Affiliations: Public Governance Institute (PGI), KU Leuven, Belgium | E-mail: [email protected]
Correspondence:
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Corresponding author: Public Governance Institute (PGI), KU Leuven, Belgium. E-mail: [email protected].
Abstract: AI solutions can significantly leverage open government data (OGD) ecosystems in public governance. For that, it is important to design effective and transparent governance mechanisms that create value in an OGD ecosystem through AI solutions. This article develops a conceptual model for a systematic design of an OGD governance model, which adopts a platform governance approach and integrates the governance needs derived from the use of AI. The purpose of the conceptual model is to systematically identify and analyze the interrelationships among multiple change factors on OGD governance design and to project available AI-based solutions for the OGD ecosystem by assessing the managerial, organizational, legal, technological, moral, and institutional variances. The proposed ‘6-step model’ suggests that an AI-compatible OGD ecosystem design requires (i) identifying contingencies, (ii) identifying data prosumers, (iii) assigning data governance roles, (iv) identifying design values, (v) designing the governance of AI, and (vi) designing the governance by AI. Through the recursive and reflexive analysis of each step, policymakers and system designers can develop reliable strategies in leveraging AI solutions for the use of OGD in public governance.
Keywords: Open government data, AI, data ecosystem, digital governance, public governance, digital transformation, platform governanceKey points for practitioners:•An AI-compatible OGD ecosystem design requires assessment of contingencies, data prosumers, data governance roles, design values, governance of and by AI;•Each step requires a recursive and reflexive analysis in leveraging AI solutions for the use of OGD in public governance;•Design choices in OGD governance vary with the values, ethical bases, and contingencies in the area of application, the maturity of existing data governance systems, and institutional contexts.
