A classification of data quality assessment and improvement methods. (1st January 2014)

• Record Type: Journal Article
• Authors: Woodall, Philip; Oberhofer, Martin; Borek, Alexander
• Is Part Of: International journal of information quality. Volume 3:Number 4 (2014)
• Page Start: 298
• Page End: 321
• Publication Date: 2014-01-01
• Subjects: information quality -- data quality assessment -- data quality improvement -- software tools -- automated data quality software -- information systems; Information resources management -- Periodicals; Information retrieval -- Periodicals; Knowledge management -- Periodicals; 658.4038
• DOI: 10.1504/IJIQ.2014.068656
• Languages: English
• ISSNs: 1751-0457

Abstract

Data quality (DQ) assessment and improvement in larger information systems would often not be feasible without using suitable 'DQ methods', which are algorithms that can be automatically executed by computer systems to detect and/or correct problems in datasets. Currently, these methods are already essential, and they will be of even greater importance as the quantity of data in organisational systems grows. This paper provides a review of existing methods for both DQ assessment and improvement and classifies them according to the DQ problem and problem context. Six gaps have been identified in the classification, where no current DQ methods exist, and these show where new methods are required as a guide for future research and DQ tool development.