The Evidence that Open Government Data Improves Developing Economies

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In 2009, the United States launched the data.gov portal. Since then there has been a rapid increase in the systematic opening of government data around the world. The 2016 Open Data Barometer, published annually by the World Wide Web Foundation, found that 79 of the 115 countries surveyed had official open data initiatives.
Similarly, as part of the Open Government Partnership, some 70 countries have now issued National Action Plans, the majority of which contain strong open data commitments designed to foster greater transparency, generate economic growth, empower citizens, fight corruption, and more generally enhance governance.
Approximately half of these countries are from the developing world, suggesting the uptake of open data is happening not only within economically advanced countries, but also in those less developed. All of this is part of a general move toward more transparent and innovative governance mechanisms, as emblematized by rising interest in notions of open government and open development.
The growing enthusiasm for, and use of, open data in developing economies leads to several questions about open data’s role in fostering development.

  • Can open data bring about economic growth and social transformation?
  • Can open data truly improve people’s lives in the developing world?
  • If so, how and under what conditions?

The goal of Open Data in Developing Economies: Toward Building an Evidence Base on What Works and How is to take stock of what is known about open data’s use and impacts in developing economies, and to distil a theory of change based on existing theory and practice that can inform future open data use and research.
Four Benefits of Open Government Data
Our broad conclusion, supported by the literature, stories, and case studies, are that the theory of change being advanced in the field of open data for development is built around the premise that open data can:

  • Improve governance, specifically by enhancing transparency and accountability, introducing new efficiencies into service delivery, and increasing information sharing within government departments
  • Empower citizens in developing countries by improving their capacity to make decisions and widen their choices, and also by acting as a catalyst for social mobilization
  • Create economic opportunity, notably by enabling business creation, job creation, new forms of innovation and more generally spurring economic growth
  • Help solve complex public problems by improving situational awareness, bringing a wider range of expertise and knowledge to bear on public problems, and by allowing policymakers, civil society, and citizens to better target interventions and track impact

Again, none of these impacts are inevitable; they are currently better understood as intended rather than realized impacts.
Five Enabling Factors for Success
As part of our broader logic open data model, we have identified a number of enabling conditions and disabling factors – phenomena or aspects that may spur the potential of open data in developing economies.
In particular, the impact of open data in developing economies depends upon:

  • Problem and Demand Definition: whether and how the problem to be addressed and/or the demand for open data are clearly defined and understood
  • Capacity and Culture: whether and how resources, human capital and technological capabilities are sufficiently available and leveraged meaningfully
  • Partnerships: whether and how collaboration within and, especially, across sectors using open data exists
  • Risks: whether and how the risks associated with open data are assessed and mitigated
  • Governance: whether and how decisions affecting the use of open data are made in a responsive and legitimate manner

The Periodic Table of Open Data Impact Elements, outlined in Open Data in Developing Economies details the enabling conditions and disabling factors that must be taken into account.
The list can be used as a checklist of elements that are essential to keep in mind whenever designing or funding open data projects since they may determine the difference between success and failure.
By Stefaan Verhulst and Andrew Young
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