Data governance in the health industry: investigating data quality dimensions within a big data context

Juddo, Suraj, George, Carlisle ORCID: https://orcid.org/0000-0002-8600-6264, Duquenoy, Penny and Windridge, David ORCID: https://orcid.org/0000-0001-5507-8516 (2018) Data governance in the health industry: investigating data quality dimensions within a big data context. Applied System Innovation, 1 (4) , 43. pp. 1-16. ISSN 2571-5577 [Article] (doi:10.3390/asi1040043)

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Abstract

In the health industry, the use of data (including Big Data) is of growing importance. The term ‘Big Data’ characterizes data by its volume, and also by its velocity, variety, and veracity. Big Data needs to have effective data governance, which includes measures to manage and control the use of data and to enhance data quality, availability, and integrity. The type and description of data quality can be expressed in terms of the dimensions of data quality. Well-known dimensions are accuracy, completeness, and consistency, amongst others. Since data quality depends on how the data is expected to be used, the most important data quality dimensions depend on the context of use and industry needs. There is a lack of current research focusing on data quality dimensions for Big Data within the health industry; this paper, therefore, investigates the most important data quality dimensions for Big Data within this context. An inner hermeneutic cycle research approach was used to review relevant literature related to data quality for big health datasets in a systematic way and to produce a list of the most important data quality dimensions. Based on a hierarchical framework for organizing data quality dimensions, the highest ranked category of dimensions was determined.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science > Aspects of Law and Ethics Related to Technology group
Item ID: 25563
Notes on copyright: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Depositing User: Carlisle George
Date Deposited: 09 Nov 2018 09:33
Last Modified: 15 Sep 2020 10:50
URI: https://eprints.mdx.ac.uk/id/eprint/25563

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