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  • Updated January 17, 2020 | Dataset date: Sep 12, 2019
    This dataset updates: As needed
    This Dataset is representing the social and community media in DRC and particulary in the province of Kongo-Central.
  • 100+ Downloads
    Updated January 10, 2020 | Dataset date: Jan 10, 2020
    This dataset updates: Every year
    En esta base de datos encontrará: Educación y matrícula desde el año 1990 hasta el 2012; Educación e inversión pública desde el año 2001 al 2010; Índice de desarrollo educativo desde el año 2003 hasta el 2012; índice del nivel de vida por entidad federal; índice del nivel de vida por regiones de Venezuela.
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 400+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2019
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2019
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 20+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2016
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2017-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2018
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2016
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2016
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2019
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2018
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 80+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2017
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2019
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 100+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2016-Dec 31, 2016
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 90+ Downloads
    Updated January 2, 2020 | Dataset date: Jan 1, 2015-Dec 31, 2015
    This dataset updates: Every month
    The World Food Programme (WFP) launched the mobile Vulnerability Analysis and Mapping (mVAM) project in 2013, beginning in DRC and Somalia. mVAM uses mobile technology to track food security trends in real-time, providing high-frequency data that supports humanitarian decision-making. Data collection methods are tailored to the needs of each country that mVAM operates in. This dataset contains data from the mVAM databank covering various indicators (one per resource).
  • 6700+ Downloads
    Updated December 31, 2019 | Dataset date: Aug 8, 2019-Oct 8, 2019
    This dataset updates: Every six months
    In response to the need for accurate information on internally displaced persons (IDPs) in Nigeria, the International Organization for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The project is supporting the Government of Nigeria and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as to establish a profile of the IDP population.
  • 900+ Downloads
    Updated December 10, 2019 | Dataset date: Dec 10, 2019
    This dataset updates: Every month
    The INFORM Global Crisis Severity Index (GCSI) 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
  • 10+ Downloads
    Updated December 3, 2019 | Dataset date: Jan 1, 1950-Dec 31, 2050
    This dataset updates: Every year
    Contains data from World Health Organization's data portal covering various indicators (one per resource).
  • 800+ Downloads
    Updated December 3, 2019 | Dataset date: Jan 1, 2017-Sep 30, 2019
    This dataset updates: Every month
    This dataset contains the total number of people targeted and reached per region and per cluster in Somalia.
  • 400+ Downloads
    Updated November 22, 2019 | Dataset date: Jan 1, 1960-Dec 31, 2026
    This dataset updates: Every year
    Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Millenium development goals, Climate Change, External Debt, Trade.
  • 200+ Downloads
    Updated November 22, 2019 | Dataset date: Jan 1, 1960-Dec 31, 2026
    This dataset updates: Every year
    Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Millenium development goals, Climate Change, External Debt, Trade.