【摘要】 为探讨大数据如何更好地支撑精准扶贫研究和实践,本文对精准扶贫研究文献和大数据管理平台案例进行分析,发现精准扶贫研究和实践的数据采集与分析、大数据管理存在应用"烟囱"和数据"孤立"现象严重、跨学科研究和综合集成数据分析方法应用不足、精准扶贫"块数据"开发应用亟待加强、缺乏以贫困人口为中心的数据关联整合等问题。为应对大数据应用的不足,引入生态学中"生境"的概念,置贫困人口为中心的"人"、"事"、"物"于特定空间的"生境"中,构建基于贫困人口"生境"块数据的大数据关联整合措施,形成与基于业务流程的精准扶贫大数据管理平台互补的横向整合方案,并提出利用"生境"块数据进行精准扶贫开发的5种应用场景设想。本文主要构建了一个以贫困人口为中心的大数据关联整合方案的理论模型,其在实际应用中是否可行,还需要更多地实践证据予以检验。更多还原

【Abstract】 The objective of this paper is to illustrate and examine the possible paths of big data to support targeted poverty alleviation.The paper conducts an exploratory multi-case study which involves 11 cases of the research literature and the large data management platform(Gansu,Guizhou,Jiangxi,et al.).The analysis reveals that problems of data collection,analysis and big data management,are lack of interdisciplinary research and integrated data analysis methods,block data application and integration of poverty population-centric big data,stovepipe development and information islands.In response to the various problems of data collection,analysis and big data management,the concept of habitat in ecology is introduced into our study.Habitat is used to define the people and things that are centered around the poor in a particular space.The big data correlation integration based on the habitat of poor people forms the block data of the research and practice of the targeted poverty alleviation.Then we put forward five application scenarios of using the"habitat"block data for the development of targeted poverty alleviation.The key limitation of the study is that it focuses solely theoretical model.In the future,more empirical evidence is needed to determine whether the model is feasible in practice.更多还原