Initializing...

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

Rule-Based AI

Details

Visualisation Controls

Layout:

Highlight:

Automatic Loop Detection

Identify all feedback loops in your DAPSI(W)R(M) system.

Detection Parameters
Note: Lower values prevent hanging on complex networks

Detection Summary

                              
Processing Status

Detected Loops

Reinforcing vs. Balancing Loops

Classify loops based on polarity and understand their system behavior.

Reinforcing Loops (R)

Amplify change - can create virtuous or vicious cycles.


Balancing Loops (B)

Counteract change - seek equilibrium or stability.



Loop Type Distribution

Detailed Loop Information

Select Loop

Loop Properties

                            
Loop Visualization
Loop Narrative

Identify Key System 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 Loop 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



Node sizes reflect composite leverage scores. Larger nodes = higher leverage.

Time Series Data


Analysis Options

Time Series

Summary Statistics

                        
Pattern Analysis

Temporal Pattern Detection

Enable 'Detect Patterns' to analyze temporal dynamics.

Data

Download Data
Scenario Comparison

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 to Apply

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.



Save Simplification Warning
Export Simplified Network

Restore Original Warning

Network Visualization Comparison


Original Network

Simplified Network


Simplification Statistics



Removed Nodes

Removed Edges


Applied Simplification Methods


                                

Impact Summary

About Model 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

  1. Preserve Feedback Loops: Ensure key reinforcing and balancing loops remain intact
  2. Maintain Causality: Keep polarity and direction of relationships accurate
  3. Document Changes: Track what was removed and why
  4. Validate with Experts: Confirm simplified model still represents reality
  5. Use Multiple Methods: Combine techniques for comprehensive simplification
  6. 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)

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

  • Two sheets required:
    • Elements - Contains all nodes/elements in your SES
    • Connections - Contains all relationships/edges between elements
  • Elements sheet columns:
    • 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)
  • Connections sheet columns:
    • 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

Load Pre-built SES Models

Select from existing SES models organized by Demonstration Area to quickly start your analysis.


Click to scan SESModels directory

Export Data

Download Data

Export Visualizations

Download Visualization

Generate Report


Prerequisites Status

Report Configuration

Generate Report

Select the report format you wish to generate: