Urban mobility insights: A dataset for exploring network topology and city dynamics

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-09-18 DOI:10.1016/j.dib.2025.112076

D.D. Herrera-Acevedo , D. Sierra-Porta

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引用次数: 0

Abstract

This article presents a comprehensive dataset capturing the urban network structures and sociodemographic variables of 65 cities worldwide for the year 2023, based on the Urban Mobility Readiness Index (UMRi) developed by the Oliver Wyman Forum. The dataset includes key metrics such as graph entropy, node degree, clustering coefficient, graph diameter, GDP per capita, and population density, among others, which are essential for analysing the relationship between network topology and urban mobility readiness. By offering detailed insights into these urban networks, this dataset serves as a valuable resource for cities not currently included in major mobility rankings, allowing them to evaluate their mobility readiness in relation to established indices like the UMRi. Urban planners and researchers can leverage this data to explore complex urban mobility dynamics and develop strategies to enhance transportation systems, particularly in rapidly growing or underserved regions. The dataset is structured for seamless integration with various analytical tools, making it a vital asset for both urban planning and research aimed at fostering sustainable and efficient urban development.

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城市移动洞察：用于探索网络拓扑和城市动态的数据集

本文基于奥纬咨询论坛（Oliver Wyman Forum）开发的城市流动性准备指数（UMRi），提供了一个全面的数据集，涵盖了2023年全球65个城市的城市网络结构和社会人口变量。该数据集包括图熵、节点度、聚类系数、图直径、人均GDP和人口密度等关键指标，这些指标对于分析网络拓扑与城市交通准备度之间的关系至关重要。通过提供对这些城市网络的详细见解，该数据集为目前未列入主要流动性排名的城市提供了宝贵的资源，使他们能够根据UMRi等既定指数评估其流动性准备情况。城市规划者和研究人员可以利用这些数据来探索复杂的城市交通动态，并制定战略来加强交通系统，特别是在快速增长或服务不足的地区。该数据集的结构可与各种分析工具无缝集成，使其成为旨在促进可持续和高效城市发展的城市规划和研究的重要资产。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.