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OASIS - Organizational Adaptive Sustainability Intelligence System

Analyze organizational sustainability through the lens of ecosystem theory, using Ulanowicz's information-theoretic framework and the OASIS health assessment model.

Python Streamlit License

Overview

OASIS treats organizations as living ecosystems — networks of information, resource, and communication flows between departments, teams, or entities. By applying Robert Ulanowicz's information-theoretic measures from network ecology, it quantifies organizational health across five dimensions: Open, Autonomous, Symbiotic, Intelligent, and Sustainable.

The system provides:

  • Network flow analysis using Ulanowicz metrics (TST, AMI, Ascendency, Robustness)
  • OASIS health assessment with five-dimension scoring and actionable recommendations
  • Professional PDF reports structured to Big Four audit-firm standards
  • Interactive dark-mode dashboard with nature/ecosystem visual theme
  • Real-world dataset library (airports, supply chains, energy grids, trade networks)
  • Synthetic data generation for testing and research

What's New in v2.0.0

  • Dark mode UI — Full nature/ecosystem color palette (forest green, gold, teal) across all components
  • Professional PDF reports — Cover page, table of contents, embedded charts, headers/footers via reportlab
  • Publication-quality report narratives — Restructured to Big Four audit-firm standards with narrative findings
  • Interactive documentation system — In-app tooltips and reference documentation for all metrics
  • OASIS health model — Five-dimension organizational health scoring with traffic-light indicators
  • SQLite metrics database — Precomputed metrics for faster analysis of saved networks
  • HuggingFace dataset discovery — AI agent for finding relevant network datasets
  • Ecosystem sample datasets — US airports, Bitcoin transactions, pharma, manufacturing networks

Quick Start

# Clone the repository
git clone https://github.com/maxdolphin/OASIS.git
cd OASIS

# Install dependencies
pip install -r docs/requirements.txt

# Launch the app
streamlit run app.py

Open your browser to http://localhost:8501

Python API

import numpy as np
from src.ulanowicz_calculator import UlanowiczCalculator

flow_matrix = np.array([
    [0, 8, 6, 4],
    [5, 0, 7, 3],
    [4, 6, 0, 5],
    [3, 4, 5, 0]
])
departments = ['Sales', 'Marketing', 'Operations', 'Support']

calc = UlanowiczCalculator(flow_matrix, departments)
metrics = calc.get_extended_metrics()

print(f"Robustness: {metrics['robustness']:.3f}")
print(f"Viable: {'YES' if metrics['is_viable'] else 'NO'}")

Key Features

Ulanowicz Metrics

  • Total System Throughput (TST), Average Mutual Information (AMI)
  • Ascendency (A), Development Capacity (C), Overhead (Phi)
  • Robustness, Window of Viability analysis
  • Flow Diversity, Redundancy, Regenerative Capacity
  • Trophic Depth, Network Efficiency, Structural Information

OASIS Health Assessment

Each organization is scored across five ecosystem-inspired dimensions:

  • Open — Connectivity and exchange capacity
  • Autonomous — Self-governance and adaptive capacity
  • Symbiotic — Mutualistic relationships and cooperation
  • Intelligent — Information processing and flow efficiency
  • Sustainable — Long-term viability and resilience

Visualizations

  • Robustness curve with Window of Viability
  • Sankey flow diagrams and network heatmaps
  • OASIS radar chart and dimension gauges
  • Network topology graphs
  • All charts interactive (Plotly) with dark theme

Professional Reporting

  • PDF export with cover page, ToC, and embedded charts
  • Narrative findings structured per Big Four audit conventions
  • OASIS dimension assessments with framework alignment (ESRS, GRI, TCFD)
  • Prioritized recommendations (Immediate / Short-term / Medium-term)

Data Sources

  • Upload your own data (JSON or CSV flow matrices)
  • Generate synthetic organizations with configurable parameters
  • Built-in ecosystem samples: US airports, Bitcoin, pharma, manufacturing
  • Real-world datasets: energy grids, supply chains, financial networks, trade flows
  • HuggingFace dataset discovery agent

Project Structure

OASIS/
├── app.py                          # Streamlit web application
├── .streamlit/config.toml          # Dark theme configuration
├── src/
│   ├── ulanowicz_calculator.py     # Core Ulanowicz metrics
│   ├── oasis_calculator.py         # OASIS health assessment
│   ├── oasis_visualizer.py         # OASIS charts and gauges
│   ├── oasis_report.py             # OASIS narrative report
│   ├── visualizer.py               # Network visualizations
│   ├── network_generator.py        # Synthetic data generation
│   ├── pdf_generator.py            # Professional PDF export
│   ├── publication_report.py       # Publication-quality narratives
│   ├── docs_registry.py            # Documentation content registry
│   ├── docs_ui.py                  # In-app documentation UI
│   ├── database/                   # SQLite metrics storage
│   └── services/                   # Validation and metrics services
├── data/
│   ├── ecosystem_samples/          # Real-world network datasets
│   ├── user_saved_networks/        # Saved analysis networks
│   └── synthetic_organizations/    # Generated test data
├── papers/                         # Scientific references
├── docs/                           # Documentation and requirements
└── tests/                          # Test suite

Theoretical Foundation

Based on the work of:

  • Robert E. Ulanowicz — Ecosystem sustainability theory, Ascendency concept, Window of Viability
  • Brian D. Fath & Robert E. Ulanowicz — "Measuring Regenerative Economics: 10 principles and measures undergirding systemic economic health" (2019)
  • Bernard C. Patten — Network environ analysis, indirect effects in ecosystems
  • Stuart Kauffman — Self-organization, edge of chaos in complex systems

Key Concepts

  • Window of Viability: Sustainable systems operate between 20-60% efficiency ratio (A/C)
  • Robustness: Optimal balance at approximately 37% efficiency, following R = -a * log(a)
  • Ascendency vs Overhead: The tension between organized efficiency and adaptive reserve capacity

Data Formats

JSON

{
  "organization": "My Company",
  "nodes": ["Sales", "Marketing", "Operations", "Support"],
  "flows": [
    [0.0, 8.0, 6.0, 4.0],
    [5.0, 0.0, 7.0, 3.0],
    [4.0, 6.0, 0.0, 5.0],
    [3.0, 4.0, 5.0, 0.0]
  ]
}

CSV

,Sales,Marketing,Operations,Support
Sales,0.0,8.0,6.0,4.0
Marketing,5.0,0.0,7.0,3.0
Operations,4.0,6.0,0.0,5.0
Support,3.0,4.0,5.0,0.0

Requirements

  • Python 3.8+
  • 8GB RAM recommended for large networks

Install all dependencies:

pip install -r docs/requirements.txt

Contributing

Contributions welcome — report bugs, suggest features, improve documentation, or add analysis methods via GitHub issues and pull requests.

License

MIT License — see LICENSE for details.

Acknowledgments

  • Robert E. Ulanowicz for the foundational ecosystem theory
  • Brian D. Fath for extending the framework to regenerative economics
  • Streamlit for the web framework
  • Plotly for interactive visualizations

git clone https://github.com/maxdolphin/OASIS.git
cd OASIS && streamlit run app.py

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Organizational sustainability analysis using Ulanowicz ecosystem theory and the OASIS health assessment model

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