从地理空间大数据中生成可操作的情报:最新技术和概念

A. F. Jocea, Liviu Porumb, Lucian Necula, Alexandru-Cosmin Grivei, D. Raducanu
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摘要

在当前的信息时代,全球范围内,结构化和非结构化信息的可用性和使用呈指数级增长,这种现象被称为大数据。“大数据”一词不仅指数据本身的庞大数量和种类,而且还指围绕数据收集、存储、检索、管理、处理和分析数据的一系列技术,以解决社会中的复杂问题,分别提高生活质量的各个方面。鉴于每天产生的数据中约有80%具有空间成分,研究表明,到2025年,需要分析的数据将超过150泽字节(150万亿千兆字节),因此有必要创建用于存储、组织、操作、查看和检索相关信息的大数据解决方案。今天,在“数据革命”的浪潮中,越来越多的国家正在启动雄心勃勃的计划,旨在发展对数据的利用。这些项目测试决策者识别、组织和利用数据的能力,这些数据被认为是一种有价值的资源,并通过方便访问来创造从中产生价值的手段。大数据现象也征服了军事领域,其中当前和新兴的大规模数据分析领域的目标是利用经典技术,如基于规则的系统,形状分析,树形结构等分析技术,以开发高效的工具。在本文中,我们将从大数据的基本特征调查开始,并继续涉及地理空间大数据的生成,收集,存储和分析所需的技术细节,将这些数据转化为可操作的情报。
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GENERATING ACTIONABLE INTELLIGENCE FROM GEOSPATIAL BIG DATA: STATE OF THE ART AND CONCEPT
The current information age has led, globally, to an exponential increase regarding the availability and the use of the information, both structured and unstructured, a phenomenon known as Big Data. The term Big Data refers not only to the massive volume and variety of data itself, but also to the set of technologies that surround it, in order to collect, store, retrieve, manage, process and analyze data in order to solve complex problems in society, respectively for increasing the quality of life in all its aspects. Given that approximately 80% of the data generated daily has a spatial component, and studies indicate that more than 150 zettabytes (150 trillion gigabytes) of data will require analysis by 2025, it is necessary to create Big Data solutions for storage, organizing, manipulating, viewing, and retrieving relevant information. Today, in the midst of the �data revolution�, more and more countries are launching ambitious programs aimed at developing their use. These programs test the ability of decisionmakers to recognize, structure and exploit data, which is considered a valuable resource, and create the means to generate value from it by facilitating access. The Big Data phenomenon has also conquered the military field, in which the current and emerging object of large-scale data analysis areas is the exploitation of classical techniques such as rule-based systems, shape analysis, tree structures and other analysis technologies in order to develop efficient tools. In this paper we will start from the investigation of the basic characteristics of Big Data and continued with technical details that involves the generation, collection, storage and analysis of geospatial Big Data needed to transform these data into an actionable intelligence.
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