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 dataset contains agency- and publicly-reported data for events in which an aid worker was killed, injured, kidnapped, or arrested (KIKA). Categorized by country.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
This dataset is an extraction of roads and streets networks from OpenStreetMap database for use in GIS applications.
The data is updated every month and include all latest updates.
Resources:
Ukraine Roads Network (main roads)
Ukraine streets and pathways
The data set provides the number of participants enrolled in four free online courses as of February 13, 2024. The courses are designed to support early childhood educators, primary school teachers, and practical psychologists in Ukraine.
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'.
The CoRA employs a multi-sectoral location-level assessment (MSLA) methodology conducted with local authority key informants at the settlement or city-raion level.
The assessment is based on 20 indicators divided into five ‘drivers’:
(1) livelihoods,
(2) utilities and services
(3) residential destruction,
(4) safety and security, and
(5) public life.
The indicators describe the critical or minimum conditions required for sustainable return and reintegration in Ukraine. The scores of each indicator and driver are grouped into three categories: low, medium, and high severity of living conditions.
For more information on the methodology, please refer to the full report. When requesting the dataset, please specify if you would like to receive the report as well.
1) The dataset is produced by the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) in collaboration with humanitarian partners. It presents the number of people in need (PiN), the severity of those needs, the activities of the planned response, and the number of people to be targeted for humanitarian assistance in Ukraine as explained the 2024 Humanitarian Needs and Response Plan (HNRP).
2) The interpretation and use of this data should be guided by the 2024 Ukraine Humanitarian Needs and Response Plan.
3) The data sources and methodology for the derivation of the PIN and severity is explained in Annex 4.2 of the Ukraine 2024 HNRP, "Analysis Methodology & Data Sources", which also includes the description and sources of the baseline population estimates.
This dataset gives cases of provision of free secondary legal aid to clients in accordance with the Criminal Procedure Code of Ukraine and the Code of Ukraine on Administrative Offenses. It also gives general information on client appeals to the free legal aid system in Ukraine.
This dataset contains a pre-/post- satellite imagery damage assessment of every cross-corroborated medical facility in Mariupol from 6/21/2021 - 7/13/2022. Medical facility data was obtained from Google Maps, Open Street Map, the Ukrainian Healthcare Center, and Wikimapia. Commercially available satellite imagery was sourced from Maxar Technologies and Planet Labs.
This document is compiled by the Information Management team in the Global Health Cluster Unit GHCU, and aims to gather the figures relevant to Humanitarian Health response at global levels. The information is collected from the last available data from publicly validated sources. See detailed info below. The data is mainly compiled from HRP and follows the structure of the Global Humanitarian Overview.
For any ideas, updates, or corrections please contact GHCU-IMU at 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 expected to be updated. Not all the fields are available in the reviewed documents, and it is expected to be complemented.
This dataset contains publicly-reported cases of sexual violence by conflict actors, security personnel, and sexual violence violence that targets aid workers, educators, health workers and IDPS/refugees.
Please get in touch if you are interested in curated datasets.
Ukraine population density for 400m H3 hexagons.
Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.
Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.
The COVID-19 preventative health survey is designed to help policymakers and health researchers better monitor and understand people’s knowledge, attitudes and practices about COVID-19 to improve communications and their response to the pandemic.
This dataset contains the list of voyages completed under the Black Sea Grain Initiative. Data on the Black Sea Grain Initiative vessel movements covers the period 1 August 2022 - 17 July 2023. The Initiative was not renewed after its third term, which expired on 17 July 2023.
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.
To ensure the centrality of IDP’ voices in discussions about their future, as well as to inform evidence-based inter-agency responses in support of the Government of Ukraine, UNHCR is leads the regular implementation of intentions surveys with IDPs and refugees from Ukraine, collecting primary data on their profiles, their current situation and intentions, and the factors influencing their decision-making.
The first round of intentions surveys among IDPs in Ukraine was completed and the report published in February 2023 (https://data.unhcr.org/en/documents/details/99164). This data was collected during the second round, conducted in May 2023, in parallel to the fourth round of the refugees' intentions surveys. A joint report was published in July 2023 (https://reporting.unhcr.org/ukraine-lives-hold-intentions-and-perspectives-refugees-and-idps).
This data is an anonymous version of the original data collected and used for the primary analysis.
This dataset contains layers ESRI ArcGIS Online feature services for the following layers of interest to the logistics cluster in Ukraine:
- Entry and exit points
- Ports
- Supply routes
- Roads
- Railways
- Reception points
- Roads in Poland
