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Data Collaboratives

Andrew Young and Stefaan Verhulst at The Palgrave Encyclopedia of Interest Groups, Lobbying and Public Affairs: “The rise of the open data movement means that a growing amount of data is today being broken out of information silos and released or shared with third parties. Yet despite the growing accessibility of data, there continues to exist a mismatch between the supply of, and demand for, data (Verhulst & Young, 2018). This is because supply and demand are often widely dispersed – spread across government, the private sector, and civil society – meaning that those who need data do not know where to find it, and those who release data do not know how to effectively target it at those who can most effectively use it (Susha, Janssen, & Verhulst, 2017). While much commentary on the data era’s shortcomings focuses on issues such as data glut (Buchanan & Kock, 2001), misuse of data (Solove & Citron, 2017), or algorithmic bias (Hajian, Bonchi, & Castillo, 2016), this mismatch between supply and demand is at least equally problematic, resulting in tremendous inefficiencies and lost potential.

Data collaboratives, when designed responsibly (Alemanno, 2018), can help to address such shortcomings. They draw together otherwise siloed data – such as, for example, telecom data, satellite imagery, social media data, financial data – and a dispersed range of expertise. In the process, they help match supply and demand, and ensure that the appropriate institutions and individuals are using and analyzing data in ways that maximize the possibility of new, innovative social solutions (de Montjoye, Gambs, Blondel, et al., 2018)….(More)”.

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