Data governance in the health industry: investigating data quality dimensions within a big data context
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 782
- Type
- D - Journal article
- DOI
-
10.3390/asi1040043
- Title of journal
- Applied System Innovation
- Article number
- 43
- First page
- 1
- Volume
- 1
- Issue
- 4
- ISSN
- 2571-5577
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
http://eprints.mdx.ac.uk/25563/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper applies two rigorous and systematic research methods with the aim of clearly identifying the most important data quality dimensions applicable to Big Data in the context of healthcare. The few existing research studies in the field depend upon subjective interpretations. This paper is significant, firstly, because it grounds its feature selection in formal mechanisms. Secondly, the results support researchers and practitioners, in the domain of Big Data quality, when focusing their efforts on issues of data accuracy and completeness.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -