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  • 80+ Downloads
    Updated 27 February 2021 | Dataset date: January 01, 1960-December 31, 2019
    This dataset updates: Every month
    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Aid effectiveness is the impact that aid has in reducing poverty and inequality, increasing growth, building capacity, and accelerating achievement of the Millennium Development Goals set by the international community. Indicators here cover aid received as well as progress in reducing poverty and improving education, health, and other measures of human welfare.
  • 70+ Downloads
    Updated 27 February 2021 | Dataset date: January 01, 1960-December 31, 2019
    This dataset updates: Every month
    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.
  • 1300+ Downloads
    Updated 26 February 2021 | Dataset date: September 21, 2020-September 21, 2020
    This dataset updates: Every year
    This data contains aggregated weighted statistics at the regional level by gender for the Survey on Gender Equality At Home fielded in July 2020. Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. If you're interested in becoming a Survey on Gender Equality research partner, please email gendersurvey@fb.com.
  • 40+ Downloads
    Updated 26 February 2021 | Dataset date: January 01, 1997-April 12, 2021
    This dataset updates: Never
    The Armed Conflict Location & Event Data Project (ACLED) is a disaggregated data collection, analysis, and crisis mapping project. ACLED collects the dates, actors, locations, fatalities, and types of all reported political violence and protest events across Africa, the Middle East, Latin America & the Caribbean, East Asia, South Asia, Southeast Asia, Central Asia & the Caucasus, Europe, and the United States of America. This dataset contains information on the specific dates and locations of political violence, the types of event, the groups involved, fatalities and changes in territorial control. Information is recorded on the battles, killings, riots, and recruitment activities of rebels, governments, militias, armed groups, protesters and civilians. Data can be used for medium- and long-term analysis and mapping of political violence across developing countries through use of historical data from 1997, as well as informing humanitarian and development work in crisis and conflict-affected contexts through realtime data updates and reports. Despite the waning of civil wars across the developing world, ACLED data show that political violence rates have remained relatively stable in the past eighteen years. ACLED seeks to support research and work devoted to understanding, predicting and reducing levels of violence and their consequences.
  • 400+ Downloads
    Updated 14 January 2021 | Dataset date: January 14, 2021-January 14, 2021
    This dataset updates: Every month
    This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long
  • 200+ Downloads
    Updated 12 January 2021 | Dataset date: January 01, 2011-June 30, 2020
    This dataset updates: Every six months
    Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across almost 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns).
  • 3700+ Downloads
    Updated 31 December 2020 | Dataset date: December 31, 2020-December 31, 2020
    This dataset updates: Every day
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
  • 200+ Downloads
    Updated 16 December 2020 | Dataset date: January 01, 1970-December 31, 2019
    This dataset updates: Every three months
    Education indicators for Antigua and Barbuda. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: National Monitoring (made 2020 September), SDG 4 Global and Thematic (made 2020 September), Demographic and Socio-economic (made 2020 September)
  • Updated 23 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 3 and 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. 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
  • 20+ Downloads
    Updated 23 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. 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
  • 90+ Downloads
    Updated 27 September 2020 | Dataset date: January 01, 1990-December 31, 2005
    This dataset updates: Every month
    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For countries with an active poverty monitoring program, the World Bank—in collaboration with national institutions, other development agencies, and civil society—regularly conducts analytical work to assess the extent and causes of poverty and inequality, examine the impact of growth and public policy, and review household survey data and measurement methods. Data here includes poverty and inequality measures generated from analytical reports, from national poverty monitoring programs, and from the World Bank’s Development Research Group which has been producing internationally comparable and global poverty estimates and lines since 1990.
  • 10+ Downloads
    Updated 22 September 2020 | Dataset date: September 01, 2017-September 30, 2017
    This dataset updates: Never
    The dataset contains number of IDPs!
  • 346000+ Downloads
    Updated Live | Dataset date: January 22, 2020-April 11, 2021
    This dataset updates: Live
    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
  • 10+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: network addr:city source amenity name addr:full operator This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 40+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: rooms addr:housenumber man_made addr:city source tourism amenity addr:street name addr:full beds shop opening_hours This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: railway IN ('rail','subway','station') Features may have these attributes: layer addr:city source ele name operator:type addr:full railway This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 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: port addr:city source amenity name operator:type addr:full building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy') Features may have these attributes: addr:city source amenity healthcare:speciality name capacity:persons operator:type healthcare addr:full building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 50+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: building:levels addr:housenumber addr:city source building:materials addr:street name office addr:full building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university') Features may have these attributes: addr:city source amenity name capacity:persons operator:type addr:full building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 60+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: layer blockage water depth source tunnel waterway name natural width covered This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 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: addr:full addr:city source emergency:helipad name capacity:persons operator:type aeroway emergency building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: highway layer source lanes smoothness name width bridge surface oneway This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 30+ Downloads
    Updated 4 July 2020 | Dataset date: April 02, 2021-April 02, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: place IN ('isolated_dwelling','town','village','hamlet','city') Features may have these attributes: source is_in name population place This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Updated 29 June 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. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. The 'Unconstrained global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. These are produced using the unconstrained top-down modelling method. 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