The Data for Children Collaborative with UNICEF is a unique partnership between UNICEF, The Scottish Government and the University of Edinburgh.

Our goal is to leverage expertise from each of our partner organisations in order to address existing problems for children using innovative data science techniques.

In today’s fast-paced technological landscape, where data is a driving force and evidence is vital to decision making, we want to provide the platform that brings together the data, skills and expertise to answer our challenge questions. Our role is to build and support project teams to produce real-world impacts that help the world’s children.

All of our projects look to make progress against one of the UN’s Sustainable Development Goals. In addition, we are focused on providing data driven insights. That means our projects might use novel data science techniques, combine data sets in unique ways or tackle an existing problem in a new way by using data.

Items in this Collection

  • Uganda Travel Time to nearest Level IV health centre Map Output 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to level IV health facilities in Uganda. Level IV facilities typically have Qualified nurses, Nurse aids, Clinical officers (physicians assistants) and Doctors (not all will ...
  • Uganda Travel Time to nearest Level III health centre Map Ouput 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to level III health facilities in Uganda. Level III facilities typically have Qualified nurses, Nurse aids and Clinical officers (physicians assistants) present withing them. ...
  • Uganda Travel Time to any health facility Map Ouput 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to health facilities in Uganda. The data was generated using the Child Poverty and Access to Services (CPAS) software (10.5281/zenodo.4638563) and was created as part of the ...
  • Uganda 20 m cost allocation surfaces for the travel time maps 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    20 m resolution cost allocation or friction surface data for Uganda. This data was created using the CPAS software (10.5281/zenodo.4638563). There are two surfaces here, one with water masked to prevent travel across open ...
  • Uganda Road Data for Travel Time Maps 

    Watmough, Gary
    This .shp file is a polyline shapefile containing the roads data in Uganda that was used to create the Uganda cost allocation/friction surfaces. The data are a combination (merged) of Open Street Map roads data and MapwithAi ...
  • Mozambique Road Data for Travel Time Maps 

    Watmough, Gary
    A polyline shapefile dataset containing roads merged from two source datasets (1) Open street map and (2) MapwithAI project. Used in the creation of travel time estimates in mozambique
  • Zimbabwe Road Data for Travel Time Maps 

    Watmough, Gary
    A polyline shapefile of roads in Zimbabwe used for estimating travel times. It was merged from two source datasets (1) Open street map roads and (2) MapwithAI roads.
  • Uganda Travel Time to nearest Level IV health centre & Hospital Map Output 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to level III health facilities in Uganda. Level III facilities typically have Qualified nurses, Nurse aids and Clinical officers (physicians assistants) present withing them. ...
  • Mozambique Land Cover Data for Cost Surface estimation 

    Watmough, Gary
    The ESA CCI Landcover20-m Map for Africa Geotiff file containing 9 land cover types. This was used to create the cost allocation surfaces for the CPAS project. This data set was downloaded from the ESA data portal and ...
  • Tanzania Road Data for Travel Time Maps 

    Watmough, Gary
    A polyline data set of roads used for estimating travel time in Tanzania. The roads have been merged from two source datatsets.
  • Tanzania friction surface 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    The friction (cost allocation/effort) surface was assembled using three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. Landcover data were from ...
  • Mozambique friction surface 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    The friction (cost allocation/effort) surface was assembled using three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. Landcover data were from ...
  • Zimbabwe friction surface 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    The friction (cost allocation/effort) surface was assembled using three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. Landcover data were from ...
  • Zimbabwe Travel Time to nearest hospital Map Output 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to the nearest hospital in Zimbabwe. Hospitals here included mission hospitals, district hospitrals and provincial hospitals, these facilities all have medical doctors present ...
  • Zimbabwe Travel Time to any health facility Map Output 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    A 20 m spatial resolution geotiff of travel time to the nearest of any tyoe of health facility in Zimbabwe. The data was generated using the Child Poverty and Access to Services (CPAS) software (10.5281/zenodo.4638563) and ...
  • Zimbabwe Travel Time to the nearest health clinic Map Output 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    Travel_time_rural_health_centres.jpg (311.6Kb) - jpeg image of the geotiff file to indicate how the map should look once loaded. service_area_Zim_clinics.tif (11.56Gb) - geotiff with 20 m spatial resolution for whole of ...
  • Tanzania travel time to nearest hospital 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    Travel time surface was estimated using the cost allocation (friction surfaces) which used three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. ...
  • Tanzania travel time to nearest health centre 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    Travel time surface was estimated using the cost allocation (friction surfaces) which used three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. ...
  • Tanzania travel time to nearest dispensary 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    Travel time surface was estimated using the cost allocation (friction surfaces) which used three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. ...
  • Mozambique travel time to any health facility 

    Watmough, Gary; Hagdorn, Magnus; Brumhead, Jodie
    Travel time surface was estimated using the cost allocation (friction surfaces) which used three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. ...

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