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

Author

Listed:
  • Keegan McBride
  • Gerli Aavik
  • Tarmo Kalvet
  • Robert Krimmer

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.

Suggested Citation

  • Keegan McBride & Gerli Aavik & Tarmo Kalvet & Robert Krimmer, 2017. "Co-creating an Open Government Data Driven Public Service: The Case of Chicago’s Food Inspection Forecasting Model," The Other Canon Foundation and Tallinn University of Technology Working Papers in Technology Governance and Economic Dynamics 76, TUT Ragnar Nurkse Department of Innovation and Governance.
    • Handle: RePEc:tth:wpaper:76
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