Feature: Unified User Interface for OG-Core and OSeMOSYS Integration (OG-CLEWS Framework)

[ayushk687]

Problem statement

Summary

Develop a standardized and user-friendly interface to integrate OG-Core and OSeMOSYS (CLEWS) models, enabling policymakers to perform unified climate–economy analysis within a single workflow.

Currently, OG-Core and OSeMOSYS (CLEWS) operate as separate modeling systems:

❌ No unified interface for combined execution
❌ Manual data transfer between models
❌ Limited accessibility for non-technical policymakers
❌ Difficult to analyze cross-sectoral + macroeconomic impacts together

This fragmentation limits the ability to perform integrated policy simulations across climate, energy, land, water, and macroeconomic systems.

Proposed solution

Build a standardized modelling interface and execution system that:

Connects OG-Core and OSeMOSYS workflows
Provides a unified UI for configuring, running, and visualizing simulations
Automates data exchange between models
Enables reproducible and scalable analysis

Key Features
🔹 Unified Interface
Single dashboard to configure both models
Input forms for economic, climate, and resource parameters
🔹 Shared Execution Engine
Orchestrates sequential/parallel execution of models
Handles data transformation between outputs and inputs
🔹 Visualization Layer
Policy impact dashboards (GDP, emissions, resource usage)
Comparative scenario analysis
🔹 Reproducibility
Config-based runs (YAML/JSON)
Exportable simulation pipelines

Implementation Outline

# Example: Unified execution pipeline

def run_integrated_model(config):
    # Step 1: Run OSeMOSYS (CLEWS)
    clews_output = run_clews(config["clews"])

    # Step 2: Transform output for OG-Core
    og_input = transform_to_ogcore(clews_output)

    # Step 3: Run OG-Core
    og_output = run_ogcore(og_input)

    # Step 4: Aggregate results
    return combine_results(clews_output, og_output)```


### Acceptance criteria

Use Cases
Nationally Determined Contributions (NDCs) planning
Climate adaptation strategies
Fiscal policy analysis under climate constraints
Resource allocation across energy–land–water systems

### Dependencies and constraints

Expected Impact
✅ Enables integrated climate + economic policy analysis
✅ Supports evidence-based policymaking
✅ Improves accessibility for non-technical users
✅ Reduces manual workflow overhead
✅ Scalable deployment across 10+ countries

### Related work checked

Backend: Python (FastAPI / Flask)
Frontend: React / Next.js
Workflow orchestration: Airflow / Prefect
Data handling: Pandas, NumPy
Visualization: Plotly / D3.js

### Proposed track

None

[cloobTech]

Hi @ayushk687 ,

Thanks for opening this issue. I’ve been working on the OG‑Core integration for GSoC. I checked with @SeaCelo about the tech stack, and he confirmed that for now the priority is to get a reliable solution using the existing codebase (Flask + static frontend). My prototype follows those patterns.

If the project later migrates to FastAPI/React, that can be a future enhancement. I’m also comfortable working with those technologies and can adapt the design accordingly. For GSoC, I’ll stick with the current architecture to deliver a working integration. Let me know if there are specific parts of this issue you'd like me to address in that context.