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Data Governance in Public Sector: A Study of U.S. Municipal Open Data Platforms
Wu, Yusheng
Wu, Yusheng
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Abstract
As big data technologies are increasingly adopted in public sector globally, many local governments in the United States (US) bring the technologies into their daily administration to provide better public services. There arise many public values concerns such as transparency, privacy, social equity, among others regarding big data applications. Traditional concept of data management, which focus on the technical logistics of development, execution, and supervision of data operations, is insufficient to deal with those public values concerns. A new concept of data governance (DG), which specifies a framework of decision rights, accountabilities, rules, and policies related to data management and data operations, is a promising tool to integrate public values into data management.However, there exists very little research of DG in public administration (PA). Such research in information systems (IS) field is also emerging. Hence, no DG theories could be directly borrowed from the IS field to PA. This dissertation proposes a theoretical framework of DG based on Lynn, Heinrich, and Hill’s governance studies and applies the framework into two empirical studies to understand the state-of-the-art DG practices among US municipal governments through the lens of public values, and to understand the impact factors of DG adoption.Based on a systematic literature review in both PA and IS fields, the study defines DG as the regimes of laws, administrative rules, judicial rulings, organizational policies, and practices of data management that constrain, prescribe, and enable government activity, where such activity is broadly defined and used to enable the production and delivery of publicly supported goods and services. A data governance framework (DGF) is constructed at the institutional, the organizational, and the technical levels. The institutional factors include DG rules and DG authority. The organizational factors include DG leadership, DG organizational goals, DG organizational structure, data management maturity of the municipal government, DG training, and DG in the collaboration network. The technical factors include DG decision domains, DG strategies, and client characteristics.Based on the examination of DG documents from 120 municipalities in the US, the study synthesizes four types of DG practices using hierarchical clustering method based on the analytical DGF proposed previous through the lens of public values. The first type is Comprehensive Data Governance, which is characterized by formal rules, professional DG leadership, federated DG organizational forms, abundant DG training programs and collaborations, and complete DG decision domains coverage. The second type is Customer-Centric Data Governance, which is characterized by mid-size population, mayor-council form, self-motivated DG legislation, and general guidance of DG practices. The third type is Citizen-Centric Data governance, which is characterized by mid-size population, complete OGD platform adoption, DGC establishment, centralized DG form, and relatively complete DG decision domain coverage. And the last type is No Data Governance, which means no DG documents are publicly accessible.Based on the innovation diffusion theory and the proposed DGF, this dissertation builds logistic regression models to understand the impact factors of DG adoption and DG choice revealed in the second study. The results show two findings in the DG adoption. First, total population, minority population percentage, education level, and the complexity of municipal data are positively related to DG adoption. Second, joining a professional data-driven network is positively related to DG adoption. The study also shows three findings in the DG choice models. First, the existence of state-level open data laws influences cities to choose Customer-Centric Data Governance at the early exploration stage. Second, joining a professional data-driven network influences cities to choose Citizen-Centric Data Governance at the developing stage. Third, growing population influences cities to evolve into a mature Comprehensive Data Governance stage. No conclusions could be drawn from political conservative culture, the form of government, and performance budgeting practices.This dissertation contributes to the field with a first theoretical framework of data governance to extend the traditional governance studies in the big data era. Such framework serves as the foundation for the two empirical studies of data governance to address the public values issues raised by big data technologies and to understand the impact factors for public organizations to adopt data governance. This study brings an innovative way to embed public values into public administration studies in open government data. However, the study is constrained by the limited access to literature database, publicly accessible data governance documents, and limited theoretical input. The dissertation is hoped to shed light on more studies of data governance in the future.
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2023-05-31
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University of Kansas
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Public administration,