Implementing Big Data Lake for Heterogeneous Data Sources

Hassan Mehmood, Ekaterina Gilman, Marta Cortés, Panos Kostakos, A. Byrne, K. Valta, Stavros Tekes, J. Riekki
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引用次数: 38

Abstract

Modern connected cities are more and more leveraging advances in ICT to improve their services and the quality of life of their inhabitants. The data generated from different sources, such as environmental sensors, social networking platforms, traffic counters, are harnessed to achieve these end goals. However, collecting, integrating, and analyzing all the heterogeneous data sources available from the cities is a challenge. This article suggests a data lake approach built on Big Data technologies, to gather all the data together for further analysis. The platform, described here, enables data collection, storage, integration, and further analysis and visualization of the results. This solution is the first attempt to integrate a diverse set of data sources from four pilot cities as part of the CUTLER project (Coastal urban development through the lenses of resiliency). The design and implementation details, as well as usage scenarios are presented in this paper.
实现异构数据源大数据湖
现代互联城市越来越多地利用信息通信技术的进步来改善其服务和居民的生活质量。来自不同来源的数据,如环境传感器、社交网络平台、流量计数器,被用来实现这些最终目标。然而,收集、集成和分析来自城市的所有异构数据源是一个挑战。本文建议采用基于大数据技术的数据湖方法,将所有数据收集在一起进行进一步分析。这里描述的平台支持数据收集、存储、集成以及对结果的进一步分析和可视化。作为CUTLER项目(通过弹性镜头的沿海城市发展)的一部分,该解决方案首次尝试整合来自四个试点城市的各种数据源。文中给出了系统的设计实现细节和使用场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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