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Big data open platform for water resources management

机译:水资源管理大数据开放平台

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Nowadays Big Data are becoming a popular topic and a comparatively new technological concept focused on many different disciplines like environmental science, social media and networks, industry and healthcare. Data volumes are on an upward trajectory associated with increased data velocity, and variety. Furthermore, they are needed to develop effective solutions to support intelligent, proactive and predictive processes. In this paper we exploit Big Data concepts for environmental sciences and water resources. The aim of this article is to present the concept and architecture of our Big Data Open Platform used for supporting Water Resources Management. This Platform has been designed to provide effective tools that allow water system managers to solve complex water resources systems, water modeling issues and help in decision making. The Platform brings a variety of information technology tools including stochastic aspects, high performance computing, simulation models, hydraulic and hydrological models, grid computing, decision tools, Big Data analysis system, communication and diffusion system, database management, geographic information system (GIS) and Knowledge based expert system. The operators' objectives of this Big Data Open Platform are to solve and discuss water resources problems that are featured by a huge volume of collected, analyzed and visualized data, to analyze the heterogeneity of data resulting from various sources including structured, unstructured and semi-structured data, also to prevent and/or avoid a catastrophic event related to floods and/or droughts, through hydraulic infrastructures designed for such purposes or strategic planning. This first paper will focus on the first part developed and based on J2EE platform and specifically the hypsometrical approach considered as a decision tool allowing users to compare the effects of different current and future management scenarios and make choice to preserve the environment and natural res- urces.
机译:如今,大数据正成为一个流行的话题,并且是一个相对较新的技术概念,重点关注环境科学,社交媒体和网络,工业和医疗保健等许多不同学科。数据量处于与增加的数据速度和多样性相关的上升轨迹。此外,他们需要开发有效的解决方案来支持智能,主动和预测性过程。在本文中,我们将大数据概念用于环境科学和水资源。本文的目的是介绍用于支持水资源管理的大数据开放平台的概念和体系结构。该平台旨在提供有效的工具,使水系统管理者能够解决复杂的水资源系统,水模型问题并帮助决策。该平台带来了多种信息技术工具,包括随机方面,高性能计算,模拟模型,水力和水文模型,网格计算,决策工具,大数据分析系统,通信和扩散系统,数据库管理,地理信息系统(GIS)和基于知识的专家系统。该大数据开放平台的运营商目标是解决和讨论以大量收集,分析和可视化数据为特征的水资源问题,以分析各种来源(包括结构化,非结构化和半结构化)产生的数据异质性。结构化数据,也可以通过为此目的设计的液压基础设施或战略规划来预防和/或避免与洪水和/或干旱有关的灾难性事件。本文的第一部分将重点关注基于J2EE平台开发的第一部分,尤其是将测高法作为一种决策工具,使用户可以比较当前和将来不同管理方案的影响,并选择保留环境和自然资源的方法。 。

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