Data governance: A conceptual framework, structured review, and research agenda

By Rene Abraham, Johannes Schneider, Jan vom Brocke. International Journal of Information Management, 2019

546 citations recorded by the source corpus.

Abstract Data governance refers to the exercise of authority and control over the management of data. The purpose of data governance is to increase the value of data and minimize data-related cost and risk. Despite data governance gaining in importance in recent years, a holistic view on data governance, which could guide both practitioners and researchers, is missing. In this review paper, we aim to close this gap and develop a conceptual framework for data governance, synthesize the literature, and provide a research agenda. We base our work on a structured literature review including 145 research papers and practitioner publications published during 2001-2019. We identify the major building blocks of data governance and decompose them along six dimensions. The paper supports future research on data governance by identifying five research areas and displaying a total of 15 research questions. Furthermore, the conceptual framework provides an overview of antecedents, scoping parameters, and governance mechanisms to assist practitioners in approaching data governance in a structured manner.

Subfields: Information Systems, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/16f81e71c27caa7ed2c9d7abdf481c3e74a5fd2b

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