Today we are proud to announce our latest collaboration with UNICEF through their Magic Box initiative – a Big Data for Social Good platform which collects real-time data, combining and analysing aggregated and anonymised data from private sector companies. Magic Box was launched in 2014, when it was used to respond to the Ebola crisis in Western Africa, and more recently to the spread of the Zika virus.
Unlike other initiatives, which have mostly focused on pilots to demonstrate the value of Big Data to better understand humanitarian disasters, Magic Box goes one step further. It combines real-time data sourced from the private sector with other existing public data sets relating to climate, GIS (UNICEF’s Geographic Information System), and socioeconomic and epidemiological data. By unlocking the value of this real-time data, UNICEF can optimise its response to public health emergencies and natural disasters – protecting children and saving lives in an increasingly unpredictable world.
|Figure 1: Unicef demo showing mobile communications in Colombia.|
By means of an Application Programming Interface (API), companies are able to share their anonymised and aggregated datasets in the Magic Box platform, where, once combined with public data sets, provides insights for emergencies.
At the Mobile World Congress, we will be demonstrating the first pilot of this partnership, where mobile network data from Colombia will be used to show how data can be analysed to improve the management of humanitarian disasters, providing alarms, and supporting critical response and recovery monitoring. The natural disasters include an earthquake, a landslide and a flood. They were analysed for this first project, using mobile usage data per antenna (e.g. number of calls, megabytes and SMS) and mobility data to understand human movement. You can see a short taster of the demo here:
Our VP for Big Data for Social Good, Richard Benjamins, stated: “So far we have seen a wide range of pilots which show that Big Data can be a force for good, however, we now need to shift from pilots and ‘one-offs’ to real operative systems which provide a continuous data feed. Data needs to come from both the public and private sector and therefore partnerships like this one are key. This is the only way to have a meaningful impact and bring the power of data to the people who need it most.”
Alfonso Gómez, President of Telefónica Colombia, also highlighted: “Colombia is one of the most vulnerable countries to climate change. The telecommunications sector has a pivotal role to play due to the precision and availability of data which can ultimately save lives. Integrating this agreement between UNICEF and Telefónica, the technology, the data and the collaboration across different sectors in a proactive and innovative way will allow us to enhance our capabilities to respond to emergencies”.
“Magic Box is a way to bring together partners like Telefonica and others from the private sector, who want to use their data as a public social good. We collaborate with them to build a product that allows us to have real-time insights to improve our work for children around the world. To reach the hardest-to-reach children, we need to know where, when and how to act, and we can do this if we have forward-thinking partnerships in place, now.” commented Cynthia McCaffrey, Director, Office of Innovation, UNICEF.
As well as sharing datasets as part of the agreement, UNICEF’s innovation department will work closely with us to accelerate the use of Data Science and Data Engineering in developing real-time humanitarian data analytics.
Today we join other companies like Google, Amadeus and IBM to enable the growth of Big Data for Social Good in line with the United Nation’s Sustainable Development Goals and we’re very excited to be a part of this movement.
Unlike other initiative, which has more often than not focused on pilots to demonstrate the worth of Big Data to better appreciate humanitarian disaster, Magic Box goes one step additional. UK Assignment | Ready Assignment, It combine real-time data foundation from the confidential sector with other obtainable public data sets connecting to type of weather.
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