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  • 4200+ Downloads
    Updated 28 May 2022 | Dataset date: May 31, 2020-May 31, 2020
    This dataset updates: Every day
    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)
  • 10000+ Downloads
    Updated 28 May 2022 | Dataset date: May 28, 2022-May 28, 2022
    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.
  • 8100+ Downloads
    Updated Live | Dataset date: December 01, 2019-May 27, 2022
    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.
  • 100+ Downloads
    Updated 27 May 2022 | Dataset date: January 01, 1970-December 31, 2021
    This dataset updates: Every month
    Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.
  • Updated 27 May 2022 | Dataset date: January 01, 2022-May 28, 2022
    This dataset updates: Never
    Shapefiles and data of the Information Management Toolbox from Vichada
  • Updated 27 May 2022 | Dataset date: May 10, 2022-May 28, 2022
    This dataset updates: Never
    Shapefiles and data of the Information Management Toolbox from Guainía
  • Updated 27 May 2022 | Dataset date: May 27, 2022-May 28, 2022
    This dataset updates: As needed
    Estas bases contienen la información de las alertas hidrológicas reportadas por el IDEAM y eventos por desastres de origen natural reportados por la UNGRD en Colombia, con un periodo de tiempo de enero a abril 2022.
  • 50+ Downloads
    Updated 27 May 2022 | Dataset date: January 01, 2022-May 28, 2022
    This dataset updates: Every year
    Shapefiles and data of the Information Management Toolbox from Chocó
  • 6300+ Downloads
    Updated 27 May 2022 | Dataset date: September 02, 2020-May 28, 2022
    This dataset updates: Every month
    The Syrian IDP camps monitoring interactive study is issued by the IMU of the ACU on a monthly basis, to monitor the humanitarian situation of 231 IDp camps in Idleb and Aleppo governorates in Syria’s northwest, shedding light on the needs of the IDPs and the services provided in the camps in the following sectors: Population statistics, WASH, Health, Education, FSL, Shelter and NFI, in addition to the priority needs of IDPs. The study also includes statistics of those who arrive at and leave the camps and the important incidents which took place during the month of the data collection.
  • 40+ Downloads
    Updated 27 May 2022 | Dataset date: April 22, 2021-May 28, 2022
    This dataset updates: As needed
    Base que contiene información de migrantes registrados en el Servicio Público de Empleo por departamento, tipo de vacantes (alta rotación, Neutral y Difícil consecución) e información de la demanda laboral venezolana a dos y tres dígitos según la clasificación CIUO 08 AC. Periodo de recolección entre julio de 2020 a marzo 2022.
  • 1600+ Downloads
    Updated 27 May 2022 | Dataset date: January 27, 2019-March 31, 2022
    This dataset updates: Every three months
    Situation des personnes déplacées internes au Burkina Faso.
  • 50+ Downloads
    Updated 27 May 2022 | Dataset date: January 01, 2018-May 22, 2022
    This dataset updates: Every year
    The data is about emergencies caused by natural disasters such as floods and heavy rains.
  • 40+ Downloads
    Updated 27 May 2022 | Dataset date: April 04, 2022-May 28, 2022
    This dataset updates: Every year
    Benin administrative level 0-2 edge-matched gazetteer, shapefiles, geodatabase, and geoservice. These layers are suitable for database or GIS linkage to the Benin - Subnational Population Statistics tables. Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
  • Updated 26 May 2022 | Dataset date: February 28, 2017-May 31, 2022
    This dataset updates: Every month
    Ethiopia Current Situation FEWS NET IPC Classification data since 2017 to 2022.
  • Updated 26 May 2022 | Dataset date: February 29, 2020-September 30, 2022
    This dataset updates: Every month
    Cameroon Near Term Projection FEWS NET IPC Classification data since 2020 to 2022.
  • 40+ Downloads
    Updated 26 May 2022 | Dataset date: March 01, 2022-May 21, 2022
    This dataset updates: As needed
    This dataset is part of the Ukraine Data Explorer Consolidated Multi-Purpose Cash (MPC) 4W and 5W data (Who does What, Where) from Ukraine Cash Working Group (CWG), collected from partners involved in the MPC assistance.
  • 300+ Downloads
    Updated 26 May 2022 | Dataset date: February 24, 2022-May 28, 2022
    This dataset updates: Every week
    Data collected by CBi on cash and in-kind donations made by private sector entities (corporations and corporate-affiliated foundations) to help support the the humanitarian response in Ukraine. This data is used to power the Ukraine Private Sector Donations Tracker.
  • Updated 26 May 2022 | Dataset date: March 03, 2021-May 28, 2022
    This dataset updates: Every week
    Nigeria Weekly staple food price data collected by FEWS NET since 2021.
  • Updated 26 May 2022 | Dataset date: February 28, 2017-April 30, 2022
    This dataset updates: Every month
    Yemen Current Situation FEWS NET IPC Population data since 2017 to 2022.
  • 2000+ Downloads
    Updated 26 May 2022 | Dataset date: April 14, 2022-April 14, 2022
    This dataset updates: As needed
    This dataset includes the names and coordinates of international border crossings of Ukraine with Belarus, Hungary, Moldova, Poland, Romania, Russian Federation and Slovakia. The names of the border crossings are in English and Ukrainian.
  • Updated 25 May 2022 | Dataset date: November 01, 2019-February 28, 2022
    This dataset updates: Every six months
    Ce jeu de données donne la présence opérationnelle des partenaires humanitaires dans les communes au Burkina Faso.
  • Updated 25 May 2022 | Dataset date: January 31, 2017-December 31, 2022
    This dataset updates: Every year
    This data has been produced by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. The data provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance. It represents a consolidated evidence base and helps inform joint strategic response planning.
  • Updated 25 May 2022 | Dataset date: June 01, 2021-May 16, 2022
    This dataset updates: Every six months
    This data is about the internally displaced persons (IDPs) in Niger disaggregated by sites.
  • Updated 25 May 2022 | Dataset date: November 01, 2015-February 28, 2021
    This dataset updates: Every six months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed).
  • Updated 25 May 2022 | Dataset date: November 13, 2019-May 28, 2022
    This dataset updates: Every year
    With its Global Militarisation Index (GMI), BICC is able to objectively depict worldwide militarisation for the first time. The GMI compares, for example, a country’s military expenditure with its Gross Domestic Product (GDP) and its health expenditure. It contrasts the total number of military and paramilitary forces in a country with the number of physicians. Finally, it studies the number of heavy weapons available to a country’s armed forces. These and other indicators are used to determine a country’s ranking, which in turn makes it possible to measure the respective level of militarisation in comparison to other countries. The latest GMI of 2021 covers 153 countries and is based on the latest available figures (in most cases data for 2020). Israel, Oman, Azerbaijan, Kuwait, Armenia, Saudi Arabia, Brunei, Bahrain, Singapore and Russia are the top 10 worldwide. These countries allocate particularly high levels of resources to the military in comparison to other areas of society. See project website for more information