Knowledge Graph Datasets

This repository contains various knowledge graph datasets and import tools.

🚌 GTFS Transit Data Import

The main project is located in the gtfs/ directory and provides a complete solution for importing GTFS (General Transit Feed Specification) data into Dgraph.

Prerequisites

• Python 3.8+
• uv package manager
• Dgraph instance (local or remote)
• Configuration file with Dgraph connection details

Install uv

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Quick Start

# Navigate to the GTFS project directory
cd gtfs

# Option 1: Use the automated setup script (recommended)
./setup_uv.sh

# Option 2: Manual setup
uv venv
source .venv/bin/activate  # macOS/Linux
# or
.venv\Scripts\activate     # Windows
uv pip install -e .

# Configure Dgraph connection
make config-example
# Edit config.env with your connection details

# Validate GTFS data
uvx run test_gtfs_data.py

# Import data to Dgraph
uvx run gtfs_import.py

# Explore with sample queries
uvx run sample_queries.py

Documentation

• gtfs/README_GTFS_Import.md - Detailed usage instructions
• gtfs/PROJECT_OVERVIEW.md - Comprehensive project documentation
• gtfs/docker-compose.yml - Dgraph setup configuration

Features

• Complete GTFS data import into Dgraph
• Comprehensive transit knowledge graph
• Interactive query examples
• Docker-based Dgraph setup
• Data validation and analysis tools

See the gtfs/ directory for complete project details and implementation.