Data Datasets [20] | Archived Datasets[0] [?]
Refine your search: Clear all
Featured:
Data series [?]:
More
Locations:
Formats:
More
Organisations:
More
Tags:
More
Licenses:
  • 10+ Downloads
    Time Period of the Dataset [?]: September 27, 2023-March 25, 2024 ... More
    Modified [?]: 25 March 2024
    Dataset Added on HDX [?]: 14 December 2023
    This dataset updates: Every day
    This dataset is part of the data series [?]: IDMC - Internal Displacement Updates
    Resource has no data rows! No conflict and disaster population movement (flows) data recorded for Svalbard and Jan Mayen Islands in the last 180 days. Internally displaced persons are defined according to the 1998 Guiding Principles (https://www.internal-displacement.org/publications/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. The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD), accessible at https://www.internal-displacement.org/database/displacement-data. The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.
  • Time Period of the Dataset [?]: March 05, 2024-March 05, 2024 ... More
    Modified [?]: 5 March 2024
    Dataset Added on HDX [?]: 15 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Railways
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['railway'] IN ('rail','station') Features may have these attributes: name name:en railway ele operator:type layer addr:full addr:city source name:no 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 [?]: 15 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:no 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 [?]: 15 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:no 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 [?]: 15 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:no 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 [?]: 15 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Roads
    OpenStreetMap contains roughly 852 km of roads in this region. Based on AI-mapped estimates, this is approximately 84 % of the total road length in the dataset region. The average age of data for the region is 4 years ( Last edited 15 days ago ) and 17% 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:no 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 [?]: 15 May 2020
    This dataset updates: Every month
    This dataset is part of the data series [?]: HOTOSM - Buildings
    OpenStreetMap contains roughly 2.0 thousand buildings in this region. Based on AI-mapped estimates, this is approximately 100% of the total buildings.The average age of data for this region is 4 years ( Last edited 15 days ago ) and 14% 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:no 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 [?]: 15 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:no 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 [?]: 15 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:no 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 [?]: 15 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:no 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 [?]: 15 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:no 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 [?]: 15 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:no This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 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
    Svalbard and Jan Mayen Islands 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 [?]: July 10, 2023-July 10, 2023 ... More
    Modified [?]: 10 July 2023
    Dataset Added on HDX [?]: 10 July 2023
    This dataset updates: As needed
    This dataset is part of the data series [?]: Kontur - Administrative Division with Aggregated Population
    Svalbard and Jan Mayen Islands 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. Gobal version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
  • 30+ 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.
  • 100+ Downloads
    Time Period of the Dataset [?]: January 01, 1970-December 31, 2012 ... More
    Modified [?]: 21 December 2022
    Dataset Added on HDX [?]: 4 August 2021
    This dataset updates: Every three months
    This dataset is part of the data series [?]: UNESCO - Education Indicators
    Education indicators for Svalbard and Jan Mayen Islands. 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)
  • Time Period of the Dataset [?]: January 01, 2019-March 29, 2024 ... More
    Modified [?]: 4 December 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 Svalbard and Jan Mayen Islands 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
  • 10+ Downloads
    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
  • 10+ 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
  • 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