Nigeria

Data Grid Completeness
80% 
16/20 Core Data 20 Datasets 14 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.
Legend:
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
100% 
Internally-Displaced Persons
International Organization for Migration (IOM)
Refugees & Persons of Concern
UNHCR - The UN Refugee Agency
Returnees
International Organization for Migration (IOM)
Humanitarian Needs
Coordination & Context
5 Datasets
40%  40%  19% 
3w - Who is doing what where
International Aid Transparency Initiative
Funding
OCHA Financial Tracking System (FTS)
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Climatic Hazards
Food Security & Nutrition
3 Datasets
100% 
Acute Malnutrition
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
75%  25% 
Administrative Divisions
Roads
WFP - World Food Programme
Airports
Health & Education
2 Datasets
100% 
Health Facilities
Education Facilities
Population & Socio-economy
2 Datasets
100% 
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 100+ Downloads
    Updated 29 January 2016 | Dataset date: December 31, 2015-December 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.
  • 500+ Downloads
    Updated 8 December 2015 | Dataset date: October 31, 2014-July 31, 2015
    This dataset updates: Never
    Maisha is VoicesAfrica’s online pan Africa study on lifestyle and viewpoints on various aspects of life. The research report covers the following information areas: Income and expenditure • If earn a personal income • Share of wallet • Whether overall expenditure has gone up, down, or remained the same compared to the previous year Values • Determinants of well being • Aspects that have made life better/worse • Threats to self and country Role models • Most admired personality • Part of the world/Africa that offers greatest inspiration and hope Africa unity • If would support the integration of all African countries Technology • Devices used • Device that has made life better/worse • Device that has had greatest influence in life Attitudes • Response to statements on politics, insecurity, family, religion, sports, patriotism, economy, corruption, health, relationships, among others
  • 300+ Downloads
    Updated 25 November 2015 | Dataset date: October 01, 2015-October 01, 2015
    This dataset updates: Never
    Nigeria Admin Level 2 boundaries created by the Bill & Melinda Gates foundation. The boundaries were made by mapping all settlements, and then using the Ward Level 2 admin attributes and the ESRI Thiessen polygons tool to create boundaries at each admin level.
  • 300+ Downloads
    Updated 24 November 2015 | Dataset date: November 01, 2012-November 01, 2012
    This dataset updates: Never
    The dataset represents the extent of floods in Nigeria from July to November 2012.
  • 10+ Downloads
    Updated 14 October 2015 | Dataset date: June 30, 2015-June 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)
  • 30+ Downloads
    Updated 14 October 2015 | Dataset date: March 25, 2015-March 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)
  • 20+ Downloads
    Updated 14 October 2015 | Dataset date: October 01, 2014-October 01, 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)
  • 10+ Downloads
    Updated 14 October 2015 | Dataset date: July 01, 2014-July 01, 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 14 October 2015 | Dataset date: April 01, 2014-April 01, 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 14 October 2015 | Dataset date: January 01, 2014-January 01, 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 14 October 2015 | Dataset date: July 01, 2013-July 01, 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 14 October 2015 | Dataset date: April 01, 2013-April 01, 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 14 October 2015 | Dataset date: January 01, 2013-January 01, 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)
  • 300+ Downloads
    Updated 28 August 2015 | Dataset date: January 01, 2013-April 01, 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/
  • 10+ Downloads
    Updated 10 August 2015 | Dataset date: April 02, 2015-April 02, 2015
    This dataset updates: Never
    This map illustrates satellite-detected shelters and other buildings at the Minawao refugee settlement, Mayo-Tsanaga District, Far North Province, in Cameroon as seen by the WorldView-2 satellite on 10 March 2015. UNOSAT analyzed a total of 5,220 structures (4,027 tent shelters, 903 improvised shelters and 290 administrative buildings) within the 261 hectares of the settlement area. Note that apparently adjoining, contiguous shelters were counted as a single shelter which may thus underestimate total number of shelters. This is a preliminary analysis & has not yet been validated in the field. Please send ground feedback to UNITAR / UNOSAT