GeoGraphNetworks: Shapefile-Derived Datasets for Accurate and Scalable Graphical Representations

The GeoGraphNetworks data repository provides a comprehensive collection of networks, including the road and railway networks of the United States of America (USA) and the road and river networks of Great Britain (GB). This dataset offers nationwide coverage for both countries.The networks representing the road infrastructure of the USA include primary and secondary roads, covering all 50 states, 1 federal district (Washington, D.C.), and 5 territories, resulting in a total of 56 networks. The rail line infrastructure of the USA is represented as a single network that covers the entire country and includes connectivity to Canada. A total of 114 files , including 57 in Excel (.xlsx) format and 57 in JSON format, representing a total of 56 road networks and 1 rail network.Great Britain dataset comprises a comprehensive collection of 106 files, including 53 in Excel (.xlsx) format and 53 in JSON format, representing a total of 53 unique networks, 52 road networks and 1 river network. Each file is named with a unique code assigned by Ordnance Survey, which systematically divides Great Britain into 100 km by 100 km tiles (https://www.ordnancesurvey.co.uk/documents/product-support/user-guide/os-open-roads-overview.pdf).It allows researchers, urban planners, and anyone interested to explore how these networks connect people and places. With GeoGraphNetworks, you can easily analyze the travel routes and waterways that play a crucial role in the transportation systems of GB and the USA.The JSON files contain graph objects created using the widely used Python library NetworkX, allowing for immediate use without the need for pre-processing. Meanwhile, the Excel files are designed to support the construction of these graph networks across various platforms and programming languages, providing users with flexibility and ease of integration into their projects. This ensures that whether you're a developer, researcher, or data analyst, you can leverage this dataset effectively in your work.<br>Visual representation of each network along with the code to use these networks (in Notebooks) are hosted on the Github Profile: https://github.com/Harsh9650/GeoGraphNetworksGeoGraphNetworks 数据集存储库提供了覆盖全面的网络数据集，涵盖美利坚合众国（United States of America, USA）的道路与铁路网络，以及大不列颠（Great Britain, GB）的道路与河网。该数据集覆盖两国全境。美国道路基础设施网络包含主次干道，覆盖全美50个州、1个联邦特区（华盛顿哥伦比亚特区）及5个海外领地，总计56个网络。美国铁路线基础设施为单一全域网络，可实现与加拿大的互联互通。本数据集共包含114个文件，其中57个为Excel (.xlsx) 格式，57个为JSON格式，分别对应56个道路网络与1个铁路网络。大不列颠数据集包含106个文件，其中53个为Excel (.xlsx) 格式，53个为JSON格式，总计53个独立网络，含52个道路网络与1个河网。每个文件均采用英国地形测量局（Ordnance Survey, OS）分配的唯一编码命名，该局将大不列颠地区系统划分为100km×100km的网格瓦片（参考文档：https://www.ordnancesurvey.co.uk/documents/product-support/user-guide/os-open-roads-overview.pdf）。本数据集可供研究人员、城市规划者及所有相关爱好者探索各类网络如何实现人与地域的互联互通。借助GeoGraphNetworks，用户可便捷分析英美两国交通系统中发挥关键作用的出行路线与航道。JSON文件包含采用主流Python库NetworkX构建的图对象，可直接使用，无需预处理。Excel文件则支持跨平台、多编程语言构建此类图网络，为用户提供灵活的项目集成方案。无论开发者、研究人员还是数据分析从业者，均可高效利用本数据集开展工作。各网络的可视化展示与使用代码（含Jupyter Notebook示例）已托管于GitHub仓库：https://github.com/Harsh9650/GeoGraphNetworks