Data for: Towards Sustainable Smart City by Particulate Matter Prediction using Urban Big Data, Excluding Expensive Air Pollution Infrastructures

It is vital to capture and analyze, from various sources in smart cities, the data that are beneficial in urban planning and decision making for governments and individuals. Urban policy makers can find a suitable solution for urban development by using the opportunities and capacities of big data, and by combining different heterogeneous data resources in smart cities. This paper presents data related to urban computing with an aim of assessing the knowledge that can be obtained through integration of multiple independent data sources in Smart Cities. The data contains multiple sources in the city of Aarhus, Denmark from August 1, 2014 to September 30, 2014. The sources include land use, waterways, water barriers, buildings, roads, amenities, POI, weather, traffic, pollution, and parking lot data. The published data in this paper is an extended version of the City Pulse project data to which additional data sources collected from online sources have been added.

捕捉与分析智慧城市中各来源的有益数据，对于城市规划和政府及个人决策至关重要。城市政策制定者可通过运用大数据的机遇与潜能，以及融合智慧城市中多样化的异构数据资源，寻找到适合的城市发展解决方案。本文旨在通过整合智慧城市中多个独立数据源，评估所能获取的知识，并展示了与城市计算相关的数据。该数据集涵盖了丹麦奥尔胡斯市2014年8月1日至2014年9月30日之间的多个数据源，包括土地利用、水道、水利设施、建筑物、道路、公共设施、兴趣点、天气、交通、污染和停车场数据。本文中发布的数据是City Pulse项目数据的扩展版本，其中增加了从在线来源收集的额外数据源。