Big Data for Development: A Review of Promises and Challenges

Abstract

The article uses a conceptual framework to review empirical evidence and some 180 articles related to the opportunities and threats of Big Data Analytics for international development. The advent of Big Data delivers a cost‐effective prospect for improved decision‐making in critical development areas such as healthcare, economic productivity and security. At the same time, the well‐known caveats of the Big Data debate, such as privacy concerns and human resource scarcity, are aggravated in developing countries by long‐standing structural shortages in the areas of infrastructure, economic resources and institutions. The result is a new kind of digital divide: a divide in the use of data‐based knowledge to inform intelligent decision‐making. The article systematically reviews several available policy options in terms of fostering opportunities and minimising risks.

Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development

“…S2 Content of data: words, locations, behavior, transactions, or nature [19]. Transaction data concern data about people's activities in a commercial setting as a customer (e.g.…”

“…Existing taxonomies are organized around how data is collected and opened [16], in which format it is provided [17], and how data can be used [18]. Hilbert [19] classified data sources based on the content and what they capture: words, locations, behavior, transactions, production, nature, or other. Furthermore, a report by Vaitla [7] distinguished between the different tracking technologies to capture these data: data exhaust (e.g.…”

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“…Most of the limitations of the use of computational social science are very similar to the challenges tackled by traditional ICTD projects, including challenges in the areas of infrastructure, human resources, and institutional frameworks [19].…”

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