A early paper based on LIRNEasia’s work on big data was presented at the 2014 CPRsouth conference in Maropeng, South Africa. The journal article based on that has just been published. The abstract: Rapid urban population growth is straining transportation systems. A big data–centric approach to transportation management is already a reality in many developed economies, with transportation systems being fed a large quantity of sensor data. Developing countries, by contrast, rely heavily on infrequent and expensive surveys.
The research was done in Sri Lanka, but it was first reported on in India, then in Bangladesh and now the Sri Lankan English-language Sunday newspaper with the largest circulation has chosen to reprint what Nalaka Gunawardene wrote for SciDev. Now we need to work on Pakistan and Nepal. City planners need to know where people live and congregate, when and how they move, their economic conditions, where they spend their money, and about their social networks. Currently the best big data source for these variables involves mobile phones – ubiquitous device used by the rich and poor alike. Mobile network big data (MNBD) is produced by all phones, smart and otherwise, and include call detail records (CDRs) generated when calls and texts are sent or received, web is accessed, and prepaid values are loaded.
Partha Mukhopadhdyaya is an expert on cities, having studied them in multiple countries including China and India. He also happens to serve on our scientific advisory board. Mint carried the first part of an interesting discussion with Partha on cities. When we talk about the insights from big data for cities, we naturally get slotted into the data for “planning” box. But I’ve always been wary about planning and also talk about experimentation using near-real-time and low-cost feedback.