数据驱动的智慧城市:组织、技术和数据的复杂性

Megan K. Sutherland, Meghan E. Cook
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引用次数: 21

摘要

这篇管理论文着眼于城市政府在建立利用数据实现智慧城市承诺的能力时所面临的挑战。虽然生成分析和可视化已经引起了很多关注,但本文认为,在数据生命周期的早期阶段解决数据质量和数据管理实践对于实现数据驱动的智慧城市非常重要。为了证明这一点,本文讨论了纽约州(NYS)的一个案例,展示了在数据收集和初始存储开始时未解决数据质量和数据管理问题时城市面临的挑战。最后,本文为城市领导者提出了评估其环境和解开复杂性的建议,以便他们能够建立数据能力,以实现数据驱动的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Driven Smart Cities: A Closer Look at Organizational, Technical and Data Complexities
This management paper looks at the challenges faced by city governments as they build their capability to leverage data to achieve the promise of a smarter city. While producing analytics and visualizations have captured much attention, this paper argues that addressing data quality and data management practices in the early stages of the data life cycle are very important to achieving data-driven smart cities. To demonstrate this point, this paper discusses a case from New York State (NYS), demonstrating the challenges cities face when data quality and data management are not addressed at the onset of data collection and initial storage. Finally, this paper sets forth recommendations for city leaders to assess their environment and unpack complexities so that they can build data capability to enable data-driven decision making.
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