Open Data Impact: When Supply and Demand Meet-Key Findings of the Open Data Impact Case Studies

December 27, 2016

Govlab/Omidyar Network, Stefan Verhulst and Andrew Young, March 2016 - Recent years have witnessed considerable enthusiasm over the opportunities offered by open data. Across sectors, it is widely believed today that we are entering a new era of information openness and transparency, and that this has the potential to spur economic innovation, social transformation, and fresh forms of political and government accountability. Focusing just on economic impacts, in 2013, for example, the consulting firm McKinsey estimated the possible global value of open data to be over $3 trillion per year.A study commissioned by Omidyar Network has likewise calculated that open data could result in an extra $13 trillion over five years in the output of G20 nations.

Yet despite the evident potential of open data, and despite the growing amounts of information being released by governments and corporations, little is actually known about its use and impact. What kind of social and economic transformations has open data brought about, and what transformations may it effect in the future? How – and under what circumstances – has it been most effective? How have open data practitioners mitigated risks (e.g., to privacy) while maximizing social good?

As long as such questions remain unanswered, the field risks suffering from something of a mismatch between the supply (or availability) of data and its actual demand (and subsequent use). This mismatch limits the impact of open data, and inhibits its ability to produce social, economic, political, cultural and environmental change. This report begins from the premise that, in order to fully grasp the opportunities offered by open data, a more full and nuanced understanding of its workings is necessary.

Our knowledge of if, how and when open data actually works in practice is lacking because there have been so few systematic studies of its actual impact and workings. The field is dominated by conjectural estimates of open data’s hypothetical impact; those attempts that have been made to study concrete, real-world examples are often anecdotal or suffer from a paucity of information. In this report, we seek to build a more systematic study of open data and its impact by rigorously examining 19 case studies from around the world. These case studies are chosen for their geographic and sectoral representativeness. They are built not simply from secondary sources (e.g., by rehashing news reports) but from extensive interviews with key actors and protagonists who possess valuable and thus far untapped on-the-ground knowledge. They go beyond the descriptive (what happened) to the explanatory (why it happened, and what is the wider relevance or impact).

In order to provide these explanations, we have assembled an analytical framework that applies across the 19 case studies and allows us to present some more widely applicable principles for the use and impact of open data. Impact – a better understanding of how and when open data really works – is at the center of our research. Our framework seeks to establish a taxonomy of impact for open data initiatives, outlining various dimensions (from improving government to creating economic opportunities) in which open data has been effective. In addition, the framework lays out some key conditions that enable impact, as well as some challenges faced by open data projects.



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