  Water is a crucial pre-requisite for all human activities. Due to growing
demand from population and shrinking supply of potable water, there is an
urgent need to use computational methods to manage available water
intelligently, and especially in developing countries like India where even
basic data to track water availability or physical infrastructure to process
water are inadequate. In this context, we present a dataset of water pollution
containing quantitative and qualitative data from a combination for modalities
- real-time sensors, lab results, and estimates from people using mobile apps.
The data on our API-accessible cloud platform covers more than 60 locations and
consists of both what we have ourselves collected from multiple location
following a novel process, and from others (lab-results) which were open but
hither-to difficult to access. Further, we discuss an application of released
data to understand spatio-temporal pollution impact of a large event with
hundreds of millions of people converging on a river during a religious
gathering (Ardh Khumbh 2016) spread over months. Such unprecedented details can
help authorities manage an ongoing event or plan for future ones. The community
can use the data for any application and also contribute new data to the
platform.
