运输启动数据包:非洲、亚洲和南美洲部分国家的客运和货运历史数据

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Naomi Tan , Robert Ambunda , Nikola Medimorec , Angel Cortez , Agustina Krapp , Erin Maxwell , John Harrison , Mark Howells
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引用次数: 0

摘要

随着各国应对城市交通的复杂性,对数据驱动模型的需求变得越来越重要,以便为可持续交通规划提供信息。然而,数据的收集和整理非常耗时,而且由于数据的不可取性和不准确性,数据收集和整理工作可能具有挑战性。因此,交通起步数据工具包旨在应对这些挑战,为交通建模相关数据提供一站式服务。该工具包包含客运和货运活动、能源强度、负载率和车辆保有量等方面的年度历史数据(1990-2021 年),可按模式和燃料分列。此外,还包括影响运输活动的人口和 GDP 数据。该数据集的价值不仅在于其提供的变量范围,还在于其从多个权威来源汇编而成,为对基于数据的交通建模感兴趣的研究人员、顾问和决策者提供了开发模型的基础。通过采用、调整和应用这些数据,可以制定明确的政策,为可持续交通发展提供必要的资金支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transport starter data kit: Historical passenger and freight transport data for selected countries in Africa, Asia, and South America
The demand for data-driven models to inform sustainable transportation planning has become more important as countries address the complexities of urban mobility. However, data collection and curation are time-consuming and can be challenging due to data inaccessibility and inaccuracy. The Transport Starter Data Kit therefore aims to address these challenges, offering a one-stop-shop for transport modelling-related data. The Kit contains historical annual data (1990–2021) on passenger and freight activity, energy intensities, load factors, and vehicle stock, segregated by mode and fuel where available. Additionally, population and GDP data, which influence transport activity, are included. The value of the dataset lies not only in the range of variables it offers but also in the compilation from multiple authoritative sources, providing researchers, consultants, and policymakers interested in data-based transport modelling with a foundational base for their model development. By adopting, adapting, and applying the data, clear policies may be developed which can underpin the necessary finances for sustainable transport development.
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来源期刊
Data in Brief
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.
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