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Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics

机译:空间城市数据系统:基于云的大数据基础架构,用于社会和经济城市分析

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The Spatial Urban Data System (SUDS) is a spatial big data infrastructure to support UK-wide analytics of the social and economic aspects of cities and city-regions. It utilises data generated from traditional as well as new and emerging sources of urban data. The SUDS deploys geospatial technology, synthetic small area urban metrics, and cloud computing to enable urban analytics, and geovisualization with the goal of deriving actionable knowledge for better urban management and data-driven urban decision making. At the core of the system is a programme of urban indicators generated by using novel forms of data and urban modelling and simulation programme. SUDS differs from other similar systems by its emphasis on the generation and use of regularly updated spatially-activated urban area metrics from real or near-real time data sources, to enhance understanding of intra-city interactions and dynamics. By deploying public transport, labour market accessibility and housing advertisement data in the system, we were able to identify spatial variations of key urban services at intra-city levels as well as social and economically-marginalised output areas in major cities across the UK. This paper discusses the design and implementation of SUDS, the challenges and limitations encountered, and considerations made during its development. The innovative approach adopted in the design of SUDS will enable it to support research and analysis of urban areas, policy and city administration, business decision-making, private sector innovation, and public engagement. Having been tested with housing, transport and employment metrics, efforts are ongoing to integrate information from other sources such as IoT, and User Generated Content into the system to enable urban predictive analytics.
机译:空间城市数据系统(SUDS)是空间大数据基础架构,用于支持英国范围内对城市和城市区域的社会和经济方面的分析。它利用从传统以及新兴的城市数据源中生成的数据。 SUDS部署了地理空间技术,合成的小区域城市度量标准和云计算,以实现城市分析和地理可视化,目的是获得可操作的知识,以更好地进行城市管理和以数据为依据的城市决策。该系统的核心是通过使用新颖的数据形式以及城市建模和模拟程序生成的城市指标程序。 SUDS与其他类似系统的不同之处在于,SUDS强调从实时或近实时数据源生成和使用定期更新的空间激活的市区度量,以增进对城市内部互动和动态的理解。通过在系统中部署公共交通,劳动力市场可及性和房屋广告数据,我们能够识别出城市范围内主要城市服务以及英国主要城市的社会和经济边缘输出区域的空间变化。本文讨论了SUDS的设计和实现,遇到的挑战和局限性以及在开发过程中应考虑的因素。 SUDS设计中采用的创新方法将使其能够支持对城市地区,政策和城市管理,商业决策,私营部门创新和公众参与的研究和分析。经过住房,交通和就业指标的测试,正在努力将来自其他来源(例如物联网)和用户生成内容的信息集成到系统中,以进行城市预测分析。

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