Data Grid Completeness
11/27 Core Data 24 Datasets 13 Organisations Show legend
What is Data Grid Completeness?
Data Grid 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 Grid 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
4 Datasets
Internally-Displaced Persons
International Organization for Migration
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
2 Datasets
Food security
Integrated Food Security Phase Classification (IPC)
Global Acute Malnutrition Rate
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
7 Datasets
Administrative Divisions
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
WFP - World Food Programme
Humanitarian OpenStreetMap Team (HOT)
Health & Education
5 Datasets
Health Facilities
Global Healthsites Mapping Project
Humanitarian OpenStreetMap Team (HOT)
Education Facilities
Affected Schools
Population & Socio-economy
2 Datasets
Baseline Population
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 100+ Downloads
    Updated October 6, 2016 | Dataset date: Oct 5, 2016
    This dataset updates: Every day
    Includes Assessment, two shapefiles: basemaps
  • 300+ Downloads
    Updated October 6, 2016 | Dataset date: Sep 30, 2016
    This dataset updates: Never
    This dataset contains the integrated phase classification (IPC) for September 2016, and livelihood zones for Haiti, extracted to each administrative level 3 unit (sections). It also contains the population for each admin 3 unit based on WorldPop (2015 v2b UN adjusted). Source datasets: IPC and Livelihoods Administrative Boundaries (version released 6-Oct-2016)
  • 400+ Downloads
    Updated October 6, 2016 | Dataset date: Sep 28, 2016
    This dataset updates: Never
    Who does what where dataset for Haiti.
  • 100+ Downloads
    Updated October 5, 2016 | Dataset date: Oct 5, 2016
    This dataset updates: Never
    This report illustrates the population exposure to the tropical cyclone Matthew-16 in Haiti, Cuba and Jamaica.
  • 600+ Downloads
    Updated September 23, 2016 | Dataset date: Sep 15, 2016
    This dataset updates: Never
    Epidemiological update on Zika Virus, week of 15 September 2016
  • 300+ Downloads
    Updated August 16, 2016 | Dataset date: Jun 1, 2016-Dec 31, 2016
    This dataset updates: Every three months
    List of projects being developed currently in Haiti in the context of the drought response. The data of this document was collected only for 4 towns, that are considered to be in IPC phase 3 by the National coordination of Food Security (CNSA) The dataset contains the list of projects organized by sectors: Food Security, Agriculture, Nutrition and WASH. The document also contains the estimated populations in need by commune and sector. The caseload for the nutrition projects corresponds only to children under five years old. An analysis document developed with this data is available at: https://goo.gl/NBHRZI
  • 200+ Downloads
    Updated August 5, 2016 | Dataset date: Dec 30, 2010-Mar 31, 2016
    This dataset updates: Never
    Master list of IDPs currently residing in Haiti as of March 2016
  • 100+ Downloads
    Updated August 5, 2016 | Dataset date: Dec 30, 2010-Jun 30, 2016
    This dataset updates: Never
    Master list of IDPs currently residing in Haiti as of June 2016
  • 500+ Downloads
    Updated June 21, 2016 | Dataset date: Apr 21, 2016
    This dataset updates: Every three months
    This dataset contains a list of the countries affected by the El Niño as at April 21, 2016 as reported jointly by FAO, the Global Food Security Cluster and WFP on 21 April 2016 in the 2015-2016 El Niño: WFP and FAO Overview update. According to the World Bank, El Niño is likely to have a negative impact in more isolated local food markets, and many countries are already facing increased food prices. Food Security Cluster partners have implemented preparedness activities and are responding in countries where the effects of El Niño have materialised, such as Ethiopia, Papua New Guinea, Malawi and throughout Central America. In Southern Africa, many areas have seen the driest October-December period since at least 1981, and some 14 million people in the region are already facing hunger, which adds to fears of a spike in the numbers of the food insecure later this year through 2017.
  • 200+ Downloads
    Updated May 5, 2016 | Dataset date: Apr 19, 2016
    This dataset updates: Never
    It is estimated that at least 300,000 Haitian undocumented migrants are residing in the DR remain at risk of deportation. Since 17 June 2015, increased population movements took place due to the end of the expiration date given by the Dominican authorities to irregular migrants to regularize their status in the country (National Plan for the Regularization of Foreigners).
  • 1000+ Downloads
    Updated May 5, 2016 | Dataset date: Apr 1, 2016
    This dataset updates: Never
    Number of registered cases of cholera in Haiti since 2010. Also includes one dataset of number of cases per department and per month between Jan/2015 and Mar/2016
  • 200+ Downloads
    Updated May 5, 2016 | Dataset date: Apr 1, 2016
    This dataset updates: Never
    Who does What and Where in the response to Zika epidemic in Haiti. Data collected by WHO/PAHO
  • 100+ Downloads
    Updated January 29, 2016 | Dataset date: Dec 31, 2015
    This dataset updates: Never
    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.
  • 400+ Downloads
    Updated December 16, 2015 | Dataset date: Dec 4, 2015
    This dataset updates: As needed
    This is the 3W information in Haiti collected for the month of December 2015
  • 800+ Downloads
    Updated November 24, 2015 | Dataset date: May 14, 2015
    This dataset updates: Every month
    The Income Activities dataset includes data on income generation at the household level. Sources of income listed include labor, agriculture, asset sales, and remittances, among others. It is available for 32 countries.
  • 1100+ 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.
  • 1500+ 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.
  • 10+ Downloads
    Updated October 13, 2015 | Dataset date: Jan 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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 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 13, 2015 | Dataset date: Apr 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on May 15, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for April-June 2013 LAC201304_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 October 13, 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: 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)
  • Updated October 13, 2015 | Dataset date: Oct 1, 2013
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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 October 13, 2015 | Dataset date: Jan 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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 October 13, 2015 | Dataset date: Apr 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on April 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: xx201404_ML1 Most likely food security outcome for April-June 2014 xx201404_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 October 13, 2015 | Dataset date: Jul 1, 2014
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. It was last updated on September 30, 2014. The classification used is IPC V2.0 Compatible, aimed to address acute food insecurity. The two shapefiles represent the two analytic periods: LAC201304_ML1 Most likely food security outcome for July-September 2014 LAC201304_ML2 Most likely food security outcome for October-December 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 13, 2015 | Dataset date: Oct 1, 2015
    This dataset updates: Never
    This Archive contains shapefiles for FEWS NET Food Security Outlook for Central America and The Caribbean. 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: LAC201304_ML1 Most likely food security outcome for October-December 2014 LAC201304_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)