World

Refine your search: Clear all
Featured:
Locations:
More
Formats:
More
Organisations:
More
Tags:
More
Licenses:
More
  • 2200+ Downloads
    Updated Live | Dataset date: Dec 1, 2019-Jul 12, 2020
    This dataset updates: Live
    Data Overview This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Metabiota at info@metabiota.com to obtain a commercial use license. The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source. The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag. Data are collected, structured, and validated by Metabiota’s digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report. This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Metabiota maintains a database of epidemiological information for over two thousand high-priority infectious disease events. Please contact us (info@metabiota.com) if you are interested in licensing the complete dataset. Cumulative vs. Non-Cumulative Incidence Reporting sources provide either cumulative incidence, non-cumulative incidence, or both. If the source only provides a non-cumulative incidence value, the cumulative values are inferred using prior reports from the same source. Use the CUMULATIVE FLAG variable to subset the data to cumulative (TRUE) or non-cumulative (FALSE) values. Case Confirmation Status The incidence datasets include the confirmation status of cases and deaths when this information is provided by the reporting source. Subset the data by the CONFIRMATION_STATUS variable to either TOTAL, CONFIRMED, SUSPECTED, or PROBABLE to obtain the data of your choice. Total incidence values include confirmed, suspected, and probable incidence values. If a source only provides suspected, probable, or confirmed incidence, the total incidence is inferred to be the sum of the provided values. If the report does not specify confirmation status, the value is included in the "total" confirmation status value. The data provided under the "Metabiota Composite Source" often does not include suspected incidence due to inconsistencies in reporting cases and deaths with this confirmation status. Outcome - Cases vs. Deaths The incidence datasets include cases and deaths. Subset the data to either CASE or DEATH using the OUTCOME variable. It should be noted that deaths are included in case counts. Spatial Resolution Data are provided at multiple spatial resolutions. Data should be subset to a single spatial resolution of interest using the SPATIAL_RESOLUTION variable. Information is included at the finest spatial resolution provided to the original epidemic report. We also aggregate incidence to coarser geographic resolutions. For example, if a source only provides data at the province-level, then province-level data are included in the dataset as well as country-level totals. Users should avoid summing all cases or deaths in a given country for a given date without specifying the SPATIAL_RESOLUTION value. For example, subset the data to SPATIAL_RESOLUTION equal to “AL0” in order to view only the aggregated country level data. There are differences in administrative division naming practices by country. Administrative levels in this dataset are defined using the Google Geolocation API (https://developers.google.com/maps/documentation/geolocation/). For example, the data for the 2019-nCoV from one source provides information for the city of Beijing, which Google Geolocations indicates is a “locality.” Beijing is also the name of the municipality where the city Beijing is located. Thus, the 2019-nCoV dataset includes rows of data for both the city Beijing, as well as the municipality of the same name. If additional cities in the Beijing municipality reported data, those data would be aggregated with the city Beijing data to form the municipality Beijing data. Sources Data sources in this repository were selected to provide comprehensive spatiotemporal data for each outbreak. Data from a specific source can be selected using the SOURCE variable. In addition to the original reporting sources, Metabiota compiles multiple sources to generate the most comprehensive view of an outbreak. This compilation is stored in the database under the source name “Metabiota Composite Source.” The purpose of generating this new view of the outbreak is to provide the most accurate and precise spatiotemporal data for the outbreak. At this time, Metabiota does not incorporate unofficial - including media - sources into the “Metabiota Composite Source” dataset. Quality Assurance Data are collected by a team of digital surveillance experts and undergo many quality assurance tests. After data are collected, they are independently verified by at least one additional analyst. The data also pass an automated validation program to ensure data consistency and integrity. NonCommercial Use License Creative Commons License Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) This is a human-readable summary of the Legal Code. You are free: to Share — to copy, distribute and transmit the work to Remix — to adapt the work Under the following conditions: Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial — You may not use this work for commercial purposes. Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one. With the understanding that: Waiver — Any of the above conditions can be waived if you get permission from the copyright holder. Public Domain — Where the work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license. Other Rights — In no way are any of the following rights affected by the license: Your fair dealing or fair use rights, or other applicable copyright exceptions and limitations; The author's moral rights; Rights other persons may have either in the work itself or in how the work is used, such as publicity or privacy rights. Notice — For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to this web page. For details and the full license text, see http://creativecommons.org/licenses/by-nc-sa/3.0/ Liability Metabiota shall in no event be liable for any decision taken by the user based on the data made available. Under no circumstances, shall Metabiota be liable for any damages (whatsoever) arising out of the use or inability to use the database. The entire risk arising out of the use of the database remains with the user.
  • 600+ Downloads
    Updated July 13, 2020 | Dataset date: Jul 13, 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. Glide Id=EP-2020-000012-001, Date=2020-01-30T16:23:01.558Z
  • Updated July 12, 2020 | Dataset date: May 5, 2020
    This dataset updates: Every day
    Living Atlas live feed sources for hurricane path, observed path, forecast path, and intensity of tropical cyclone activity (hurricanes, typhoons, cyclones) from the National Hurricane Center and Joint Typhoon Warning Center
  • 70+ Downloads
    Updated Live | Dataset date: May 1, 2019-Dec 31, 2020
    This dataset updates: Live
    This dataset combines two sources of education-insecurity data: Machine-learning-driven counts of tweets from Africa and the Middle East on the topic of education insecurity—in Arabic, English, and French—via the Artificial Intelligence for Disaster Response (AIDR) project Human-curated reports of actual education-insecurity events in Africa and the Middle East, via the Armed Conflict Location & Event Data (ACLED) project.
  • 70+ Downloads
    Updated July 10, 2020 | Dataset date: May 29, 2019
    This dataset updates: Every day
    Reference historic FX rates quoted by the European Central Bank (ECB) converted to USD base currency. There are two resources - one with USD as the quote currency (more standard x/USD) and another with USD as the base currency (USD/x). Note that where the rate is 0 or NaN, it means that the currency existed in the past but no longer exists.
  • 20+ Downloads
    Updated July 10, 2020 | Dataset date: Jun 25, 2020
    This dataset updates: Every week
    Raw Global 3W national data visualized in the Global Humanitarian Operational Presence Who, What, Where (3W) Portal as of 10 July 2020 Fields: 'Country_Code' -- example 'UKR' for Ukraine 'Sector' -- example 'CCCM' = Camp Coordination / Management 'Org_name' -- Organization name. Note these are not verified, cleaned, or standardized. 'Org_acr' -- Organization acronym. Note these are not verified, cleaned, or standardized. 'Org_type' -- INGO (International NGO), NNGO (National NGO), UN (United Nations), 'Undefined', or 'Other' 'COVID_19' -- 'yes' / 'no' (pertaining to the context) '3w_month_year' -- date of data applicability Users with questions are encouraged to use the 'Contact the contributor' button below.
  • 3700+ Downloads
    Updated July 9, 2020 | Dataset date: Jan 8, 2020-Jul 9, 2020
    This dataset updates: Every day
    Coronavirus COVID-19 daily new and cumulative cases and deaths by country.
  • 3300+ Downloads
    Updated July 9, 2020 | Dataset date: Mar 10, 2020-Jul 9, 2020
    This dataset updates: Every day
    This data has been collected from various sources and is displayed in this online dashboard: http://arcg.is/uHyuO Mobile version: http://arcg.is/0q8Xfj The data is divided in two datasets: COVID-19 restrictions by country: This dataset shows current travel restrictions. Information is collected from various sources: IATA, media, national sources, WFP internal or any other. COVID-19 airline restrictions information: This dataset shows restrictions taken by individual airlines or country. Information is collected again from various sources including WFP internal and public sources. The data displayed is a collaborative effort and anybody with more accurate/updated information is highly encouraged to contact WFP GIS unit for Emergencies at the following email address: hq.gis@wfp.org
  • 600+ Downloads
    Updated July 9, 2020 | Dataset date: Jul 9, 2020
    This dataset updates: Every week
    Understanding gender is essential to understanding the risk factors of poor health, early death and health inequities. The COVID-19 outbreak is no different. At this point in the pandemic, we are unable to provide a clear answer to the question of the extent to which sex and gender are influencing the health outcomes of people diagnosed with COVID-19. However, experience and evidence thus far tell us that both sex and gender are important drivers of risk and response to infection and disease. In order to understand the role gender is playing in the COVID-19 outbreak, countries urgently need to begin both collecting and publicly reporting sex-disaggregated data. At a minimum, this should include the number of cases and deaths in men and women. In collaboration with CNN, Global Health 50/50 began compiling publicly available sex-disaggregated data reported by national governments to date and is exploring how gender may be driving the higher proportion of reported deaths in men among confirmed cases so far. For more, please visit: http://globalhealth5050.org/covid19
  • 12000+ Downloads
    Updated July 9, 2020 | Dataset date: Mar 17, 2020
    This dataset updates: As needed
    The #COVID19 Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic. Data collection includes secondary data review. The researched information available falls into five categories: Social distancing Movement restrictions Public health measures Social and economic measures Lockdowns Each category is broken down into several types of measures. ACAPS consulted government, media, United Nations, and other organisations sources. For any comments, please contact us at info@acaps.org Please note note that some measures together with non-compliance policies may not be recorded and the exact date of implementation may not be accurate in some cases, due to the different way of reporting of the primary data sources we used.
  • 100+ Downloads
    Updated July 5, 2020 | Dataset date: Jul 10, 2020
    This dataset updates: Every week
    This dataset lists all contributions made by donors to the Central Emergency Response Fund (CERF). CERF receives broad support from United Nations Member States, observers, regional governments and international organizations, and the private sector, including corporations, non-governmental organizations and individuals.
  • 80+ Downloads
    Updated July 3, 2020 | Dataset date: May 31, 2020
    This dataset updates: Every two weeks
    Aggregated figures for Natural Disasters in EM-DAT More on the EM-DAT database : ( website / data portal ). Each line corresponds to a given combination of year, country, disaster subtype and reports figures for : number of disasters total number of people affected total number of deaths economic losses (original value and adjusted)
  • 20+ Downloads
    Updated July 3, 2020 | Dataset date: Jul 2, 2020
    This dataset updates: Every six months
    United Nations office for the Coordination of Humanitarian Affairs office locations
  • Updated July 2, 2020 | Dataset date: May 6, 2020
    This dataset updates: Every day
    This includes layers for detectable thermal activity from VIIRS satellites for the last 7 days and MODIS satellites for the last 48 hours. VIIRS Thermal Hotspots and Fire Activity is a product of NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) Earth Observation Data, while MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), both a part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World. The application includes live feed sources for US wildfire reports (I-209), perimeters, MODIS hot spots, wildfire conditions / red flag warnings, wildfire potential and weather radar. Each of these layers provides insight into where a fire is located, its intensity and the surrounding areas susceptibility to wildfire.
  • Updated July 2, 2020 | Dataset date: May 6, 2020
    This dataset updates: Every day
    Live feed sources on severe weather across the United States. The Current Weather and Wind Station Data layer is created from hourly METAR station data provided from NOAA and contains approximately 11 weather variables for each location.
  • 700+ Downloads
    Updated July 1, 2020 | Dataset date: Jun 26, 2020
    This dataset updates: Every two weeks
    The current outbreak of COVID-19 has affected global mobility in the form of various travel disruptions, restrictions and blockages. To better understand how COVID-19 affects global mobility, the International Organization for Migration (IOM) has been working to map the impacts on human mobility, at Global, Regional and Country level. Using direct input from IOM missions, this dashboard displays updated mobility restrictions at location level (airport, land border points, sea border points, internal transit points). For each point of entry, data is collected on: type of restriction, measured applied & timeframe, population category that might be affected from the measures.
  • 3200+ Downloads
    Updated June 30, 2020 | Dataset date: Jun 29, 2020
    This dataset updates: Every day
    This dataset contains key figures (topline numbers) on the world's most pressing humanitarian crises. The data, curated by ReliefWeb's editorial team based on its relevance to the humanitarian community, is updated regularly. The description of the files and columns can be found in the additional metadata spreadsheet file.
  • 900+ Downloads
    Updated June 29, 2020 | Dataset date: Jan 19, 2015
    This dataset updates: Never
    (DEPRECATED: please use the data at https://data.humdata.org/dataset/global-coordination-groups-beta instead — also available at http://vocabulary.unocha.org). Based on feedback from Humanitarian Information Management community, the Humanitarianresponse.info team in OCHA has released three letters standard clusters codes via APIs to help facilitate interoperability between websites and data from several humanitarian platforms including HumanitarianRespons.info, ReliefWeb, HDX, Online Reporting System, Online Project System, Financial Tracking Service and the developer communities.
  • 700+ Downloads
    Updated June 29, 2020 | Dataset date: Apr 23, 2020
    This dataset updates: As needed
    Global Humanitarian Response Plan COVID-19 administrative level 1 boundaries, gazetteer and population tables for countries covered by the May update of the Global Humanitarian Response Plan COVID-19. Population statistics are available for 37 of the 63 countries or territories. Data fields: ADM1_PCODE: Administrative level 1 (various types) P-code ADM0_PCODE: Administrative level 0 (country or territory) P-code alpha_3: ISO 3166-1 Alpha 3 country or territory identifier ADM0_REF: Administrative level 0 (country or territory) reference name (Latin script without special characters) ADM1_REF: Administrative level 1 (various types) reference name (Latin script without special characters) Population: Most recent available total population. PLEASE SEE CAVEATS
  • Updated June 29, 2020 | Dataset date: Jan 1, 2000-Dec 31, 2020
    This dataset updates: Every year
    Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The '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. Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing 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/WP00646
  • Updated June 29, 2020 | Dataset date: Jan 1, 2000-Dec 31, 2020
    This dataset updates: Every year
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data and methods can be found in Tatem et al, a description of the modelling methods used found in Stevens et al, and access to modelling code here. 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). Individual countries 2000-2020: Consistent 100m resolution population count datasets created using "top-down" methods for all countries of the World for each year 2000-2020. Individual countries 2000-2020 UN adjusted: Adjusted to match official United Nations population estimates (UN 2019). Global mosaics 2000-2020: Mosaiced 1km resolution versions of the "Individual countries 2000-2020" datasets. Bespoke methods for individual countries (WOPR): Bespoke 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. 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/WP00647
  • 700+ Downloads
    Updated June 27, 2020 | Dataset date: Sep 25, 2017
    This dataset updates: As needed
    Missing Migrants Project draws on a range of sources to track deaths of migrants along migratory routes across the globe. Data from this project are published in the report “Fatal Journeys: Tracking Lives Lost during Migration,” which provides the most comprehensive global tally of migrant fatalities for 2014, and estimates deaths over the past 15 years.
  • 100+ Downloads
    Updated Live | Dataset date: Sep 18, 2019
    This dataset updates: Live
    These datasets include the approval projects allocated from CBPFs and the current contributions linked to each pooled fund.
  • 50+ Downloads
    Updated Live | Dataset date: Jun 1, 2018-Jun 1, 2028
    This dataset updates: Live
    Subset of the full list of crisis identifiers available at GLIDEnumber.net. OCHA provides these GLIDE numbers for interoperability purposes only, so that partners will know what identifiers we are using internally. Please refer to GLIDEnumber.net for the complete and most up-to-date list.
  • 10+ Downloads
    Updated June 25, 2020 | Dataset date: Dec 30, 2015
    This dataset updates: Never
    Development assistance data from AFD - French Development Agency The dataset covers French development assistance, on ongoing projects in 2015. The data are disclose as receivers agreed France to share it. AFD aims at updating the data every trimester to take into account the flow of new project being funded. Cumulative fundings were update December the 30th 2015 and respect IATI standards. Données de l'aide au développement de l' AFD - Agence Française de Développement Les données portent sur l’aide au développement française sur les projets réalisés en souverain et en cours d’exécution en 2015. Ces données peuvent être publiées dès lors que l'accord de la contrepartie a été obtenu.L'Agence Française de Développement visera une actualisation trimestrielle de la publication de ces données, notamment pour prendre en compte les nouveaux projets de développement financés par l’Agence. Il est à noter que les montants cumulés des versements ont été mis à jour le 30 décembre 2015. Ces données respectent le standard IATI (Initiative internationale pour la transparence de l’aide).