Large volumes of complex and variable data - often called 'big data' - promise to help improve government service delivery, complement official statistics, and facilitate development in sectors such as health, urban development, transportation, and humanitarian response. Data now stream from daily life: from phones, credit cards, and televisions, from the infrastructure of cities, from sensor-equipped buildings, trains, planes, buses and factories. The data flow so fast that the total accumulation of the past two years—a zettabyte—dwarfs the prior production of data for the entirety of human civilization. Interest in capturing and analysing these data sets for public purposes - big data for development (BD4D) - is still relatively new, but accelerated when the post-2015 development agenda called for a data revolution to draw on existing and new sources of data to monitor progress on the new Global Goals.Though big data sets, such as purchase-transaction or mobile usage data, are not new, until recently limitations on computer memory, retrieval and processing meant that only institutions like the US National Security Agency and American Express could afford the supercomputers necessary to analyse the huge volumes of information. Declining prices and improved functionality for hardware and memory have democratized data usage, and open-source tools (such as Hadoop) have broadened the mechanisms for people to conduct big-data analytics outside of proprietary and expensive software packages. Interest in BD4D has produced a great demand for computer scientists and statisticians who can understand and analyse large data sets. Yet, as big data scientists are in short supply in developing economies, much of the BD4D research is coming from northern institutions - the United Nations and World Bank, universities and from the private sector [such as IBM and Orange]. This dynamic has meant that the issues deemed significant to the debate tend to be driven by northern concerns, rather than by southern voices and global South collaboration. The same can be said for big data's relationship to gender. The vast majority of data scientists are men, who rarely focus on designing applications that address women's challenges in the Global South. As such, solutions need to be found to address inequalities in capacities and benefits to big data. This grant will support research on big data for development that supports developing countries to measure progress on and contributes to the achievement of the Sustainable Development Goals (SDGs).  This is a proposal jointly presented by LIRNEasia , a Sri Lankan think tank, the African Institute of Mathematical Sciences  and the Centro de Pensamiento Estratégico Internacional –CEPEI, a Colombian think tank.  The network will develop capacity amongst researchers from the Global South, focusing on activities linked to the Sustainable Development Goals (SDGs) and to those that address gender related issues. Over a two-year period