Co-creating an Open Government Data Driven Public Service: The Case of Chicago’s Food Inspection Forecasting Model

Date
2018-01-03
Authors
McBride, Keegan
Aavik, Gerli
Kalvet, Tarmo
Krimmer, Robert
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Abstract
Large amounts of Open Government Data (OGD) have become available and co-created public services have started to emerge, but there is only limited empirical material available on co-created OGD-driven public services. To address this shortcoming and explore the concept of co-created OGD-driven public services the authors conducted an exploratory case study. The case study explored Chicago’s use of OGD in the co-creation of a predictive analytics model that forecasts critical safety violations at food serving establishments. The results of this exploratory work allowed for new insights to be gained on co-created OGD-driven public services and led to the identification of six factors that seem to play a key role in allowing for a OGD-driven public service to be co-created. The results of the initial work also provide valuable new information that can be used to aid in the development and improvement of the authors’ conceptual model for understanding co-created OGD-driven public service.
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Open Data, Information Processing, and Datification in Government, co-creation, co-production, open data, open government data, public service innovation
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