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Open AccessArticle

Data Governance in the Health Industry: Investigating Data Quality Dimensions within a Big Data Context

1
School of Science and Technology, Middlesex University Mauritius, Uniciti, Cascavelle 90203, Mauritius
2
Department of Computer Science, School of Science and Technology, Middlesex University, London NW4 4BT, UK
*
Author to whom correspondence should be addressed.
Appl. Syst. Innov. 2018, 1(4), 43; https://doi.org/10.3390/asi1040043
Received: 30 September 2018 / Revised: 25 October 2018 / Accepted: 26 October 2018 / Published: 1 November 2018
(This article belongs to the Special Issue Healthcare System Innovation)
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. View Full-Text
Keywords: Big Data; data quality; health data; data quality dimensions Big Data; data quality; health data; data quality dimensions
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MDPI and ACS Style

Juddoo, S.; George, C.; Duquenoy, P.; Windridge, D. Data Governance in the Health Industry: Investigating Data Quality Dimensions within a Big Data Context. Appl. Syst. Innov. 2018, 1, 43.

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