Study title

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 slums covered 36 slums across the city. The slums were chosen based on stratification criteria which included the geographical location of the slums, whether the slums were resettled or rehabilitated, slums in planned localities, 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 1107 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.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. To identify the poor is to be able to deliver benefits to them. 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 slums covered 36 slums across the city. The slums were chosen based on stratification criteria which included the geographical location of the slums, whether the slums were resettled or rehabilitated, slums in planned localities, 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 in the dataset. The data...