Nigeria

Data Grid Completeness
85% 
17/20 Core Data 21 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
6 Datasets
60%  40% 
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)
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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  • 400+ Downloads
    Updated 24 November 2016 | Dataset date: August 20, 2016-August 20, 2016
    This dataset updates: Never
    AFDB Commodity Prices, Monthly January 1960 - July 2016
  • 400+ Downloads
    Updated 24 November 2016 | Dataset date: October 12, 2015-October 12, 2015
    This dataset updates: Never
    AFDB Market Trends, January 2011 - July 2015
  • 500+ Downloads
    Updated 24 November 2016 | Dataset date: April 17, 2016-April 17, 2016
    This dataset updates: Never
    African Regional Energy Statistics, 2000 - 2014
  • 700+ Downloads
    Updated 24 November 2016 | Dataset date: July 15, 2015-July 15, 2015
    This dataset updates: Never
    The AfDB Statistics Department and the Fragile States Unit have compiled this data set from various sources (the World Bank, WHO, IMF, and many others)
  • 500+ Downloads
    Updated 24 November 2016 | Dataset date: July 08, 2016-July 08, 2016
    This dataset updates: Never
    African Financial Survey Database, 2005-2014
  • 400+ Downloads
    Updated 24 November 2016 | Dataset date: August 22, 2013-August 22, 2013
    This dataset updates: Never
    Economic Community of Central African States Statistics, 2013
  • 300+ Downloads
    Updated 24 November 2016 | Dataset date: April 22, 2014-April 22, 2014
    This dataset updates: Never
    AfDB Country Policy and Institutional Assessment, 2013
  • 200+ Downloads
    Updated 24 November 2016 | Dataset date: December 08, 2011-December 08, 2011
    This dataset updates: Never
    African Development Bank, Food Security, January 1960 - December 2011
  • 300+ Downloads
    Updated 24 November 2016 | Dataset date: December 08, 2011-December 08, 2011
    This dataset updates: Never
    African Development Bank, Food Security, Prices, Monthly, January 1980 - December 2011
  • 500+ Downloads
    Updated 24 November 2016 | Dataset date: July 16, 2013-July 16, 2013
    This dataset updates: Never
    African Port Statistics, 2005-2009
  • 50+ Downloads
    Updated 31 October 2016 | Dataset date: October 26, 2016-October 26, 2016
    This dataset updates: Never
    This map illustrates satellite-detected areas of displaced persons shelters in the Sangaya settlement, Borno state, Nigeria, and in the surrounding town of Dikwa. UNITAR-UNOSAT analysis of satellite imagery acquired 29 September 2016 revealed a total of 433 shelters and 54 infrastructure and support buildings within the Sangaya compound and a total of 2,259 shelters scattered in the surrounding town. A density analysis has been performed to highlight the most dense shelters areas (Sangaya settlement included), ranging from 400 to 10,500 shelters per square kilometer. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
  • 500+ Downloads
    Updated 7 October 2016 | Dataset date: August 23, 2016-September 22, 2016
    This dataset updates: Never
    Nigeria Child Protection 5W - September 2016
  • 300+ Downloads
    Updated 7 October 2016 | Dataset date: October 07, 2016-October 07, 2016
    This dataset updates: Never
    A vector based map showing three administrative levels in the Northern Nigeria
  • 700+ Downloads
    Updated 12 September 2016 | Dataset date: July 23, 2016-August 22, 2016
    This dataset updates: Never
    Child Protection Sub-Sector working group (CPSWG) - Who is doing what, where,when and for whom (5W) – August 2016
  • 800+ Downloads
    Updated 19 August 2016 | Dataset date: June 23, 2016-July 22, 2016
    This dataset updates: Never
    Nigeria Child Protection Sector 5W - July 2016
  • 800+ Downloads
    Updated 28 July 2016 | Dataset date: May 23, 2016-June 22, 2016
    This dataset updates: Never
    Nigeria, Child Protection 5W for month of June 2016
  • 20+ Downloads
    Updated 8 March 2016 | Dataset date: February 25, 2016-February 25, 2016
    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 19 November 2015. UNOSAT analysed a total of 11,777 structures (9,390 tent shelters, 551 administrative buildings, 634 improvised shelters, and 1,202 semi-permanent shelters) within 502 hectares of the settlement area. Previous analysis from 10 March 2015 indicated 5, 220 shelters over 261 hectares and thus the updated analysis indicates an increase of approximately 126% on shelters and 93% in land occupied. 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.
  • 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.
  • 400+ 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.
  • 800+ Downloads
    Updated 24 November 2015 | Dataset date: April 02, 2015-April 02, 2015
    This dataset updates: Never
    Ebola outbreak time series data at national and sub national levels since March 2014. Data compiled manually from a number of published reports. Updated by OCHA ROWCA every working day.
  • 50+ Downloads
    Updated 14 October 2015 | Dataset date: September 30, 2015-September 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 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)
  • 20+ 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)