Human‐superviseddata science framework for city governments: A design science approach

Abstract

AbstractThe importance of involving humans in the data science process has been widely discussed in the literature. However, studies lack details onhowto involve humans in the process. Using a design science approach, this paper proposes and evaluates ahuman‐supervised data science frameworkin 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.