Data Completeness
5/26 Core Data 16 Datasets 11 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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  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
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Affected People
2 Datasets
Coordination & Context
5 Datasets
Food Security & Nutrition
2 Datasets
Health & Education
1 Datasets
Population & Socio-economic Indicators
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  • 200+ Downloads
    Updated November 24, 2016 | Dataset date: Apr 17, 2016
    This dataset updates: Never
    African Regional Energy Statistics, 2000 - 2014
  • 80+ Downloads
    Updated October 14, 2016 | Dataset date: Jul 1, 2016
    This dataset updates: Never
    CAR Shapefile Contour line - Equidistant 10m
  • 300+ Downloads
    Updated May 23, 2016 | Dataset date: Jan 1, 2006-Dec 31, 2015
    This dataset updates: Never
    Total migrants in Africa.
  • 200+ Downloads
    Updated May 19, 2016 | Dataset date: Jan 1, 2010-Dec 31, 2015
    This dataset updates: Never
    1-3. Economically active population - Population active
  • 100+ Downloads
    Updated May 12, 2016 | Dataset date: Jun 1, 2010-Dec 31, 2015
    This dataset updates: Never
    Population Urban and female population percentages Population urbain et feminine (%)
  • 20+ Downloads
    Updated March 21, 2016 | Dataset date: Jan 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West 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: xx201304_ML1 Most likely food security outcome for January-March 2013 xx201304_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 March 21, 2016 | Dataset date: Apr 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on June 14, 2013. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201304_ML1 Most likely food security outcome for April-June 2013 xx201304_ML2 Most likely food security outcome for July-September 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)
  • Updated March 21, 2016 | Dataset date: Jul 1, 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: xx201304_ML1 Most likely food security outcome for July-September 2013 xx201304_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)
  • Updated March 21, 2016 | Dataset date: Oct 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West 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: xx201304_ML1 Most likely food security outcome for October-December 2013 xx201304_ML2 Most likely food security outcome for January-March 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)
  • Updated March 21, 2016 | 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 January 19, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201401_ML1 Most likely food security outcome for January-March 2014 xx201401_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)
  • Updated March 21, 2016 | Dataset date: Apr 1, 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: WA201304_ML1 Most likely food security outcome for April-June 2014 WA201304_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)
  • Updated March 21, 2016 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on September 29, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: WA201304_ML1 Most likely food security outcome for July-September 2014 WA201304_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)
  • 10+ Downloads
    Updated March 21, 2016 | Dataset date: Oct 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on November 13, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: WA201304_ML1 Most likely food security outcome for October-December 2014 WA201304_ML2 Most likely food security outcome for January-March 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)
  • The data shows the ground and Satellite-Based Damage Assessment in Western CAR (2013-2014) Human Rights Watch ground and satellite-based damage assessment of 790 villges and towns in western Central African Republic (CAR) covering the period from April 2013 to April 2014. A total of 125 villages had identified building destruction related to the conflict, with a total of over 17,500 mostly destroyed residential buildings.
  • The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.
  • 20+ Downloads
    Updated November 25, 2015 | Dataset date: Oct 21, 2015
    This dataset updates: Never
    This map illustrates satellite-detected IDP shelters and administrative buildings in M'Poko Airport in Bangui, Central African Republic using satellite images acquired on 4 October 2015 and 6 June 2014. As of 6 June 2014 3,254 structures were detected. Imagery from 4 October 2015 shows a decrease in the number of tent shelters present inside of the airport. As of 6 June UNOSAT detected a total of approximately 2,578 tent shelters and 148 camp infrastructure building. Compared to previous UNOSAT analysis the number of shelters has decreased by 19.3%. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT..
  • 10+ Downloads
    Updated November 25, 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: westafrica201304_ML1 Most likely food security outcome for July-September 2015 westafrica201304_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)
  • 10+ Downloads
    Updated November 25, 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: westafrica201304_ML1 Most likely food security outcome for April-June 2015 westafrica201304_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)
  • 10+ Downloads
    Updated November 25, 2015 | Dataset date: Mar 25, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for West Africa. It was last updated on March 25, 2015. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: westafrica201304_ML1 Most likely food security outcome for January-March 2015 westafrica201304_ML2 Most likely food security outcome for April-June 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)
  • This map illustrates locations of destroyed structures in the area of Marcounda Sub-Prefecture in the Central African Republic. Using satellite images acquired 21 June, 23 June & 7 July 2014, UNOSAT reviewed almost 4,500 square kilometers of Marcounda to locate signs of destroyed structures. An estimated 3,840 damaged structures are visible across 50 distinct locations in the sub-prefecture. Destruction in many cases was likely due to arson based on appearance of structural remains. In addition, it appears violence and destruction continued between 21 June and 7 July, and heavy rains apparently caused significant damage to structures as well. Overall, UNOSAT estimates that approximately 40% of structures in Marcounda Sub-Prefecture have been completely destroyed and many others are likely damaged to some degree. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • Updated November 24, 2015 | Dataset date: Jul 2, 2014
    This dataset updates: Never
    This map illustrates locations of destroyed structures within the arrondissements of Bangui, Central African Republic. Using satellite imagery acquired 16 November 2013, 22 February 2014, and 6 June 2014 UNOSAT reviewed the city of Bangui to locate signs of destroyed structures. By 22 February 2014, a total of 1,872 structures were destroyed in the area of Bangui, with 1,341 structures detected in the 8 arrondissements and an additional 531 located in the surrounding area. As of 6 June 2014 a total of 368 damaged structures have been reconstructed and 871 additional structures have been severely damaged or destroyed since 22 February 2014. Pre-crisis imagery used for this analysis was collected on 16 November 2013, and thus structures destroyed previous to 16 November 2013 are not indicated on this map. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • This map illustrates satellite-detected IDP shelters and administrative buildings in M'Poko Airport in Bangui, Central African Republic using satellite images acquired on the 20 January, 22 February and 6 June 2014. As of 22 February 2014 approximately 7,789 structures were detected. Imagery from 6 June shows an important decrease in the number of tent shelters present inside of the airport since an extensive area has been significantly cleared of shelters. As of 6 June UNOSAT detected a total of approximately 3193 tent shelters and 61 administrative support and other structures. Compared to previous UNOSAT analysis the number of shelters has decreased by 58.7%. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • This map illustrates locations of destroyed structures in the area of Paoua, Central African Republic. Using a satellite image acquired 18 June 2014 and compared to an image from 12 January 2012, UNOSAT reviewed the town of Paoua and surrounding areas to locate obvious signs of destroyed structures (see inset for example). An estimated total of 323 destroyed structures were located in the area as well as 25 possible damage structures, both in Paoua and in outlying towns and villages. The destroyed structures comprise an estimated 2.2% of the total number of pre-conflict structures in Paoua.Most destruction detected in the 18 June image was most likely a result of burning given the blackened structural remains visible in the imagery. This is a preliminary analysis and has not yet been validated in the field.
  • 10+ Downloads
    Updated November 24, 2015 | Dataset date: Jun 19, 2014
    This dataset updates: Never
    This map illustrates satellite-detected areas of likely refugee populations in Sido village, Moyen - Chari Region, Republic of Chad, as seen by the WorldView-1 and WorldView-2 satellites on 29 January 2014 and 13 June 2014. As of 29 January, fleeing outbreaks of violence in the Central African Republic, refugees had established a primary settlement area in the central portion of Sido village and along the primary road. As of that date, the camp included approximately 543 improvised shelters and 200 tent shelters. As of 13 June 2014 approximately 2,731 tent shelters and new housing structures, 798 improvised shelters or small huts, and 1,255 tukuls or large huts were detected within and around Sido village. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.
  • This map illustrates satellite-detected areas of a refugee settlement in Sido village, southern Chad as seen by the WorldView-1 satellite on 29 January 2014. Fleeing outbreaks of violence in the Central African Republic, refugees have established a settlement in a portion of Sido village. Note that the camp occupied areas include 543 improvised shelters and 200 tent shelters approximately. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT.