July 5, 2020
| Dataset date: Jan 1, 1990-Jun 15, 2020
This dataset updates: Every week
This dataset contains Global Food Prices data from the World Food Programme covering 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.
| Dataset date: Dec 1, 2019-Jul 4, 2020
This dataset updates: Live
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 email@example.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 (firstname.lastname@example.org) 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.
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.
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.
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/
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.
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.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
railway IN ('rail','subway','station')
Features may have these attributes:
This dataset is one of many OpenStreetMap exports on
See the Humanitarian OpenStreetMap Team website for more
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.
July 4, 2020
| Dataset date: Mar 1, 2020-May 28, 2020
This dataset updates: Every two weeks
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.
This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University
July 3, 2020
| Dataset date: Jan 1, 2019-Dec 31, 2019
This dataset updates: As needed
These datasets contain information on violent and threatening incidents affecting aid operations, civilians, education, healthcare, refugees and IDPs in Pakistan to ensure staff safety and better response outcomes.
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)
July 3, 2020
| Dataset date: Jun 3, 2020-Jul 3, 2020
This dataset updates: As needed
This datasets show location of hand washing stations in Indonesia taken from https://handwashing-station.ushahidi.io/ website. All of the features provided in here use Bahasa Indonesia.
Features may be include in here such as:
Nama object (ID) / Object name (EN) = provide description about the object name
Alamat (ID) / Address (EN) = provide address where the hand-washing station located
Tipe tempat cuci tangan (ID) / Type of hand-washing station (EN) = provide the type of hand-washing station. There are two values provided here:
Sumber air dari tempat cuci tangan (ID) / water source (EN) = provide the water source of the hand-washing station. There are several values provided here:
manual/isi sendiri (ID) - manual (EN)
pipa paralon (ID) - pipe (EN)
truk air (ID) - water truck (EN)
lainnya (ID) - other (EN)
Tambahan sumber air (ID) / additional water source (EN) = provide additional information about water source if the user fill other in the previous questions.
Penyedia tempat cuci tangan (ID) / provider (EN) = provide information about who create the hand-washing station. There are several values provided here:
Inisiatif individu (ID) - individual (EN)
Komunitas sekitar (Desa, RT, RW) - local community (EN)
Pemerintah (ID) - Government (EN)
Perusahaan swasta (ID) - Private company (EN)
LSM (ID) - NGO (EN)
Status (ID/EN) = provide the status of hand-washing station. There are three values provided here:
Berfungsi (ID) - Function (EN)
Tidak berfungsi (ID) - Not function (EN)
Sementara tidak digunakan (ID) - Not being used at the moment (EN)
Informasi tambahan apabila tidak berfungsi (ID) / Additional information if not function (EN) = provide additional information if the user fill not function in the previous question
Komponen utama penyusun tempat cuci tangan (ID) / Main materials of hand-washing station (EN) = provide information about the materials of hand-washing station. There are several value provided here:
Plastik (ID) - Plastic (EN)
Keramik (ID) - Ceramic (EN)
Fiber (ID) - Fiber (EN)
Besi (ID) - Iron (EN)
Tanah liat (ID) - Clay (EN)
Kayu (ID) - Wood (EN)
Waktu pengisian tempat cuci tangan (ID) / Schedule for water filling (EN) = provide information about the when the water refil. There are several value provided here:
Setiap hari (ID) - Daily (EN)
Setiap minggu (ID) - Weekly (EN)
Setiap bulan (ID) - Monthly (EN)
Otomatis (ID) - Automatically (EN)
Tidak tahu (ID) - I don't know (EN)
Lokasi (ID) / location (EN) = provide the location of the hand-washing station
Foto / Photo
July 3, 2020
| Dataset date: Jan 1, 2008-Dec 31, 2010
This dataset updates: Every month
Contains data from World Health Organization's data portal covering the following categories:
Mortality and global health estimates, Sustainable development goals, Millennium Development Goals (MDGs), Health systems, Malaria, Tuberculosis, Child health, Infectious diseases, World Health Statistics, Health financing, Public health and environment, Substance use and mental health, Tobacco, Injuries and violence, HIV/AIDS and other STIs, Nutrition, Urban health, Noncommunicable diseases, Noncommunicable diseases CCS, Negelected tropical diseases, Health Equity Monitor, Infrastructure, Essential health technologies, Medical equipment, Demographic and socioeconomic statistics, TOBACCO, Neglected tropical diseases, International Health Regulations (2005) monitoring framework, Insecticide resistance, Oral health, Universal Health Coverage, UHC, Global Observatory for eHealth (GOe), RSUD: GOVERNANCE, POLICY AND FINANCING : PREVENTION, RSUD: GOVERNANCE, POLICY AND FINANCING: TREATMENT, RSUD: GOVERNANCE, POLICY AND FINANCING: FINANCING, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT SECTORS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: TREATMENT CAPACITY AND TREATMENT COVERAGE, RSUD: SERVICE ORGANIZATION AND DELIVERY: PHARMACOLOGICAL TREATMENT, RSUD: SERVICE ORGANIZATION AND DELIVERY: SCREENING AND BRIEF INTERVENTIONS, RSUD: SERVICE ORGANIZATION AND DELIVERY: PREVENTION PROGRAMS AND PROVIDERS, RSUD: SERVICE ORGANIZATION AND DELIVERY: SPECIAL PROGRAMMES AND SERVICES, RSUD: HUMAN RESOURCES, RSUD: INFORMATION SYSTEMS, RSUD: YOUTH, FINANCIAL PROTECTION, AMR GLASS, Noncommunicable diseases and mental health, Health workforce, Neglected Tropical Diseases, AMR GASP, ICD, SEXUAL AND REPRODUCTIVE HEALTH
For links to individual indicator metadata, see resource descriptions.
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.
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
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.
| Dataset date: Jan 1, 2019-Jan 1, 2020
This dataset updates: Live
Live list of active aid activities for Turks and Caicos 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