Creating Open Government Data ecosystems: Network relations among governments, user communities, NGOs and the media

被引:19
|
作者
Reggi, Luigi [1 ]
Dawes, Sharon S. [2 ,3 ]
机构
[1] Italian Presidency Council, Agcy Terr Cohes, Via Sicilia 162, I-00198 Rome, Italy
[2] SUNY Albany, Rockefeller Coll Publ Affairs & Policy, Albany, NY 12222 USA
[3] SUNY Albany, Ctr Technol Govt, Albany, NY 12222 USA
关键词
Open government data; Open government data ecosystem; Open data intermediaries; Social network analysis; ERGM; Civic engagement; EXPONENTIAL FAMILY MODELS; INNOVATION;
D O I
10.1016/j.giq.2022.101675
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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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页数:12
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