Roy Debraj, Palavalli Bharath, Menon Niveditha, King Robin, Pfeffer Karin, Lees Michael, Sloot Peter M A
University of Amsterdam, Amsterdam 1098 XH, The Netherlands.
Nanyang Technological University, Singapore 639798, Singapore.
Sci Data. 2018 Jan 9;5:170200. doi: 10.1038/sdata.2017.200.
In 2010, an estimated 860 million people were living in slums worldwide, with around 60 million added to the slum population between 2000 and 2010. In 2011, 200 million people in urban Indian households were considered to live in slums. In order to address and create slum development programmes and poverty alleviation methods, it is necessary to understand the needs of these communities. Therefore, we require data with high granularity in the Indian context. Unfortunately, there is a paucity of highly granular data at the level of individual slums. We collected the data presented in this paper in partnership with the slum dwellers in order to overcome the challenges such as validity and efficacy of self reported data. Our survey of Bangalore covered 36 slums across the city. The slums were chosen based on stratification criteria, which included geographical location of the slum, whether the slum was resettled or rehabilitated, notification status of the slum, the size of the slum and the religious profile. This paper describes the relational model of the slum dataset, the variables in the dataset, the variables constructed for analysis and the issues identified with the dataset. The data collected includes around 267,894 data points spread over 242 questions for 1,107 households. The dataset can facilitate interdisciplinary research on spatial and temporal dynamics of urban poverty and well-being in the context of rapid urbanization of cities in developing countries.
2010年，全球估计有8.6亿人生活在贫民窟，2000年至2010年间贫民窟人口增加了约6000万。2011年，印度城市家庭中有2亿人被认为生活在贫民窟。为了制定和创建贫民窟发展计划及扶贫方法，有必要了解这些社区的需求。因此，在印度背景下，我们需要高粒度的数据。不幸的是，单个贫民窟层面缺乏高粒度的数据。为了克服自我报告数据的有效性和功效等挑战，我们与贫民窟居民合作收集了本文中呈现的数据。我们对班加罗尔的调查覆盖了全市36个贫民窟。这些贫民窟是根据分层标准挑选的，包括贫民窟的地理位置、是否是重新安置或改造的贫民窟、贫民窟的通知状态、贫民窟的规模以及宗教概况。本文描述了贫民窟数据集的关系模型、数据集中的变量、为分析而构建的变量以及数据集中发现的问题。收集到的数据包括分布在1107户家庭的242个问题中的约267894个数据点。该数据集有助于在发展中国家城市快速城市化背景下，对城市贫困和福祉的时空动态进行跨学科研究。
