Creating Open Government Data ecosystems: Network relations among governments,user communities,NGOs and the media |
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| Institution: | 1. Agency for Territorial Cohesion, Italian Presidency of the Council, Rome, Italy;2. Rockefeller College of Public Affairs and Policy, University at Albany, SUNY, Albany, New York, USA;3. Center for Technology in Government, University at Albany, SUNY, Albany, New York, USA;1. Department of Human and Social Sciences, University of Naples L''Orientale, Italy;2. Department of Economics, University of Rome Roma Tre, Italy;3. Interuniversity Department of Regional and Urban Studies and Planning, University of Turin, Italy;4. Department of law, economics, politics and modern languages, Libera Università degli Studi Maria Ss. Assunta di Roma, Italy;5. Department of Politics, Birkbeck College, University of London, UK |
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| Abstract: | Open Government Data (OGD) ecosystems are composed of public, private and non-profit actors playing specific roles related to the availability and use of publicly accessible government information. The literature considers the presence of healthy ecosystems as crucial for effective use of OGD, with positive effects on democracy, policy effectiveness, and economic development. This paper employs the Exponential Random Graph model (ERGM) technique to empirically explore relations among the actors of an OGD ecosystem for public participation in the context of the European Policy in Italy. The models estimate the likelihood of an ecosystem connection between actors as documented online via Twitter, by considering the type of actor - namely government organizations, user communities, NGOs and the media - and their locations. The analysis showed that governmental organizations as data providers and intermediaries play a crucial role in disseminating OGD and facilitating their use by local communities. Government organizations as policy makers were much less active. In addition, NGOs and the media were less disposed than government actors to serve as data intermediaries and less likely than local communities to engage in policy deliberation. These patterns suggest that the nature and level of engagement by various actors may be influenced by their interest in the specific purpose of the ecosystem. Finally, co-location is a powerful predictor of the creation of new connections among actors of all kinds, demonstrating that effective local data use can be enabled and encouraged by national data provision. |
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