Data [17639]
  • Updated August 12, 2020 | Dataset date: Jul 27, 2020
    Peacekeeping Uniformed Contributions by Rank of Troop- or Police-Contributing Country, as of end of last calendar month, associated with unique ID, Country ISO Code, M49 DESA code, Country Name of Troop or Police Contributing country, Rank for the Month, Number of male uniformed personnel, Number of female uniformed personnel, and Monthly report Date. This data set will be updated monthly.
    4000+ Downloads
    This dataset updates: Every month
  • Updated August 12, 2020 | Dataset date: Jul 27, 2020
    Peacekeeping Uniformed Contributions by Gender, as of end of last calendar month, associated with unique OD, Country ISO Code, M49 DESA code, Country Name of Troop or Police Contributing country, Mission, Description of uniformed category, Gender, and Monthly report Date. This data set will be update monthly.
    2000+ Downloads
    This dataset updates: Every month
  • Updated August 12, 2020 | Dataset date: May 20, 2020-Aug 10, 2020
    This dataset contains the number of confirmed cases, deaths and recoveries by province due to the Coronavirus pandemic in Mozambique.
    900+ Downloads
    This dataset updates: Every week
  • Updated August 12, 2020 | Dataset date: Jan 8, 2020-Aug 12, 2020
    Coronavirus COVID-19 daily new and cumulative cases and deaths by country.
    4200+ Downloads
    This dataset updates: Every day
  • Updated August 12, 2020 | Dataset date: Jan 1, 2020-Jun 30, 2020
    This dataset includes the latest available information on COVID-19 developments impacting the security of aid work and operations to help aid agencies meet duty of care obligations to staff and reach people in need. The COVID-19 Aid Security Overview Data by Insecurity Insight is provisional and awaiting final approval. It may contain errors.
    900+ Downloads
    This dataset updates: Every month
  • Updated August 12, 2020 | Dataset date: Aug 12, 2020
    This dataset contains the number of confirmed cases, recoveries and deaths by locations due to the Coronavirus pandemic in Libya.
    90+ Downloads
    This dataset updates: Every day
  • Updated August 12, 2020 | Dataset date: Dec 31, 2014
    Angola Census 2014 Final and Preliminary Population Reports (pdf) from the Angola Instituto Nacional de Estatística (INE) Census (in Portuguese). The spreadsheet includes Census 2014 final population at Province (Admin 1) Level and Census 2014 PRELIMINARY population at Municipality (Admin 2) level, extracted from reports. These CSV tables are suitable for database or GIS linkage to the administrative level 0-2 shapefiles.
    1200+ Downloads
    This dataset updates: Every year
  • Updated August 12, 2020 | Dataset date: Jan 1, 1990-Aug 12, 2020
    This dataset contains Food Prices data for all countries where the data is available. Food prices data comes from the World Food Programme (WFP) and covers foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
    10+ Downloads
    This dataset updates: Every week
  • Updated August 12, 2020 | Dataset date: Mar 10, 2020-Aug 11, 2020
    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
    3900+ Downloads
    This dataset updates: Every day
  • 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.
    2500+ Downloads
    This dataset updates: Live
  • Updated August 12, 2020 | Dataset date: Jan 1, 2020-Aug 7, 2020
    Number of Refugees returning to Afghanistan for the period of 01 January 2020 to 07 August 2020 by district of destination and origin.
    200+ Downloads
    This dataset updates: Every month
  • Updated August 12, 2020 | Dataset date: Aug 12, 2020
    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.
    6400+ Downloads
    This dataset updates: Every day
  • Updated August 12, 2020 | Dataset date: Aug 12, 2020
    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.
    2000+ Downloads
    This dataset updates: Every day
  • No abstract provided
    20+ Downloads
    This dataset updates: As needed
  • Updated August 12, 2020 | Dataset date: Jan 1, 1997-Dec 31, 2020
    The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
    200+ Downloads
    This dataset updates: Every week
  • Updated August 11, 2020 | Dataset date: Sep 1, 2016-Apr 1, 2018
    The Future of Business survey is a collaboration between Facebook, the OECD and the World Bank to provide timely insights on the perceptions, challenges, and outlook of online Small and Medium Enterprises (SMEs). The Future of Business survey was first launched as a monthly survey in 17 countries in February 2016 and expanded to 42 countries in 2018. In 2019, the Future of Business survey increased coverage to 97 countries and moved to a bi-annual cadence. The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. To date, more than 90 million SMEs have created a Facebook Page, and more than 700,000 of these Facebook Page owners have taken the survey. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest. The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download. This dataset contains survey response data aggregated by country and wave. Future of Business Survey website: futureofbusinesssurvey.org
    2400+ Downloads
    This dataset updates: As needed
  • Updated August 11, 2020 | Dataset date: Mar 1, 2020-Aug 31, 2020
    These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day. Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
    3200+ Downloads
    This dataset updates: Every day
  • UNOSAT code: FL20200713BGD This map illustrates potentially exposed population to floods (cumulative) aggregated by district using NOAA20-VIIRS in Bangladesh between the 12th and the 21st of July 2020 and Worldpop spatial demographic data. About 34 million people were exposed or living close to flooded areas. The most exposed districts mainly located in Sylhet, Mymensingh and Rajshahi divisions.
    This dataset updates: Never
  • Updated Live | Dataset date: May 1, 2019-Dec 31, 2020
    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
    This dataset updates: Live
  • Updated August 11, 2020 | Dataset date: May 29, 2019
    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.
    80+ Downloads
    This dataset updates: Every day
  • Updated August 11, 2020 | Dataset date: May 5, 2020
    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
    This dataset updates: Every day
  • Updated August 11, 2020 | Dataset date: Jan 1, 2010-Aug 11, 2020
    Venezuela SGD Indicators
    This data is by request only
  • Updated August 11, 2020 | Dataset date: Dec 10, 2019
    The INFORM Severity Index is a regularly updated, and easily interpreted model for measuring the severity of humanitarian crisis globally. It is a composite index, which brings together 31 core indicators, organised in three dimensions: impact, conditions of affected people, and complexity. All the indicators are scored on a scale of 1 to 5. These scores are then aggregated into components, the three dimensions (Impact, Conditions, Complexity), and the overall severity category based on the analytical framework. The three dimensions have been weighted according to their contribution to severity: impact of the crisis (20%); conditions of affected people (50%); complexity (30%). The weightings are currently a best estimate and will be refined using expert analysis and statistical methods. Each crisis will fall into 1 of 5 categories based on their score ranging from very low to high. ACAPS – an INFORM technical partner – is responsible for collection, cleaning, analysis and input of data into the model and the production of the final results. Read more on the GCSI methodology here: https://www.acaps.org/methodology/severity
    1800+ Downloads
    This dataset updates: Every month
  • The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak. Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak. We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak. The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository. United States Data Data on cumulative coronavirus cases and deaths can be found in two files for states and counties. Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information. Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data. State-Level Data State-level data can be found in the us-states.csv file. date,state,fips,cases,deaths 2020-01-21,Washington,53,1,0 ... County-Level Data County-level data can be found in the us-counties.csv file. date,county,state,fips,cases,deaths 2020-01-21,Snohomish,Washington,53061,1,0 ... In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these. Github Repository This dataset contains COVID-19 data for the United States of America made available by The New York Times on github at https://github.com/nytimes/covid-19-data
    4500+ Downloads
    This dataset updates: Every day
  • Updated August 11, 2020 | Dataset date: Jan 24, 2020-Aug 11, 2020
    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
    700+ Downloads
    This dataset updates: Every day