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A Comprehensive Review of Data Governance Literature

Olivia Benfeldt Nielsen
- Iss: 8, pp 120-133
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The article was published on 2017-01-01 and is currently open access. It has received 23 citations till now. The article focuses on the topics: Data governance & Public sector.

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

TL;DR: A conceptual framework for data governance is developed and an overview of antecedents, scoping parameters, and governance mechanisms are provided to assist practitioners in approaching data governance in a structured manner.
Journal ArticleDOI

A systematic literature review of data governance and cloud data governance

TL;DR: A systematic literature review (SLR) is presented, which offers a structured, methodical, and rigorous approach to the understanding of the state-of-the-art of research in data governance to provide a credible intellectual guide for upcoming researchers inData governance to help them identify areas in data Governance research where they can make the most impact.
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Data Governance as a Collective Action Problem

TL;DR: The value in theorizing data governance as a collective action problem is demonstrated and the necessity of ensuring researchers and practitioners achieve a common understanding of the inherent challenges is argued, as a first step towards developing data governance solutions that are viable in practice.
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Responsible Data Governance of Neuroscience Big Data

TL;DR: The concept of “responsible data governance,” applying the principles of Responsible Research and Innovation to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP), is developed.
Journal ArticleDOI

Data science for business: benefits, challenges and opportunities

TL;DR: The most frequently observed benefits of data science for organizations are support for data analysis and insight generation with agility, creation of a data-driven culture; improvement of data quality; facilitating the understanding of the business environment, opportunity sensing; and organizational performance management as discussed by the authors.