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BIGSEA: A Big Data analytics platform for public transportation information

机译:BIGSEA:用于公共交通信息的大数据分析平台

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Analysis of public transportation data in large cities is a challenging problem. Managing data ingestion, data storage, data quality enhancement, modelling and analysis requires intensive computing and a nontrivial amount of resources. In EUBra-BIGSEA (Europe-Brazil Collaboration of Big Data Scientific Research Through Cloud-Centric Applications) we address such problems in a comprehensive and integrated way. EUBra-BIGSEA provides a platform for building up data analytic workflows on top of elastic cloud services without requiring skills related to either programming or cloud services. The approach combines cloud orchestration, Quality of Service and automatic parallelisation on a platform that includes a toolbox for implementing privacy guarantees and data quality enhancement as well as advanced services for sentiment analysis, traffic jam estimation and trip recommendation based on estimated crowdedness. All developments are available under Open Source licenses (http://github.org/eubr-bigsea, https://hub.docker.com/u/eubrabigsea/). (C) 2019 Elsevier B.V. All rights reserved.
机译:大城市公共交通数据的分析是一个具有挑战性的问题。管理数据摄取,数据存储,数据质量增强,建模和分析需要密集的计算和大量的资源。在EUBra-BIGSEA(欧洲-巴西通过以云为中心的应用程序进行大数据科学研究的合作)中,我们以综合和集成的方式解决了此类问题。 EUBra-BIGSEA提供了一个平台,可在弹性云服务之上构建数据分析工作流,而无需与编程或云服务相关的技能。该方法在平台上结合了云编排,服务质量和自动并行化功能,该平台包括用于实现隐私保证和数据质量增强的工具箱,以及用于情感分析,交通拥堵估计和基于估计拥挤度的出行建议的高级服务。所有开发都可以在开源许可证下获得(http://github.org/eubr-bigsea,https://hub.docker.com/u/eubrabigsea/)。 (C)2019 Elsevier B.V.保留所有权利。

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