Data Grid Completeness
85% 
18/21 Core Data 20 Datasets 12 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
6 Datasets
50%  33%  16% 
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Transportation Status
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% 
Populated Places
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
Humanitarian OpenStreetMap Team (HOT)
Health & Education
2 Datasets
100% 
Health Facilities
Education Facilities
OCHA Afghanistan
Population & Socio-economy
2 Datasets
100% 
Baseline Population
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 20+ Downloads
    Updated 11 July 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    At the end of 2015, Herat Province was among the highest IDP hosting provinces in Afghanistan, accounting for approximately 10% of the country's IDP population. In order to obtain reliable information on the socio-economic conditions of IDPs and returnees in Herat Province, a comprehensive sample survey was carried out among 11,264 households in the 5 most populated IDP/returnee settlements (Shagofan, Jebraiel, Maslakh, Now Abad and Kahdistan) in 2017.
  • 100+ Downloads
    Updated 4 July 2021 | Dataset date: July 29, 2020-November 30, 2020
    This dataset updates: As needed
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
  • 10+ Downloads
    Updated 23 June 2021 | Dataset date: June 20, 2020-January 29, 2022
    This dataset updates: Every three months
    View the column descriptions here: https://hqfao.maps.arcgis.com/sharing/rest/content/items/9d44fdf00fde4213950e8da771163ea7/data The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries. This project is supported by the United States Agency for International Development (USAID). The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During each round of the system, more than 40,000 interviews have been completed in more than 20 countries. In order to associate each round of data collection with the dates it was performed, refer to the calendar available here: https://covid-19-data-hqfao.hub.arcgis.com/pages/rounds_calendar Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC. The present layer contains data aggregated on Admin1 level, from Afghanistan, Colombia, DRC, Liberia, Mali, Niger, Sierra Leone, Somalia, Yemen and Zimbabwe. Indicator: Percentage of households reporting needs of assistance
  • 300+ Downloads
    Updated 14 June 2021 | Dataset date: January 01, 2021-March 31, 2021
    This dataset updates: As needed
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 1600+ Downloads
    Updated 30 May 2021 | Dataset date: January 01, 2008-December 31, 2020
    This dataset updates: Every year
    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. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" 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.
  • 2000+ Downloads
    Updated 9 May 2021 | Dataset date: January 01, 2020-December 27, 2020
    This dataset updates: As needed
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 60+ Downloads
    Updated 8 May 2021 | Dataset date: May 19, 2020-May 19, 2020
    This dataset updates: As needed
    Pool fund Extended allocation Details
  • 300+ 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.
  • 400+ 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'.
  • 10+ Downloads
    Updated 4 May 2021 | Dataset date: May 05, 2014-May 05, 2014
    This dataset updates: Never
    This is "Flood vectors - Komsat-2 (05 May 2014)" of the Flood analysis for Afghanistan which began on 30 April 2014. It includes 536 satellite detected water bodies with a spatial extent of 3.52 square kilometers derived from the Komsat-2 image acquired o...
  • 7800+ Downloads
    Updated 30 April 2021 | Dataset date: January 01, 2016-December 31, 2020
    This dataset updates: As needed
    The Safeguarding Health in Conflict Coalition (SHCC) is made up of 40 health provider organizations, humanitarian groups, human rights organizations, NGOs, and academic programs to take action to protect health workers and end attacks against them. This page is managed by SHCC member Insecurity Insight.
  • 1100+ Downloads
    Updated 20 April 2021 | Dataset date: April 01, 2016-June 30, 2016
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 700+ Downloads
    Updated 20 April 2021 | Dataset date: April 01, 2017-June 30, 2017
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 900+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2017-March 31, 2017
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 900+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2016-March 31, 2016
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 500+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2021-December 31, 2021
    This dataset updates: Every year
    Afghanistan administrative levels 0 (country), and 1 (province) population statistics. REFERENCE YEAR: 2021 estimates based on 2017 study conducted by Flowminder/UNFPA. Dataset updated by OCHA in 2021. The gazetteer is compatible with the Afghanistan - Subnational Administrative Boundaries gazetteer. (COD-AB boundaries are unavailable.)
  • 300+ Downloads
    Updated 18 April 2021 | Dataset date: October 01, 2020-December 31, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 500+ Downloads
    Updated 18 April 2021 | Dataset date: January 01, 2020-March 31, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 200+ Downloads
    Updated 18 April 2021 | Dataset date: April 01, 2020-June 30, 2020
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 300+ Downloads
    Updated 18 April 2021 | Dataset date: July 01, 2020-September 30, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 200+ 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 Livelihoods 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. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org
  • 100+ Downloads
    Updated 7 April 2021 | Dataset date: March 12, 2021-March 12, 2021
    This dataset updates: As needed
    Compilation of international financial institution and economic data
  • 2400+ Downloads
    Updated 30 March 2021 | Dataset date: January 01, 2020-December 30, 2020
    This dataset updates: As needed
    Newly displaced population due to conflict between 01 January 2020 and 30 December 2020, compiled by OCHA sub offices based on inter-agency assessment results. This data is a snapshot as of 30 Mar 2021 and the numbers are expected to change as new assessment figures become available.
  • 100+ Downloads
    Updated 22 March 2021 | Dataset date: May 01, 2017-March 31, 2022
    This dataset updates: As needed
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.