Data Completeness
6/27 Core Data 13 Datasets 9 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
2 Datasets
Internally-Displaced Persons
Refugees & Persons of Concern
Returnees
Humanitarian Profile Locations
Humanitarian Needs
Casualties
Armed Conflict Location & Event Data Project (ACLED)
Coordination & Context
4 Datasets
3w - Who is doing what where
Affected Areas
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Transportation Status
WFP - World Food Programme
Damaged & Destroyed Buildings
Food Security & Nutrition
1 Datasets
Food security
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
Administrative Divisions
Populated Places
Roads
Airports
Health & Education
3 Datasets
Health Facilities
Global Healthsites Mapping Project
Education Facilities
Affected Schools
Population & Socio-economy
0 Datasets
Baseline Population
Baseline Population by Age & Sex
Poverty Rate
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  • 500+ Downloads
    Updated November 24, 2015 | Dataset date: Nov 3, 2014
    This dataset updates: Every year
    Data sourced from official Government of Ethiopia publication. More information about the data is available on the metadata of the attached datasheet.
  • 600+ Downloads
    Updated November 24, 2015 | Dataset date: Mar 3, 2014
    This dataset updates: Never
    Data has been sourced from the 2012 Inter-Censual Population Survey (ICPS) for Ethiopia.More information about the data is available on the metadata of the attached datasheet.
  • 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)
  • 10+ 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)
  • 10+ 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)
  • 10+ 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)
  • 10+ 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)