Data-Pop Alliance is a global coalition on Big Data and development created by the Harvard Humanitarian Initiative, MIT Media Lab, and Overseas Development Institute that brings together researchers, experts, practitioners, and activists to promote a people-centered Big Data revolution through collaborative research, capacity building, and community engagement. As of February 2016, Flowminder Foundation has joined Data-Pop Alliance as its fourth Core Member. Navigation
MENUMENU
  • Introduction
    • DPA & UNDP Cooperation
    • Objectives
    • Strategy & Partnerships
  • Measuring SDGs
    • Agenda 2030
    • New Approaches: Indicators
    • Tier Classification
  • Big Data
    • Data Revolution
  • Resources & Methodologies
    • Big Data Sources for Development
    • Methodologies
  • Field
  • Where
  • Prototype
    • Download Final Report
  • Training
  • Measuring the Unmeasured: Tier 3 SDGs
  • Big Data to Address Global Development Challenges Paper Series
  • EmpoderaData
  • Brazil
  • Moldova
  • Kyrgyz Republic
  • Sudan
  • Botswana
  • Egypt
  • Albania
  • Search
MENUMENU
  • Introduction
    • DPA & UNDP Cooperation
    • Objectives
    • Strategy & Partnerships
  • Measuring SDGs
    • Agenda 2030
    • New Approaches: Indicators
    • Tier Classification
  • Big Data
    • Data Revolution
  • Resources & Methodologies
    • Big Data Sources for Development
    • Methodologies
  • Field
  • Where
  • Prototype
    • Download Final Report
  • Training
  • Measuring the Unmeasured: Tier 3 SDGs
  • Big Data to Address Global Development Challenges Paper Series
  • EmpoderaData
  • Brazil
  • Moldova
  • Kyrgyz Republic
  • Sudan
  • Botswana
  • Egypt
  • Albania
  • Search

Objectives

News & Blogs

  • Protected: Partnership Announcement – CIAT

    Protected: Partnership Announcement – CIAT

    …Read More »
  • Partnership Announcement between Data-Pop Alliance and UN-ESCWA

    Partnership Announcement between Data-Pop Alliance and UN-ESCWA

    …Read More »
  • Links We Like – Algorithmic Bias and the Gender Gap

    Links We Like – Algorithmic Bias and the Gender Gap

    …Read More »

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