Document (#44018)

Author

Hagen, L.
Patel, M.
Luna-Reyes, L.

Title

Human-supervised data science framework for city governments : a design science approach

Source

Journal of the Association for Information Science and Technology. 74(2023) no.8, S.923-936

Year

2023

Abstract

The importance of involving humans in the data science process has been widely discussed in the literature. However, studies lack details on how to involve humans in the process. Using a design science approach, this paper proposes and evaluates a human-supervised data science framework in the context of local governments. Our findings suggest that the involvement of a stakeholder group, public managers in this case, in the process of data science project enhanced quality of data science outcomes. Public managers' detailed knowledge on both the data and context was beneficial for improving future data science infrastructure. In addition, the study suggests that local governments can harness the value of data-driven approaches to policy and decision making through focalized investments in improving data and data science infrastructure, which includes culture and processes necessary to incorporate data science and analytics into the decision-making process.

Content

Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24764.

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5. Fry, J.; Schroeder, R.; Besten, M. den: Open science in e-science : contingency or policy? (2009) 0.14

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