fbpx

D4D

D4D Image

Organization: Data for Development

Country: Global

Forum: Big data & healthcare

Launched in June 2012, Data for Development is a challenge organized by Orange based on using anonymized data extracted from the mobile phone network to contribute to the development and welfare of populations. The data was used to reveal information on the mobility and call patterns of the citizens of Ivory Coast, a country struggling with poverty and in the aftermath of a recent civil war.

Several D4D projects utilized this mobile phone data to tackle key health issues. For instance, analysis of human mobility patterns was used to map how disease spreads across the country, revealing that small changes in the health system could potentially reduce the spread of flu by 20% as well as substantially reduce the spread of HIV/AIDS and malaria. The data was also used to map ethnic boundaries, based on the fact that ethnic and language groups communicate far more within their own group than they communicate with others. Mapping social boundaries is important because, while we know that ethnic violence often erupts along such boundaries, the government and aid agencies are usually uncertain about the geography of these social fault lines.

In April 2014 a new year-long project was launched based on information on the hours of sunshine as well as mobile phone data in Senegal. The project will close in April 2015 when the D4D Committee will choose the best projects.

D4D

D4D Image

Organization: Data for Development

Country: Global

Forum: Big data & healthcare

Launched in June 2012, Data for Development is a challenge organized by Orange based on using anonymized data extracted from the mobile phone network to contribute to the development and welfare of populations. The data was used to reveal information on the mobility and call patterns of the citizens of Ivory Coast, a country struggling with poverty and in the aftermath of a recent civil war.

Several D4D projects utilized this mobile phone data to tackle key health issues. For instance, analysis of human mobility patterns was used to map how disease spreads across the country, revealing that small changes in the health system could potentially reduce the spread of flu by 20% as well as substantially reduce the spread of HIV/AIDS and malaria. The data was also used to map ethnic boundaries, based on the fact that ethnic and language groups communicate far more within their own group than they communicate with others. Mapping social boundaries is important because, while we know that ethnic violence often erupts along such boundaries, the government and aid agencies are usually uncertain about the geography of these social fault lines.

In April 2014 a new year-long project was launched based on information on the hours of sunshine as well as mobile phone data in Senegal. The project will close in April 2015 when the D4D Committee will choose the best projects.

TOP