Models of Data Quality

Bičevska, Zane; Bičevskis, Jānis; Odītis, Ivo

doi:10.1007/978-3-319-77721-4_11

Cited by 10 publications

(8 citation statements)

References 7 publications

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“…3(a), is the modeling, since several PS coincide in proposing a DQ model [17, 18, 44, 48, 53-55, 62, 80, 84]. In particular, [17] presents domain-specific characteristics of DQ, while [18] extends this work by proposing DQ models. In addition, in [10], the authors discuss models proposed for utility, discovering that DQ dimensions and DQ metrics are deeply influenced by utility.…”

Section: Review Resultsmentioning

confidence: 99%

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Use of Context in Data Quality Management: a Systematic Literature Review

Serra¹,

Peralta²,

Marotta³

et al. 2022

Preprint

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The importance of context in data quality (DQ) was shown many years ago and nowadays is widely accepted. Early approaches and surveys defined DQ as fitness for use and showed the influence of context on DQ. This paper presents a Systematic Literature Review (SLR) for investigating how context is taken into account in recent proposals for DQ management. We specifically present the planning and execution of the SLR, the analysis criteria and our results reflecting the relationship between context and DQ in the state of the art and, particularly, how that context is defined and used for DQ management.CCS Concepts: • Data Quality → Context in Data Quality Management.

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Section: Review Resultsmentioning

confidence: 99%

“…SQL statements. The proposals in [17,18] represent DQ requirements using SQL statements. In [18], an extension of [17], it is mentioned that SQL statements enable defining data objects using "select", and defining DQ requirements using "where" conditions.…”

Section: Context Components Representationmentioning

confidence: 99%

Use of Context in Data Quality Management: a Systematic Literature Review

Serra¹,

Peralta²,

Marotta³

et al. 2022

Preprint

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show abstract

“…The data analysis was limited to the syntax analysis of data records, temporarily avoiding the analysis of interrelated (external) objects. As stated in [5], a deeper data quality analysis would lead to the analysis of links between records of the CR database and other data objects from external sources.…”

Section: E Resultsmentioning

confidence: 99%

“…The quality of open data published by the company registers in four European countries will be evaluated using the approach described in [5], which is used to evaluate the quality of fully-structured data. This chapter gives an insight into the methodology of data quality models according to the approach described in [5]. It is characterized by the following main characteristics:…”

Section: Methodsmentioning

confidence: 99%

“…The first objective is to clarify whether publicly available data provided by company register is trustful and what is the quality of these data for simple use, for instance, identifying a company and sending a message to this company. Our second objective is to verify quality evaluation methodology with the help of executable data quality models described further in detail [5].…”

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confidence: 99%

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Data quality evaluation: a comparative analysis of company registers’ open data in four European countries

Bičevskis

Bičevska

Nikiforova

et al. 2018

Annals of Computer Science and Information Systems

Self Cite

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This paper is devoted to the analysis of open data quality of the company registers in four different countries. The data quality evaluation was obtained using a methodology that involves the creation of three-part data quality model: (1) the definition of a data object to analyse its quality, (2) data object quality specification using DSL, (3) the implementation of an executable data quality model enabling the scanning of a data object and detecting its deficiencies. All three components of the data quality model are designed as graphical language families, which allow formulating data quality specification for non-IT professionals. Validation of an open data published by company registers in four different European countries shows deficiencies in the published data and demonstrates the applicability of the proposed methodology for data quality evaluation. Index Terms-data quality, executable models, Company registerCommunication

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Understanding Machine Learning Through Data-Oriented and Human Learning Approaches

Behpour

Udash²

2022

Educational Communications and Technology: Issues and Innovations

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Models of Data Quality

Cited by 10 publications

References 7 publications

Use of Context in Data Quality Management: a Systematic Literature Review

Use of Context in Data Quality Management: a Systematic Literature Review

Data quality evaluation: a comparative analysis of company registers’ open data in four European countries

Understanding Machine Learning Through Data-Oriented and Human Learning Approaches

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