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This monorepo contains the following components:

  1. Data Parser - Parses CML data and metadata CSV files from SFTP uploads into the database
  2. Database - TimescaleDB for storing time series data and metadata
  3. Data Processor - (Stub implementation) Placeholder for future data analysis and processing logic
  4. Webserver - Main user-facing web application with interactive visualizations
  5. Grafana - Real-time dashboards for CML data visualization
  6. MNO Data Source Simulator - Simulates real-time CML data from MNO sources via SFTP
  7. SFTP Receiver - Receives uploaded CML data files

Webserver Pages

The webserver provides an intuitive interface with four main pages:

  • Landing Page (/) - System overview with data statistics and processing status
  • Real-Time Data (/realtime) - Interactive CML network map with Grafana-embedded time series plots
  • Archive (/archive) - Long-term archive statistics and data distribution analysis
  • Data Uploads (/data-uploads) - File upload interface for CML data files

Getting Started

Prerequisites

  • Docker and Docker Compose
  • Git

Setup

  1. Clone the repository:

    git clone https://github.com/OpenSenseAction/GMDI_prototype.git
    cd GMDI_prototype
  2. Generate SSH keys for SFTP server:

    cd ssh_keys
    ./generate_ssh_keys.sh
    cd ..
  3. Build and run the containers:

    docker compose up -d
  4. Access the services:

    Note: The processor service (port 5002) is currently a minimal stub implementation.

Data Flow

  1. MNO Simulator → generates CML data from NetCDF files and uploads via SFTP to SFTP Receiver
  2. Parser → watches SFTP upload directory and processes CSV files (both metadata and data)
  3. Parser → validates and writes parsed data to Database (TimescaleDB)
  4. Webserver → serves UI and provides API access to database
  5. Grafana → visualizes real-time data from database with embedded dashboards

Storage Backend

The webserver supports multiple storage backends for received files:

  • Local filesystem (default) - For development and testing
  • MinIO - S3-compatible object storage (optional)
  • AWS S3 - Production object storage (configure via environment variables)

To use MinIO, uncomment the minio service in docker-compose.yml and set:

environment:
  - STORAGE_BACKEND=minio
  - STORAGE_S3_BUCKET=cml-data
  - STORAGE_S3_ENDPOINT=http://minio:9000

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