At Fields of View, we build computational models to improve public policy-making. Such models examine, the linkages between the macro and the micro; and temporal effects, that include the immediate impact (short-term events such as evictions, floods, etc.) and slow-impact long-term events (such as inter-generational migration, poverty alleviation schemes, housing programmes, etc).

In order to build such models, we rely on a wide variety of data,

• Source: We often use data released by govt. bodies, other civil society organisations, and academia.
• License: Datasets that we use are released under a wide variety of licenses, we share the data here under the same licenses.
• Type: The datasets shared here could be quantitative, qualitative, spatial and across different granularities. The data shared here will be appropriately tagged.
• Quality: In many cases, these datasets are either not machine readable or the data requires substantial cleaning. We attempt to share both, the cleaned, machine readable data as well as the source files that we had access to in this data repository.

This repository makes available different datasets that we have collected, used and relied on for our work. In addition, some of our partners have generously agreed to share the data.

As an example, we have been working on a model to understand affordable housing in India. Inadequate affordable housing is a well-documented problem in India and across South Asia. What is not well understood though is how affordable housing programmes and policies affect the urban poor, so that we can improve both the efficacy and delivery of such programmes.