Data Grid Completeness
60%  35% 
12/20 Core Data 19 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
3 Datasets
100% 
Internally-Displaced Persons
International Organization for Migration (IOM)
Refugees & Persons of Concern
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% 
Food security
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
100% 
Administrative Divisions
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
OCHA Yemen
Airports
Health & Education
2 Datasets
50%  50% 
Health Facilities
Education Facilities
Population & Socio-economy
2 Datasets
100% 
Baseline Population
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 200+ Downloads
    Updated 14 December 2021 | Dataset date: October 07, 2021-October 15, 2022
    This dataset updates: Every year
    This table contains subnational multidimensional poverty 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 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
  • 100+ Downloads
    Updated Live | Dataset date: January 01, 2019-September 26, 2022
    This dataset updates: Live
    Live list of active aid activities for Yemen shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
  • 10+ Downloads
    Updated 17 October 2021 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: Never
    The UNHCR Energy Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches and consultations with Government, Private Sector, field-based staff and NGO partners to devise a set of common, standardized measures rooted in global good practices. More info is available on the official website: https://eis.unhcr.org/
  • 13000+ Downloads
    Updated 22 August 2021 | Dataset date: January 01, 1990-August 15, 2021
    This dataset updates: Never
    This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 3100+ Downloads
    Updated 4 August 2021 | Dataset date: January 01, 1970-December 31, 2019
    This dataset updates: Every three months
    Education indicators for Yemen. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: National Monitoring (made 2021 March), SDG 4 Global and Thematic (made 2021 March), Demographic and Socio-economic (made 2021 March)
  • 400+ Downloads
    Updated 22 July 2021 | Dataset date: January 01, 2020-September 26, 2022
    This dataset updates: Every year
    The data shows key figures on Education in Emergencies (EiE) at country level and as reported by country clusters
  • 1700+ Downloads
    Updated 18 July 2021 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    Food Security Indicators for Yemen. Contains data from the FAOSTAT bulk data service.
  • 100+ Downloads
    Updated 2 July 2021 | Dataset date: July 02, 2021-September 26, 2022
    This dataset updates: Every year
    Affected Schools July 2021 updated
  • 90+ Downloads
    Updated 11 June 2021 | Dataset date: April 30, 2021-April 30, 2021
    This dataset updates: Every month
    The Civilian Impact Monitoring Project (CIMP) is a monitoring mechanism for real-time collection, analysis and dissemination of open source data on the civilian impact from armed violence in Yemen, with the purpose of informing and complementing protection programming. CIMP is a service under the United Nations Protection Cluster for Yemen and, since going live on 01 August 2018, has reported in real-time on the impact of incidents of armed violence on civilians at the national level, divided into 5 hubs: Al-Hudaydah, Sa’ada, Sana’a, Aden and Ibb. The dataset shows the number of incidents to have impacted upon civilian houses, farms, vehicles, businesses and markets and the number of incidents to have impacted upon civilian infrastructure sites since December 2017.
  • 80+ Downloads
    Updated 11 June 2021 | Dataset date: December 01, 2017-April 01, 2021
    This dataset updates: Every month
    The Civilian Impact Monitoring Project (CIMP) is a monitoring mechanism for real-time collection, analysis and dissemination of open source data on the civilian impact from armed violence in Yemen, with the purpose of informing and complementing protection programming. CIMP is a service under the United Nations Protection Cluster for Yemen and, since going live on 01 August 2018, has reported in real-time on the impact of incidents of armed violence on civilians at the national level, divided into 5 hubs: Al-Hudaydah, Sa’ada, Sana’a, Aden and Ibb. The dataset contains the total number of incidents of armed violence reported to have impacted upon civilians each month since December 2017, and the total number of civilian casualties reported each month and per hub.
  • 400+ Downloads
    Updated 6 May 2021 | Dataset date: January 01, 2016-December 31, 2020
    This dataset updates: As needed
    This dataset contains events where air- and ground-launched explosive weapons affected health facilities between 2016 and 2020.
  • 500+ Downloads
    Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    This dataset updates: Every year
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
  • 300+ Downloads
    Updated 15 April 2021 | Dataset date: March 01, 2020-December 31, 2020
    This dataset updates: Every three months
    Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
  • Updated 11 April 2021 | Dataset date: January 01, 2019-December 31, 2019
    This dataset updates: Never
    The UNHCR Energy Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches and consultations with Government, Private Sector, field-based staff and NGO partners to devise a set of common, standardized measures rooted in global good practices. More info is available on the official website: https://eis.unhcr.org/
  • 60+ Downloads
    Updated 6 April 2021 | Dataset date: May 05, 2020-May 05, 2020
    This dataset updates: Never
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
  • 300+ Downloads
    Updated 4 March 2021 | Dataset date: November 20, 2020-November 20, 2020
    This dataset updates: As needed
    Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
  • 15000+ Downloads
    Updated 11 February 2021 | Dataset date: February 01, 2019-September 26, 2022
    This dataset updates: Every year
    This dataset is a standardized and enhanced Common Operational Dataset. Administrative boundary datasets for levels 0, 1, 2 and 3 (international, governorate, district and sub-district) for Yemen approved for use by Humanitarian Country Team in October 2019. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID. Admin Level 1= Governorate = Mohafadha Admin Level 2 = District = Modeeriyyah Admin Level 3 = Sub-district = Ozlah P-codes are those used by Yemen Central Statistical Organization ( CSO ). "YE" is added as a prefix for the codes. Point layers are created by the calculating the centroids of the polygons.
  • 1300+ Downloads
    Updated 7 January 2021 | Dataset date: November 01, 2020-November 01, 2020
    This dataset updates: Every year
    List of health facilities in Yemen by health facility type - Updated September 2020
  • 200+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
  • 500+ Downloads
    Updated 24 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
  • 300+ Downloads
    Updated 4 September 2020 | Dataset date: August 31, 2020-August 31, 2020
    This dataset updates: As needed
    The new and emerging access constraints that people are currently experiencing because of the COVID-19 outbreak.
  • 100+ Downloads
    Updated 2 September 2020 | Dataset date: August 31, 2020-August 31, 2020
    This dataset updates: Every two weeks
    This dataset contains scores for humanitarian access constraints into country, constraints within country, impacts the constraints have led to as well as the mitigation strategies in place to limit the impact. The scores have the following interpretations: 0 = NA, 1 = No or open, 2 = partially open/closed, 3 = Yes or closed
  • 1200+ Downloads
    Updated 2 September 2020 | Dataset date: August 01, 2015-May 01, 2020
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated 14 July 2020 | Dataset date: December 30, 2021-December 30, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site' Features may have these attributes: operator:type name emergency source addr:full building emergency:helipad capacity:persons aeroway addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 14 July 2020 | Dataset date: December 30, 2021-December 30, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL Features may have these attributes: operator:type name source port addr:full building amenity addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.