Ukraine

Data Grid Completeness
75% 
12/16 Core Data 15 Datasets 10 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
Affected People
4 Datasets
75%  25% 
Internally-Displaced Persons
International Organization for Migration (IOM)
Refugees & Persons of Concern
UNHCR - The UN Refugee Agency
Returnees
International Organization for Migration (IOM)
Coordination & Context
4 Datasets
60%  20%  20% 
3w - Who is doing what where
Funding
OCHA Financial Tracking System (FTS)
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Climate Impact
Food Security & Nutrition
1 Datasets
100% 
Food security
Not applicable
Acute Malnutrition
Not applicable
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
100% 
Administrative Divisions
OCHA Field Information Services Section (FISS)
Populated Places
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
Health & Education
0 Datasets
100% 
Health Facilities
Not available
Education Facilities
Not available
Population & Socio-economy
2 Datasets
100% 
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 10+ Downloads
    Time Period of the Dataset [?]: October 03, 2019-April 30, 2020 ... More
    Modified [?]: 21 December 2021
    Dataset Added on HDX [?]: 31 January 2022
    This dataset updates: Never
    This report covers the finding of the post-execution monitoring of 433 houses repaired by UNHCR in the frame of the 2019 shelter programme in the east of Ukraine. The monitoring visits took place between October 2019 and April 2020, and were performed by teams composed of at least two members, one from the shelter team and one from the protection unit. The form has two main sections, one focusing on technical aspects, the other on protection. A few changes to the questionnaire were introduced in 2019, mainly to capture the feedback on cash based interventions; all changes, though, comply with the principle of preserving the comparability of data and findings across the implementation years. The monitored sample covers repairs completed in the geographic areas of four of the five UNHCR offices in eastern Ukraine: Mariupol, Sloviansk and Sievierodonetsk in governmentcontrolled areas (GCA); and Donetsk in non government-controlled areas (NGCA). Last year, Luhansk office in NGCA was not allowed to implement field visits and therefore could not contribute to the 20192 monitoring exercise. The 433 monitoring visits on which this report is based represent 33 per cent of the 1,316 repairs conducted in 2019 by UNHCR, in line with last year’s already satisfactory achievement.
  • Time Period of the Dataset [?]: September 03, 2018-March 31, 2019 ... More
    Modified [?]: 21 December 2021
    Dataset Added on HDX [?]: 31 January 2022
    This dataset updates: Never
    This report covers the finding of the post-execution monitoring of 464 houses repaired by UNHCR in the frame of the 2018 shelter programme in the east of Ukraine. The monitoring visits took place between September 2018 and March 2019, and were performed by teams composed of at least two members, one from the shelter team and one from the protection unit. The monitored sample covers repairs completed in the geographic areas of all five UNHCR offices in eastern Ukraine (Mariupol, Sloviansk and Sievierodonetsk in government-controlled areas [GCA]; Donetsk and Luhansk in non-government-controlled areas [NGCA]). The 464 monitoring visits on which this report is based represent 34% of the 1,374 repairs conducted in 2018 by UNHCR: a significant improvement compared to the 13% covered in the 2017 shelter monitoring exercise (232 visits out of 1,732 repairs conducted). The monitoring of 2018 shelter activities confirms the main findings of the 2017 campaign: the repair of houses damaged by conflict-related incidents is still highly appreciated by recipients (95% of respondents, compared to 97% in 2017) and is executed with good quality (99% of cases, compared to 100% in 2017).
  • Time Period of the Dataset [?]: December 01, 2017-August 31, 2018 ... More
    Modified [?]: 21 December 2021
    Dataset Added on HDX [?]: 31 January 2022
    This dataset updates: Never
    This dataset covers the finding of the post-execution monitoring of 232 houses repaired by UNHCR in the frame of the 2017 shelter programme in the east of Ukraine. The monitoring visits took place between December 2017 and August 2018, and were performed by teams composed by at least two members, one from the Shelter team and one from the Protection unit. The monitored sample covers all five UNHCR offices in the field (Mariupol, Sloviansk and Severodonetsk in Government Controlled Areas (GCA); Donetsk and Luhansk in non Government Controlled Areas (NGCA)). The 232 monitoring visits included in the report represent 13% of the 1.732 repairs conducted in 2017 by UNHCR. The number of monitoring visits conducted corresponds to approximately one-third of the target recommended by the SOPs (607 visits, or 35% of the total number of repairs). The monitoring of 2017 shelter activities confirms that shelter assistance - in terms of repair of houses damaged by conflict-related activities - is highly appreciated by the recipients and is generally executed with good quality. The consistent quality is related to the fact that it is easy to find construction companies and brigades with sufficient expertise, and the technology involved is basic and repetitive.
  • 10+ Downloads
    Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 12 October 2021
    Dataset Added on HDX [?]: 17 October 2021
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey
    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
    Time Period of the Dataset [?]: January 01, 2019-March 28, 2024 ... More
    Modified [?]: 10 September 2021
    Dataset Added on HDX [?]: 14 February 2019
    This dataset updates: Live
    This dataset is part of the data series [?]: IATI - Current IATI aid activities
    Live list of active aid activities for Ukraine 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
  • 10000+ Downloads
    Time Period of the Dataset [?]: January 01, 1990-August 15, 2021 ... More
    Modified [?]: 22 August 2021
    Dataset Added on HDX [?]: 15 April 2015
    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.
  • 400+ Downloads
    Time Period of the Dataset [?]: January 01, 2020-March 28, 2024 ... More
    Modified [?]: 22 July 2021
    Dataset Added on HDX [?]: 25 June 2020
    This dataset updates: Every year
    The data shows key figures on Education in Emergencies (EiE) at country level and as reported by country clusters
  • 20+ Downloads
    Time Period of the Dataset [?]: October 01, 2020-November 30, 2020 ... More
    Modified [?]: 17 June 2021
    Dataset Added on HDX [?]: 31 January 2022
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Post-Distribution Monitoring of Cash-Based Intervention
    UNHCR conducts post-distribution monitoring (PDM) on a regular basis for assistance activities in order to deepen its understanding of the impact these activities have on the persons the organization assists and provides protection to. In Ukraine, UNHCR provides individual protection assistance in the following regions: Kyiv, Odesa, Zakarpattya (also covers Lviv) and Kharkiv regions. The UNHCR Cash-Based Interventions (CBI) support only vulnerable refugees and asylum-seekers. The type of assistance vary depending on the needs and vulnerability of persons of concern. the following types of CBI assistance that were provided to refugees and asylum-seekers by UNHCR and its Partners in Ukraine in 2020: 1. Supplementary assistance and newcomers assistance - Modality: voucher (Metro cards, a supermarket chain that partners with UNHCR) - Available only in Kyiv and Odesa - Description: Distribution of vouchers (Metro cards) for food and non-food items to refugees and asylum-seekers who meet established vulnerability criteria (newcomers, PoCs in need of supplementary food or hygiene due to medical condition). In 2020, 121 families residing in Kyiv and Odesa received voucher assistance at least once. In 2020 UNHCR used Metro Cash&Carry (big supermarket chain) cards in the value of 500 UAH. However, due to COVID-19 quarantine restrictions imposed by the government of Ukraine, UNHCR Ukraine has gradually shifted to provision of these types of assistance through other modalities. This PDM focused only on the cases processed through vouchers. MSA (Monthly Subsistence Allowance) Modality: cash. OTC (over the counter) Available in Kyiv, Odesa, Kharkiv Description: MSA (monthly subsistence allowance) aims to support the most vulnerable persons of concern. It is given based on the strict vulnerability criteria and cases are reviewed every four months at the MSA committee meetings, composed of partner social counselors, SMS and UNHCR. In 2020, 105 vulnerable families were covered by this type of support. The amount of MSA is calculated based on the family size. It is in line with the recommendations of the Cash Working Group on assistance provision at 60% of subsistence level (3 774.62 UAH as of February 2020), which corresponds to MSA amount. Assistance per single person provided by UNHCR amounted to 2 400 UAH per month, proportionally increased depending on the number of household members.
  • 300+ Downloads
    Time Period of the Dataset [?]: March 01, 2020-December 31, 2020 ... More
    Modified [?]: 15 April 2021
    Dataset Added on HDX [?]: 15 April 2021
    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.
  • Time Period of the Dataset [?]: January 01, 2018-December 31, 2018 ... More
    Modified [?]: 10 April 2021
    Dataset Added on HDX [?]: 11 April 2021
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey
    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
  • Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More
    Modified [?]: 10 April 2021
    Dataset Added on HDX [?]: 11 April 2021
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey
    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
  • 400+ Downloads
    Time Period of the Dataset [?]: November 20, 2020-November 20, 2020 ... More
    Modified [?]: 4 March 2021
    Dataset Added on HDX [?]: 20 November 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.
  • 200+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 16 September 2020
    Dataset Added on HDX [?]: 20 July 2017
    This dataset updates: Every year
    This dataset is part of the data series [?]: World Pop - Population Counts
    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
  • 400+ Downloads
    Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 4 September 2020
    Dataset Added on HDX [?]: 26 May 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
    Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 2 September 2020
    Dataset Added on HDX [?]: 22 July 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
  • 433000+ Downloads
    Time Period of the Dataset [?]: January 22, 2020-March 09, 2023 ... More
    Modified [?]: 28 July 2020
    Dataset Added on HDX [?]: 7 February 2020
    This dataset updates: As needed
    JHU Has Stopped Collecting Data As Of 03/10/2023 After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations. The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics. Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on Github. Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths. On 23/03/2020, a new data structure was released. The current resources for the latest time series data are: time_series_covid19_confirmed_global.csv time_series_covid19_deaths_global.csv time_series_covid19_recovered_global.csv ---DEPRECATION WARNING--- The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020: time_series_19-covid-Confirmed.csv time_series_19-covid-Deaths.csv time_series_19-covid-Recovered.csv
  • 300+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 22 June 2020
    Dataset Added on HDX [?]: 24 November 2020
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Population Density
    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
    Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 6 May 2020
    Confirmed [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
    This dataset updates: Every year
    This data contains the number of people in need, internally displaced persons (IDPs), returnees and refugees for 25 countries.
  • 300+ Downloads
    Time Period of the Dataset [?]: March 26, 2020-March 26, 2020 ... More
    Modified [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
    This dataset updates: As needed
    Data on unmitigated(no intervention) COVID-19 scenarios for OCHA HRP countries. Simulation done by Imperial College London.
  • 200+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 1 November 2018
    Dataset Added on HDX [?]: 27 May 2019
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Age and sex structures
    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. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. 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/WP00646
  • 100+ Downloads
    Time Period of the Dataset [?]: January 01, 1950-December 31, 2050 ... More
    Modified [?]: 28 September 2018
    Dataset Added on HDX [?]: 28 September 2018
    This dataset updates: Every year
    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.