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Using big data for evaluating development outcomes: A systematic map.

Francis Rathinam1, Sayak Khatua2, Zeba Siddiqui2

  • 1Athena Infonomics Chennai India.

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This summary is machine-generated.

Big data, like satellite imagery, offers potential for development monitoring, but evidence gaps and ethical concerns remain. More research is needed to fully leverage these tools for sustainable development goals.

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Area of Science:

  • Development Studies
  • Data Science
  • Sustainable Development

Background:

  • Policymakers require reliable data to track progress on development targets, including Sustainable Development Goals (SDGs).
  • Significant data gaps persist due to resource limitations, capacity constraints, and logistical challenges in data collection.
  • Big data offers a promising solution, with sources like satellite imagery and mobile phone records complementing traditional data.

Purpose of the Study:

  • To map big data sources against development outcomes (SDGs) to identify existing evidence, usage, and gaps.
  • To appraise impact evaluations and systematic reviews utilizing big data for development outcomes, particularly in challenging contexts.

Main Methods:

  • A systematic search of databases and repositories was conducted using keywords related to big data.
  • Studies were selected based on their use of big data sources for measuring or evaluating development outcomes.
  • Data extraction and analysis were performed using Stata, focusing on trends and descriptive statistics.

Main Results:

  • Over 17,000 records were screened, resulting in 437 studies for the systematic map.
  • A growing number of studies use big data for measurement, with a smaller proportion of impact evaluations.
  • Satellite data is the most prevalent big data source, used in over 70% of measurement studies and 80% of impact evaluations.

Conclusions:

  • Significant efforts are underway to develop big data measures for development, with potential for future impact evaluations.
  • Gaps exist in understanding the costs, ethics, and transparency of big data usage.
  • Further research is needed to address understudied development outcomes and explore new methods and data sources.