DMN4DQ+: Optimising data repair to enhance data usability
Data quality has become crucial in decision-making and data analysis. There is an intrinsic relationship between data quality and usability; however, acceptable levels of data quality depend on the contextual requirements and operational priorities of an organisation. The context of use, business ne...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:dnet:idus________::a29b80815f1b2e5e80e1b77ee2a6c054 |
| Acceso en línea: | https://hdl.handle.net/11441/186311 https://doi.org/10.1016/j.eswa.2025.129170 |
| Access Level: | acceso abierto |
| Palabra clave: | Data quality Data repair Corrective actions Constraint programming |
| Sumario: | Data quality has become crucial in decision-making and data analysis. There is an intrinsic relationship between data quality and usability; however, acceptable levels of data quality depend on the contextual requirements and operational priorities of an organisation. The context of use, business needs, and the organisation’s appetite for risk all influence the usability of data. Achieving adequate levels of usability sometimes requires specific corrections, which can be costly and may incur have far-reaching consequences. This paper introduces the concept of target usability, by representing the minimum level of usability determined by business analysts at which data records can be used without compromising organisational performance. When data records fail to meet this threshold, a combination of corrective actions can be implemented to improve both quality and usability. To achieve near-optimal outcomes, the data quality analyst can effectively combine these sets of actions. This paper proposes DMN4DQ+, an extension of DMN4DQ, where the optimal combination of corrective actions can be derived from the application of constraint optimisation techniques based on the data quality rules described in decision models, the cost model of the actions, and on the usability profile of the record to be improved. The development of a technological stack has conveniently supported DMN4DQ+, and it has been evaluated using a real dataset, thereby demonstrating its applicability and performance. |
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