Human‐supervised data science framework for city governments: A design science approach
本文通过设计科学研究方法，提出了一个面向地方政府的人工监督数据科学框架，发现公共管理者的参与能提升数据科学成果质量，并帮助政府通过投资数据基础设施来改进决策。
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.