Data Completeness
11/27 Core Data 36 Datasets 14 Organisations Show legend
What is Data Completeness?
Data Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
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Presence, freshness, and quality of dataset
  • Dataset fully matches criteria and is up-to-date
  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
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Affected People
10 Datasets
Internally-Displaced Persons
International Organization for Migration
Returnees
International Organization for Migration
Humanitarian Profile Locations
International Organization for Migration
UN Operational Satellite Applications Programme (UNOSAT)
UN Operational Satellite Applications Programme (UNOSAT)
UN Operational Satellite Applications Programme (UNOSAT)
Humanitarian Needs
Casualties
Armed Conflict Location & Event Data Project (ACLED)
Coordination & Context
11 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Transportation Status
WFP - World Food Programme
WFP - World Food Programme
Damaged & Destroyed Buildings
Food Security & Nutrition
3 Datasets
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
9 Datasets
Administrative Divisions
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
Humanitarian OpenStreetMap Team (HOT)
WFP - World Food Programme
WFP - World Food Programme
OCHA Sudan
Airports
Health & Education
5 Datasets
Health Facilities
Humanitarian OpenStreetMap Team (HOT)
Global Healthsites Mapping Project
Affected Schools
Population & Socio-economy
3 Datasets
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  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Jun 9, 2011-Jun 9, 2015
    This dataset updates: Never
    This dataset includes the Refugee, IDPs, People in need by Sector, Humanitarian Funding, inform indexes and humanitarian priorites data for countries in the wider horn of Africa Region from 2011 to date
  • 200+ Downloads
    Updated November 24, 2015 | Dataset date: Jan 1, 2015
    This dataset updates: Every year
    INFORM SUB NATIONAL data for Eastern Africa Region. It contains the Hazards/Exposures, Vulnerbilities and Lack of Coping Capacity of the Greater Horn of Africa Region and the Overal Rick Index. The scale is from 0 - 10
  • 1000+ Downloads
    Updated November 24, 2015 | Dataset date: May 14, 2015
    This dataset updates: Never
    The Coping Strategy Index dataset measures the severity and frequency of the strategies that households use to cope with acute food insecurity. The strategies vary from borrowing food or money from neighbors to selling household assets. This data is available for 31 countries at a sub-national level.
  • 1300+ Downloads
    Updated November 24, 2015 | Dataset date: May 13, 2015
    This dataset updates: Every month
    The Food Consumption Score (FCS) dataset is based on the FCS indicator, which assigns a food security score based on food consumption and diets. This data is available sub-nationally for 38 countries, such as Nepal and Sierra Leone.
  • 200+ Downloads
    Updated November 24, 2015 | Dataset date: Mar 9, 2015
    This dataset updates: Every three months
    Data on funding to 2011-2014 response plans in Djibouti, Kenya, Somalia, South Sudan, Sudan and Ethiopia.
  • 200+ Downloads
    Updated November 24, 2015 | Dataset date: Jan 26, 2015
    This dataset updates: Every three months
    Data on people in need per sector in Kenya, Somalia, Sudan, South Sudan and Ethiopia from 2011 to 2015
  • 300+ Downloads
    Updated November 24, 2015 | Dataset date: Aug 6, 2014
    This dataset updates: Every three months
    IDP numbers in Burundi, Djibouti, DRC, Eritrea, Ethiopia, Kenya, Rwanda, S.Sudan, Somalia, Sudan, Tanzania and Uganda since December 2007.
  • 400+ Downloads
    Updated November 24, 2015 | Dataset date: Aug 7, 2007
    This dataset updates: Every three months
    Refugee numbers in Burundi, Djibouti, DRC, Eritrea, Ethiopia, Kenya, Rwanda, S.Sudan, Somalia, Sudan, Tanzania and Uganda since December 2007.
  • 2100+ Downloads
    Updated November 19, 2015 | Dataset date: Dec 31, 2010
    This dataset updates: Every three months
    The Darfur Damaged and Destroyed Villages dataset describes the condition of villages in the Darfur region of Sudan that the U.S. Government has confirmed as either damaged or destroyed between the time period February 2003 to December 2010. Additionally, villages that are confirmed to have No Damage are also reported.
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Sep 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: easternafrica201507_ML1 Most likely food security outcome for July-September 2015 easternafrica201507_ML2 Most likely food security outcome for October-December 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Jun 30, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on June 30, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for April-June 2015 eastafrica201304_ML2 Most likely food security outcome for July-September 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Apr 3, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on April 03, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2015 eastafrica201304_ML2 Most likely food security outcome for April-June 2015 Where xx is one of the region codes listed above. Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 30+ Downloads
    Updated October 14, 2015 | Dataset date: Oct 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on December 31, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: EA201304_ML1 Most likely food security outcome for October-December 2014 EA201304_ML2 Most likely food security outcome for January-March 2015 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on September 26, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for July-September 2014 eastafrica201304_ML2 Most likely food security outcome for October-December 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 17, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on July 17, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for April-June 2014 eastafrica201304_ML2 Most likely food security outcome for July-September 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Jan 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on August 07, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2014 eastafrica201304_ML2 Most likely food security outcome for April-June 2014 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Nov 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on November 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for October-December 2013 eastafrica201304_ML2 Most likely food security outcome for January-March 2014 Where xx is one of the region codes listed above. Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 20+ Downloads
    Updated October 14, 2015 | Dataset date: Jul 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on July 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for July-September 2013 eastafrica201304_ML2 Most likely food security outcome for October-December 2013 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated October 14, 2015 | Dataset date: Jan 14, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for East Africa. It was last updated on January 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: eastafrica201304_ML1 Most likely food security outcome for January-March 2013 eastafrica201304_ML2 Most likely food security outcome for April-June 2013 Within the shapefiles, the food security outlook is contained in a field named as ML1 or ML2 according to the outlook period. The code itself is the IPC phase. Two additional codes are used: 66 = water 88 = parks, forests, reserves 99 = missing data (usually urban centers)
  • 10+ Downloads
    Updated August 10, 2015 | Dataset date: Aug 20, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the Pleiades satellite on 19 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Um Baba and Khartoum Bahri seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum has decreased slightly in some areas, however there also appears to be an increase in others. This increase is potentially saturated soils and not necessarily standing water. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT
  • Updated August 10, 2015 | Dataset date: Aug 19, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the Pleiades satellite on 14 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Um Baba and Khartoum Bahri seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum has decreased slightly in some areas, however the higher resolution of the Pleiades shows more smaller standing bodies of water that were likely overlooked by previous sensors. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT
  • 10+ Downloads
    Updated August 10, 2015 | Dataset date: Aug 11, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the TerraSAR-X satellite on 10 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City was inundated by floods caused by heavy rains. The area to the northeast of Khartoum City is affected by varying levels of water and/or saturated soils. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • Updated August 10, 2015 | Dataset date: Aug 11, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected in satellite imagery acquired by the TerraSAR-X satellite on 09 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Umdaba and East Nile seem to be affected by varying levels of water and saturated soils. The flooded area over Khartoum city has decreased slightly since the previous analysis using an image from 8 August 2014. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • Updated August 10, 2015 | Dataset date: Aug 8, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of flood affected land as detected by RADARSAT-2 imagery acquired 08 August 2014 in Khartoum State, Sudan. The area surrounding Khartoum City and Umdurman was inundated by floods caused by heavy rains. Areas to the South of Umdurman seem to have been flooded and many other areas including Umdaba and East Nile seem to suffer from waters and/or muds. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks, and within built-up urban areas because of the characteristics of the satellite data used. This analysis has not yet been validated in the field. Please send ground feedback to UNITAR /UNOSAT.
  • 10+ Downloads
    Updated August 10, 2015 | Dataset date: Jul 21, 2014
    This dataset updates: Never
    This map illustrates satellite-detected structures at Um Gargour refugee camp in Al Qadrif province, Sudan as seen on 05 January 2014 by the WorldView-2 satellite. This camp lies 58 km North-East from Al Qadarif city and 90 km South New Halfa. UNOSAT analyzed a total of 4,471 structures in the 206 ha of the camp. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.