印度智慧城市中的数据驱动决策:促进数据文化、用例和可视化

Irene Anna Shaji, Gayatri Doctor, Poornima Dore
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引用次数: 0

摘要

印度的智慧城市计划于2015年启动。该任务是一项城市更新和改造计划,以在全国范围内开发100个选定的智能城市。其目标是确保城市的宜居性、经济能力和可持续性。随着该任务的实施,印度智能城市开始产生数据。因此,为了评估和保持数据质量,2019年推出了数据智慧城市战略(DCS)、开放数据门户、数据成熟度评估框架(DMAF)和城市数据政策(CDP),以及其他几项举措。数据本身不能做任何事情,但数据是一种等待被利用的资源。数据驱动的决策有助于支持明智的决策,协助制定部门和城市一级的目标,作为有效决策的基础,并有助于提高透明度和问责制。该研究试图了解温哥华和新加坡的开放数据之旅,并了解印度处于非常早期的阶段。该研究根据现有数据集确定了可能的试点用例和可视化。由于本文正在进行研究,进一步的工作将研究首席数据官(cdo)在鼓励各城市通过结构化访谈调查进行数据驱动决策时所面临的便利和困难。面试将有助于确定挑战并制定克服挑战的策略。
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 decision-making in Indian Smart Cities: Promoting data culture, use cases and visualization
India's Smart Cities Mission launched in 2015. The mission is an urban renewal and retrofitting program to develop 100 selected Smart Cities across the country. Its objective is to ensure the livability, economic-ability, and sustainability of cities. With the implementation of the mission, data started generating across Indian Smart Cities. So, to assess and maintain the quality of data, DataSmart Cities Strategy (DCS), Open Data Portal, Data Maturity Assessment Framework (DMAF), and City Data Policy (CDP) were introduced in 2019, along with several other initiatives. Data in itself can't do anything but data is a resource waiting to get leveraged. Data-driven decisions help support informed decisions, assist in setting departmental and city-level goals, serve as the base for effective policymaking, and help increase transparency and accountability. The research tries to understand the open data journey of Vancouver and Singapore and understands that India is at a very early stage. The study identifies possible pilot use cases and visualizations based on existing datasets. As the paper is ongoing research, further work will study the ease and difficulties faced by Chief Data Officers (CDOs) for encouraging data-driven decisions in respective cities through structured interview-based surveys. The interview will help identify challenges and built strategies for overcoming them.
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