RETRACTED ARTICLE: Adoption of human metabolic
         processes as Data Quality Based Models

Ngueilbaye, Alladoumbaye; Wang, Hongzhi; Khan, Mehak; Mahamat, Daouda Ahmat

doi:10.1007/s11227-020-03300-3

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…5 . This input data quality level is evaluated within the data quality standard, such as ISO/IEC 25012 [ 22 ]. The proposed data quality model relies on the data quality model represented in the standard ISO/IEC 25010 [ 22 , 28 ].…”

Section: Methodsmentioning

confidence: 99%

“…This input data quality level is evaluated within the data quality standard, such as ISO/IEC 25012 [ 22 ]. The proposed data quality model relies on the data quality model represented in the standard ISO/IEC 25010 [ 22 , 28 ]. Data understanding is a product to which data can be applied in accordance with the quality interpretation established by ISO/IEC 25010.…”

Section: Methodsmentioning

confidence: 99%

“…High management tends to a propensity to believe that the bigger the big data, the greater the potential benefits. Regrettably, this occurs even when they are unsure of precise handling of big data issues or how to derive possible knowledge from big data research [ 22 , 27 ]. Therefore, the first step in any big data research is to support high management in leading the research rather than investing in and implementing sophisticated technologies that will not yield any results that are pertinent to the research issue at hand [ 25 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

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Data quality model for assessing public COVID-19 big datasets

et al. 2023

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For decision-making support and evidence based on healthcare, high quality data are crucial, particularly if the emphasized knowledge is lacking. For public health practitioners and researchers, the reporting of COVID-19 data need to be accurate and easily available. Each nation has a system in place for reporting COVID-19 data, albeit these systems’ efficacy has not been thoroughly evaluated. However, the current COVID-19 pandemic has shown widespread flaws in data quality. We propose a data quality model (canonical data model, four adequacy levels, and Benford’s law) to assess the quality issue of COVID-19 data reporting carried out by the World Health Organization (WHO) in the six Central African Economic and Monitory Community (CEMAC) region countries between March 6,2020, and June 22, 2022, and suggest potential solutions. These levels of data quality sufficiency can be interpreted as dependability indicators and sufficiency of Big Dataset inspection. This model effectively identified the quality of the entry data for big dataset analytics. The future development of this model requires scholars and institutions from all sectors to deepen their understanding of its core concepts, improve integration with other data processing technologies, and broaden the scope of its applications.

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Section: Methodsmentioning

confidence: 99%