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
This data has been produced by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. The data provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance. It represents a consolidated evidence base and helps inform joint strategic response planning
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.
"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
This table contains subnational multidimensional poverty trends data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2023).
This dataset contains data obtained from a variety of sources and transformed into a form suitable for driving the Covid-19 Data Explorer. The visual itself is driven by a JSON file which contains the same data as the resources in this dataset which point to published csvs from a Google spreadsheet.
Designated institutions to provide learning spaces and learning environments for the teaching of students. This data has been extracted from GRID3 Nigeria site
This dataset is the result of Displacement Tracking Matrix (DTM) assessments carried out by the International Organization for Migration (IOM), aims to improve the understanding of the scope of return movements in north-east Nigeria.
Data set has IDPs, Households, geographic locations and reasons of displacement etc.
In response to the need for accurate information on internally displaced persons (IDPs) in Nigeria, the International Organization
for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The project is supporting
the Government of Nigeria and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as
to establish a profile of the IDP population.
Nigeria administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
The datasets cover the period of 4 September 2019 - 30 December 2021 and includes the states mostly affected by displacement including Benue,Nasarawa, Kaduna, Kano, Katsina, Plateau, Sokoto and Zamfara.
In response to the need for accurate information on internally displaced persons (IDPs) in Nigeria, the International Organization for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The project is supporting the Government of Nigeria and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as to establish a profile of the IDP population.
To get the complete data of the assessment round, kindly download the corresponding Location Assessment data here: https://data.humdata.org/dataset/nigeria-location-assessment-data.
This dataset contains agency- and open source events published in the Attacks on Health Care News Brief and included in the Safeguarding Health in Conflict Coalition (SHCC) annual reporting on violence against or obstruction of health care. This page is managed by SHCC member Insecurity Insight.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
This dataset contains reported incidents of violence against or obstruction of health care related to vaccination campaigns from 01 January 2016 to date.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
Nigeria administrative level 0-3 edge-matched gazetteer, shapefiles, geodatabase, and geoservice.
These layers are suitable for database or GIS linkage to the Nigeria - Subnational Population Statistics tables.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
The dataset represents the Common Operational Data (COD) for administrative boundaries of Nigeria. Each administrative unit contains the p-code and name. Admin COD datasets (Admin 0 – 2) for Nigeria are endorsed by the Office of the Surveyor General of the Federal Republic of Nigeria (OSGOF) and the IMWG Feb 2017. See metadata for description of methodology for admin level 3 and the cleaning and processing performed by ITOS. Levels 0 - 3 are polygonal administrative units, Level 3 only covers Adamawa, Borno and Yobe States and are for operational purposes only.
A senatorial district shapefile is also included. Senatorial districts respect administrative level 1 (state) but are not reflected in the gazetteer, geodatabase, or live services.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
The administrative level 0-2 and senatorial district boundaries are suitable for database or GIS linkage to the Nigeria - Subnational Population Statistics tables.
A topojson generalized version of administrative level 3 is also provided.
REVISION HISTORY
14 February 2020: Topojson generalized administrative level 3 resource added
More than 200 million businesses use Facebook globally. The goal of Meta’s quarterly Small Business Surveys is to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs).
The Future of Business (FoB) Survey is conducted biannually in partnership with the World Bank and the Organisation for Economic Cooperation and Development (OECD) across nearly 100 countries. The target population consists of SMEs that have an active Facebook Business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. Meta also conducts the Global State of Small Business (GSoSB) Survey bi-annually in partnership with various academic partners across approximately 30 countries. Similarly to the FoB Survey, the target population is active Facebook Page Administrators, but also includes the general population of Facebook users.
Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, international trade, inflation, reduction of employees and challenges/needs of the business.
Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://dataforgood.facebook.com/dfg/tools/future-of-business-survey to apply for access to microdata or contact dataforgood@fb.com for any questions.
The dataset consists of settlement extents across Nigeria, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent.
Updates in this version include:
(1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets
(2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate
(3) Building count ranges have been included
(4) Predicted false positives have been included
(5) Population data have been removed until new constrained population numbers are available
(6) Settlement status has been included, as it pertains to Version 01 of the settlement extents
This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.
This dataset contains COVID-19 vaccine dose availability forecasts as well as actual deliveries for countries with Humanitarian Response Plans. The data on vaccine availability forecasts was manually extracted from the COVAX Facility Interim Distribution Forecast as announced by COVAX on 3 February 2021. Figures for actual deliveries through channels other than COVAX are compiled by OCHA from press reports. The source(s) press releases, official announcements or articles for each such vaccine delivery are included in the dataset.
Education indicators for Nigeria.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
This master list of health facilities was developed from a variety of government and non-government sources from 50 countries in sub-Saharan Africa. It uses multiple geocoding methods to provide a comprehensive spatial inventory of 98 745 public health facilities. Each data record represents a health facility and has 8 descriptive variables – Location identifiers including: country, first level administrative division, latitude, longitude and LL source (source of the coordinates). Coordinates are rounded off to four decimal places for uniformity, allowing an accuracy of 5–10 metres in decimal degrees coordinate format.
This geocoded master facility list has been made publicly and freely available through both the figshare repository and through the World Health Organization’s Global Malaria Programme in Microsoft Excel format.
These document are compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to compile the monitoring framework of the Humanitarian Response Plans in Activated Health Clusteres.
The data comes from humanitarianaction For any ideas, updates, or corrections please contact Alberto Castillo Aroca castilloalb@who.int GHCU-IM Assessment and Analysis IMO or the GHC healthcluster@who.int.
The data used as populations, names, and other designations are used only as a reference and do not imply any endorsement.
The compilation is made by the Global Health Cluster IM team and it is expected to be updated. Not all the fields are available in the reviewed documents and it is expected to be complemented. Please see the version control table in the document
