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  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Health Facilities
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['healthcare'] IS NOT NULL OR tags['amenity'] IN ('doctors', 'dentist', 'clinic', 'hospital', 'pharmacy') Features may have these attributes: name name:en amenity building healthcare healthcare:speciality operator:type capacity:persons addr:full addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Financial Services
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: name name:en amenity operator network addr:full addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Waterways
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay') Features may have these attributes: name name:en waterway covered width depth layer blockage tunnel natural water source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Airports
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['aeroway'] IS NOT NULL OR tags['building'] = 'aerodrome' OR tags['emergency:helipad'] IS NOT NULL OR tags['emergency'] = 'landing_site' Features may have these attributes: name name:en aeroway building emergency emergency:helipad operator:type capacity:persons addr:full addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Roads
    OpenStreetMap contains roughly 1.1 thousand km of roads in this region. Based on AI-mapped estimates, this is approximately 97 % of the total road length in the dataset region. The average age of data for the region is 1 year, 13 days ( Last edited 26 days ago ) and 6% of roads were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['highway'] IS NOT NULL Features may have these attributes: name name:en highway surface smoothness width lanes oneway bridge layer source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Buildings
    OpenStreetMap contains roughly 11.5 thousand buildings in this region. Based on AI-mapped estimates, this is approximately 74% of the total buildings.The average age of data for this region is 1 year, 13 days ( Last edited 26 days ago ) and 1% buildings were added or updated in the last 6 months. Read about what this summary means : indicators , metrics OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['building'] IS NOT NULL Features may have these attributes: name name:en building building:levels building:materials addr:full addr:housenumber addr:street addr:city office source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Points of Interest
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IS NOT NULL OR tags['man_made'] IS NOT NULL OR tags['shop'] IS NOT NULL OR tags['tourism'] IS NOT NULL Features may have these attributes: name name:en amenity man_made shop tourism opening_hours beds rooms addr:full addr:housenumber addr:street addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Populated Places
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['place'] IN ('isolated_dwelling', 'town', 'village', 'hamlet', 'city') Features may have these attributes: name name:en place population is_in source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Sea Ports
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] = 'ferry_terminal' OR tags['building'] = 'ferry_terminal' OR tags['port'] IS NOT NULL Features may have these attributes: name name:en amenity building port operator:type addr:full addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 13 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Education Facilities
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university') Features may have these attributes: name name:en amenity building operator:type capacity:persons addr:full addr:city source name:it This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 200+ Downloads
    Time Period of the Dataset [?]: January 01, 1998-December 31, 2010 ... More
    Modified [?]: 1 March 2024
    Dataset Added on HDX [?]: 30 July 2020
    This dataset updates: Every six months
    This dataset is part of the data series [?]: UNHCR - Data on forcibly displaced populations and stateless persons
    Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across more than 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).
  • 100+ Downloads
    Time Period of the Dataset [?]: January 01, 2018-December 31, 2021 ... More
    Modified [?]: 7 February 2024
    Dataset Added on HDX [?]: 29 April 2020
    This dataset updates: Every year
    This dataset is part of the data series [?]: UNDP Human Development Reports Office - Human Development Indicators
    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'.
  • Time Period of the Dataset [?]: July 10, 2023-November 01, 2023 ... More
    Modified [?]: 31 October 2023
    Dataset Added on HDX [?]: 30 June 2022
    This dataset updates: As needed
    This dataset is part of the data series [?]: Kontur - Population Density for 400m H3 Hexagons
    San Marino 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.
  • Time Period of the Dataset [?]: April 07, 2022-April 07, 2022 ... More
    Modified [?]: 10 July 2023
    Dataset Added on HDX [?]: 15 April 2022
    This dataset updates: As needed
    This dataset is part of the data series [?]: Kontur - Administrative Division with Aggregated Population
    San Marino administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata. Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
  • 2900+ Downloads
    Time Period of the Dataset [?]: August 02, 2021-March 28, 2024 ... More
    Modified [?]: 29 May 2023
    Dataset Added on HDX [?]: 21 April 2020
    This dataset updates: As needed
    This dataset is part of the data series [?]: HDX - COVID-19 Subnational Cases
    This dataset contains the number of confirmed cases, recoveries and deaths by country and subnational region due to the Coronavirus pandemic in Europe. Since the outbreak of the COVID-19 crisis, the Joint Research Centre (JRC) has been supporting the European Commission in multidisciplinary areas to understand the COVID-19 emergency, anticipate its impacts, and support contingency planning. This data provides an overview of the monitoring in the area of the 34 UCPM Participating States plus Switzerland related to sub-national data (admin level 1) on numbers of contagious and fatalities by COVID-19, collected directly from the National Authoritative sources (National monitoring websites, when available). The sub-national granularity of the data allows to have a fit-for-purpose model to early capture the local spread and response to the COVID-19 outbreak. The data is maintained on the JRC COVID-19 Github Repository
  • 40+ Downloads
    Time Period of the Dataset [?]: January 01, 2021-December 31, 2021 ... More
    Modified [?]: 17 April 2023
    Dataset Added on HDX [?]: 30 May 2022
    This dataset updates: Every year
    This dataset is part of the data series [?]: IDMC - Internally displaced persons
    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.
  • 400+ Downloads
    Time Period of the Dataset [?]: January 01, 1970-December 31, 2019 ... More
    Modified [?]: 21 December 2022
    Dataset Added on HDX [?]: 3 April 2020
    This dataset updates: Every three months
    This dataset is part of the data series [?]: UNESCO - Education Indicators
    Education indicators for San Marino. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
  • 4000+ Downloads
    Time Period of the Dataset [?]: September 21, 2020-September 21, 2020 ... More
    Modified [?]: 14 January 2022
    Dataset Added on HDX [?]: 22 September 2020
    This dataset updates: As needed
    This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The 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. Researchers and nonprofits interested in access to survey microdata can apply at: https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
  • 80+ Downloads
    Time Period of the Dataset [?]: December 31, 2021-December 31, 2021 ... More
    Modified [?]: 31 December 2021
    Dataset Added on HDX [?]: 28 October 2020
    This dataset updates: Every day
    This dataset is part of the data series [?]: OCHA FTS - Requirements and Funding Data
    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.
  • Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 16 September 2020
    Dataset Added on HDX [?]: 27 May 2019
    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
  • 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
  • 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
  • 900+ Downloads
    Time Period of the Dataset [?]: September 19, 2019-September 19, 2019 ... More
    Modified [?]: 5 March 2020
    Dataset Added on HDX [?]: 21 September 2019
    This dataset updates: As needed
    The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in San Marino: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
  • 20+ 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
  • Time Period of the Dataset [?]: January 01, 2008-March 28, 2024 ... More
    Modified [?]: 20 October 2017
    Dataset Added on HDX [?]: 2 June 2014
    This dataset updates: Live
    This dataset is part of the data series [?]: Our Airports - Airports
    List of airports in San Marino, with latitude and longitude. Unverified community data from http://ourairports.com/countries/SM/