Data Completeness
15/27 Core Data 19 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
3 Datasets
Internally-Displaced Persons
Refugees & Persons of Concern
Returnees
Humanitarian Profile Locations
Humanitarian Needs
Casualties
Armed Conflict Location & Event Data Project (ACLED)
Coordination & Context
5 Datasets
3w - Who is doing what where
Affected Areas
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Transportation Status
Damaged & Destroyed Buildings
Food Security & Nutrition
3 Datasets
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
Administrative Divisions
Populated Places
Roads
OCHA Mali
Airports
OurAirports
Health & Education
3 Datasets
Health Facilities
Global Healthsites Mapping Project
Education Facilities
Humanitarian OpenStreetMap Team (HOT)
Affected Schools
Population & Socio-economy
2 Datasets
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  • Updated October 14, 2015 | 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)
  • 10+ Downloads
    Updated October 14, 2015 | 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)
  • 30+ Downloads
    Updated October 14, 2015 | 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)
  • 400+ Downloads
    Updated August 28, 2015 | Dataset date: Nov 19, 2014
    This dataset updates: Every year
    This dataset contains a link to a Google Spreadsheet containing lists of the health facilities (including the facility name, status, facility type, location etc) in Guinea, Liberia, Mali and Sierra Leone. The data was compiled by the Standby Task Force from various sources.
  • 200+ Downloads
    Updated August 28, 2015 | Dataset date: Jan 1, 2013-Apr 1, 2014
    This dataset updates: Never
    Here we provide version 1 Flowminder (www.flowminder.org) human mobility models for West Africa, together with WorldPop population density data for the region, to support ongoing efforts to control the ebola outbreak. Before downloading any data, please read the documention carefully as it provides details on the datasets and models provided through the links below. The mobility data refer to estimated patterns before the Ebola outbreak and should be interpreted with caution for Ebola affected countries as mobility patters are known to have changed. Additional discussion by the authors around the use of mobile operator data for epidemilogical research see: http://currents.plos.org/outbreaks/article/containing-the-ebola-outbreak-the-potential-and-challenge-of-mobile-network-data/