storage.
Data management functionality to be implemented
PIMS Monitoring & Evaluation
Define indicators and evaluation framework for project success.
Evaluation functionality to be implemented
AI-Assisted SES Creation
Let me guide you step-by-step through building your DAPSI(W)R(M) model.
Context Wizard
SES Network
Details
Layout:
Edit Mode
Highlight:
Automatic Loop Detection
Identify all feedback loops in your DAPSI(W)R(M) system.
Detection Parameters
Detection Summary
Processing Status
Detected Loops
Reinforcing vs Balancing
Classify loops based on polarity and understand their system behavior.
Reinforcing Loops
Amplify change - can create virtuous or vicious cycles.
Balancing Loops
Counteract change - seek equilibrium or stability.
Loop Type Distribution
Detailed Loop Information
Select Loop
Loop Properties
Loop Visualization
Loop Narrative
Identify Key Drivers
Analyze which loops have the most influence on system behavior.
Dominance Metrics
Loops are ranked by length, centrality, and element importance.
Loop Strength Analysis
Element Participation
How many loops each element appears in:
Export Analysis
Download Options
Export loop detection results for documentation and reporting.
Loop Summary Statistics
Analysis Settings
About Leverage Points
Leverage points are nodes that have the highest potential for system-wide impact based on:
- Betweenness: Control over information flow
- Eigenvector: Connection to other important nodes
- PageRank: Overall importance in the network
Time Series Data
Analysis Options
Summary Statistics
Temporal Pattern Detection
Enable 'Detect Patterns' to analyze temporal dynamics.
Compare Multiple Scenarios
Upload or create multiple time series to compare different scenarios.
Feature coming soon...
Current Network Status
Original Network Summary
Simplified Network Summary
Simplification Methods
Select Methods
Choose one or more simplification techniques:
Single-Input-Single-Output (SISO) Variables
Identifies nodes with exactly one incoming and one outgoing connection. Creates a 'bridge' edge that preserves the causal relationship while removing the intermediate node.
- Reduces chains of simple relationships
- Preserves polarity through the chain
- Maintains overall network structure
Exogenous Variables (External Drivers)
Identifies nodes with outgoing connections but no incoming connections. These are external drivers that influence the system but are not influenced by it.
- Focuses on endogenous dynamics
- Useful for understanding internal feedback
- Removes nodes with outdegree > 0, indegree = 0
Connection Strength Filtering
Removes connections below a specified strength threshold to focus on dominant causal relationships.
- Highlights dominant relationships
- Reduces visual clutter
- May disconnect some nodes
Centrality-Based Filtering
Removes peripheral nodes with low importance based on network centrality metrics.
- Focuses on structurally important nodes
- Adjustable threshold for control
- Different metrics highlight different aspects
DAPSI(W)R(M) Element Selection
Focus on specific components of the SES framework.
Export Simplified Network
Network Visualization
Original Network
Simplified Network
Simplification Statistics
Removed Nodes
Removed Edges
Applied Methods
Impact Summary
About Simplification
Why Simplify Networks?
Complex social-ecological systems often contain hundreds of variables and connections. While comprehensive models capture full system complexity, simplified models offer:
- Better Communication: Easier to explain to stakeholders and decision-makers
- Focused Analysis: Concentrate on key drivers and feedback loops
- Computational Efficiency: Faster analysis and visualization
- Pattern Recognition: Clearer identification of core system dynamics
- Scenario Testing: More manageable models for policy simulation
Simplification Best Practices
- Preserve Feedback Loops: Ensure key reinforcing and balancing loops remain intact
- Maintain Causality: Keep polarity and direction of relationships accurate
- Document Changes: Track what was removed and why
- Validate with Experts: Confirm simplified model still represents reality
- Use Multiple Methods: Combine techniques for comprehensive simplification
- Iterate: Apply methods gradually and review results at each step
Method Recommendations by Goal
- Focus on Internal Dynamics: Remove exogenous variables
- Reduce Visual Complexity: Filter weak connections + SISO encapsulation
- Highlight Key Leverage Points: Low-centrality node removal with PageRank
- Sector-Specific Analysis: Element type filtering
- Maximum Simplification: Combine all methods with careful thresholds
Response Measures (R & M)
Identify management interventions and policy responses to address system challenges.
Management Measures and Policy Interventions
Document responses to address pressures, activities, and drivers in your system.
Add Response Measure
Response Measures Register
Response Measure Impact Matrix
Assess which measures address which problems in your system.
Create Impact Linkage
Impact Matrix
Visual Impact Matrix
Response Measure Prioritization
Evaluate and rank measures based on effectiveness, feasibility, and cost.
Prioritization Criteria Weighting
Priority Ranking
Prioritized Response Measures
Effectiveness vs. Feasibility
Cost vs. Expected Impact
Response Implementation Roadmap
Add Implementation Milestone
Implementation Timeline
Gantt Chart (Simplified)
Export Response Analysis
Download Response Documentation
Scenario Builder Title
Scenario Builder Description
Model Validation
Track validation activities and model confidence assessment.
Status Basic validation tracking available in ISA Exercise 12. Advanced features coming soon.
Required Excel Format
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Two sheets required:
- Elements - Contains all nodes/elements in your SES
- Connections - Contains all relationships/edges between elements
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Elements sheet columns:
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Label- Name of the element (required) -
type- Element type: Driver, Activity, Pressure, Marine Process and Function, Ecosystem Service, Good and Benefit, Response, or Measure (required)
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Connections sheet columns:
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From- Source element label (required) -
To- Target element label (required) -
Label- Connection polarity: + or - (required) -
Strength- Optional: Weak/Medium/Strong -
Confidence- Optional: 1-5 scale
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Load Pre-built SES Models
Select from existing SES models organized by Demonstration Area to quickly start your analysis.
Click to scan SESModels directory
Prerequisites Status
Report Configuration
Generate Report
Select the report format you wish to generate: