利用大数据进行灾难恢复的潜力:斯里兰卡的案例

Akila Pramodh Rathnasinghe, U. Kulatunga
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引用次数: 1

摘要

大数据时代正在为灾害管理(DM)带来新的可能性。在数据创建、存储、检索和分析方面,大数据的概念一直在不断被审视,专业人士已经确定了它在数量、速度和种类上的重要性。大数据提供了在更短的时间内收集更多信息的机会。因此,大数据分析可以大大增强各种灾害恢复能力活动,例如发布疏散预警;帮助应急人员确定需要紧急关注的领域;协调灾害管理活动;并确定各种情况下最有效的应对方法。因此,大数据被认为是灾难响应和更好地了解损害情况和决策的重要催化剂。此外,大数据有可能通过连接人员、流程、数据和技术来提高抗灾能力。然而,了解需要生成的大数据类型、开发必要的数据分析以帮助实时响应、决策和跟踪灾难受害者是至关重要的。为了达到这一目的,采用了定性研究的方法。这项专题研究标志着大数据在预测灾难期间人类行为模式方面的重要性。因此,通过发达国家现有的个案研究,对经常受灾害地区的人力和物质资源的有效管理进行了评价。此外,该研究成功地确定了在法律和技术壁垒上使用大数据所面临的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential of using big data for disaster resilience: the case of Sri Lanka
The epoch of big data is evolving new possibilities for Disaster Management (DM). The concept of Big Data has been constantly scrutinised in terms of data creation, storage, retrieval, and analysis where professionals have identified its significance upon the volume, velocity and variety. Big Data provides the opportunity to gather more information in less time. Hence, analysis of Big Data can substantially enhance various disaster resilience activities such as issuing early warnings for evacuations; help emergency response personnel to identify areas that need urgent attention; coordination of disaster management activities; and to identify the most effective response methods for various situations. Therefore, Big Data is identified as a great catalyst for disaster response and, for better understanding of the damage situation and decision-making. Moreover, Big Data has the potential to improve disaster resilience by connecting people, processes, data and technology. However, it is essential to understand the type of Big Data that needs to be generated, to develop the data analysis as in necessary to help with real time responses, decision making and tracking of disaster victim. In order to accomplish the aim, a qualitative research approach was followed. This topical study marked the importance of big data in predicting human behavioral patterns during a disaster. Accordingly, the effective management of human and physical resources in habitual disaster territories was appraised through existing case studies in developed countries. Further, the research has successfully identified the challenges in employing Big Data upon its legal and technological barriers.
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