By the outset of this review, 168 million people needed humanitarian aid, and the number grew to 235 million by the end of the completion of this review. There is no time to lose, definitely no data to lose. Humanitarian relief is crucial not just to contend with a pandemic once a century but also to provide help during civil conflicts, ever-increasing natural disasters, and other forms of crisis. Reliance on technology has never been so relevant and critical than now. The creation of more data and advancements in data analytics provides an opportunity to the humanitarian field. This review aimed at providing a holistic understanding of big data analytics in a humanitarian and disaster setting. A systematic literature review method is used to examine the field and the results of this review explain research gaps, and opportunities available for future research. This study has shown a significant research imbalance in the disaster phase, highlighting how the emphasis is on responsive measures than preventive measures. Such reactionary measures would only exacerbate the disaster, as is the case in many nations with COVID-19. Overall this research details the current state of big data analytics in a humanitarian and disaster setting.
翻译:在本次审查开始之时,1.68亿人需要人道主义援助,到本次审查结束时,人数增加到2.35亿人,没有时间损失,绝对没有数据损失。人道主义救济不仅对于对付一个世纪的大流行病至关重要,而且对于在内部冲突、不断增加的自然灾害和其他形式的危机期间提供帮助也至关重要。对技术的依赖从来没有像现在这样重要和关键。创造更多的数据和数据分析进步为人道主义领域提供了机会。这次审查旨在全面了解人道主义和灾害背景下的大数据分析。利用系统文献审查方法对实地进行审查,并用这一审查的结果来解释研究差距和今后研究的机会。这项研究显示,灾害阶段的研究严重不平衡,突出了如何强调应对措施而不是预防措施。这种反动措施只会加剧灾害,正如许多具有COVID-19的国家的情况那样。总体而言,这项研究详细介绍了人道主义和灾害背景下的大数据分析现状。