Bundled Datasets for Infrastructure in God's Eye View: Complete Data Guide

God's Eye View ships with four ready-to-use infrastructure datasets—covering global data centers, dams, submarine cables, and urban neighborhoods—bundled in src/data/local_data/ for offline visualization without external API dependencies.

The bilawalsidhu/gods-eye-view repository provides a self-contained geographic visualization toolkit that renders critical infrastructure layers without internet connectivity. These bundled datasets for infrastructure are stored as static CSV and GeoJSON files, enabling immediate parsing and 3D rendering in Cesium-based applications.

Core Infrastructure Datasets Included

The repository maintains five distinct data layers under the src/data/local_data/ directory. Each dataset includes a dedicated README documenting provenance and schema details.

Data Centers

The global data center inventory resides at src/data/local_data/datacenters/datacenters.csv. This tabular dataset contains latitude, longitude, facility names, and capacity metrics for major data center locations worldwide. Companion documentation in src/data/local_data/datacenters/README.md explains the coordinate reference system and attribution requirements.

Dams

Hydropower and reservoir infrastructure is catalogued in src/data/local_data/dams/dams.csv. Each record includes geospatial coordinates, structural height, reservoir volume, and primary purpose classification (hydroelectric, irrigation, or flood control). The dataset provides global coverage of large-scale dam installations for energy and water resource visualization.

Submarine Cables

Telecommunications infrastructure is represented by src/data/local_data/telegeography_submarine_cables/submarine_cables.csv. Sourced from Telegeography, this file contains cable track linestrings, landing point coordinates, and capacity specifications for international fiber optic networks. The data enables visualization of internet backbone topology and intercontinental connectivity.

Urban Neighborhoods

Fine-grained administrative boundaries are stored in src/data/local_data/neighborhoods/neighborhoods.json as a GeoJSON FeatureCollection. This polygon dataset defines neighborhood boundaries for major metropolitan areas, supporting street-level context and demographic overlay analysis. Source attribution is documented in src/data/local_data/neighborhoods/SOURCE.md.

Natural Earth Base Layers

Geographic context is provided by the src/data/local_data/natural_earth/ directory, which contains shapefiles and GeoJSON representations of countries, coastlines, and raster backdrop imagery. These base layers from the Natural Earth project serve as the cartographic foundation for overlaying the infrastructure datasets. Configuration details are available in src/data/local_data/natural_earth/README.md.

Data Architecture and File Formats

God's Eye View employs format-specific storage optimized for web-based geospatial engines:

• CSV files store tabular infrastructure data with WGS84 latitude/longitude columns, enabling lightweight parsing for point-based visualization (data centers, dams, cable landing points).
• GeoJSON encodes polygon boundary data for complex geometries like urban neighborhoods, supporting direct consumption by JavaScript mapping libraries.
• Shapefiles in the Natural Earth directory provide high-resolution vector basemaps for professional cartographic output.

The architecture is documented in docs/INFRASTRUCTURE-LAYERS.md, which details how these layers integrate with the rendering pipeline.

Loading Bundled Datasets in Code

Access the bundled infrastructure data using standard web APIs or visualization libraries like D3 and Cesium.

// Load tabular data center locations using D3
import { csv } from 'd3-fetch';

async function loadDatacenters() {
  const data = await csv('./src/data/local_data/datacenters/datacenters.csv');
  return data; 
  // Returns: [{ name, latitude, longitude, capacity }, ...]
}

// Load neighborhood polygons as GeoJSON
import { json } from 'd3-fetch';

async function loadNeighborhoods() {
  const geo = await json('./src/data/local_data/neighborhoods/neighborhoods.json');
  return geo; 
  // Returns: GeoJSON FeatureCollection
}

Integrate these data sources into a Cesium 3D viewer:

import { CzmlDataSource } from 'cesium';

function addInfrastructureLayer(viewer, dataSourceUrl) {
  viewer.dataSources.add(
    CzmlDataSource.load(dataSourceUrl)
  );
}

// Usage with bundled dataset
addInfrastructureLayer(viewer, './src/data/local_data/dams/dams.csv');

Summary

• God's Eye View includes four primary infrastructure datasets stored in src/data/local_data/ requiring no external downloads.
• Data centers (datacenters.csv), dams (dams.csv), and submarine cables (submarine_cables.csv) use CSV format with WGS84 coordinates.
• Neighborhoods (neighborhoods.json) provides urban boundaries as GeoJSON polygons.
• Natural Earth base layers in natural_earth/ supply cartographic context via shapefiles and GeoJSON.
• All datasets are documented in repository-specific README files and the main docs/INFRASTRUCTURE-LAYERS.md guide.

Frequently Asked Questions

What file formats are used for the bundled infrastructure datasets?

God's Eye View stores point-based infrastructure (data centers, dams, submarine cables) as CSV files containing latitude and longitude columns. Neighborhood boundaries are stored as GeoJSON polygons, while Natural Earth base layers use shapefiles and GeoJSON for global vector geometry.

Do I need an internet connection to use these datasets?

No. All infrastructure datasets are bundled locally within the src/data/local_data/ directory. The application loads these files via local HTTP requests or direct file system access, enabling fully offline visualization once the repository is cloned.

How is the submarine cable data sourced?

The submarine cable dataset originates from Telegeography and is stored at src/data/local_data/telegeography_submarine_cables/submarine_cables.csv. It includes international fiber optic cable routes, landing point coordinates, and capacity metadata for mapping global internet backbone infrastructure.

Can I add custom infrastructure datasets to the local_data folder?

Yes. The application architecture supports extending the src/data/local_data/ directory with additional CSV or GeoJSON files. Ensure new datasets follow the existing coordinate format (WGS84 EPSG:4326) and include a corresponding README.md file documenting the schema and source attribution.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}