Extending contexts with ontologies for multidimensional data quality assessment

Milani, Mostafa; Bertossi, Leopoldo; Ariyan, Sina

doi:10.1109/icdew.2014.6818333

Cited by 12 publications

(17 citation statements)

References 16 publications

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“…In other matters, we identify other kind of models, all for DQ assessment and motivated by the idea that DQ is context-dependent. For instance, the authors of [82] present a decision model to facilitate the description of business rules, and in [15,58,64] a model of context is developed. As well, there are PS that address the impact of poor DQ and propose improvement models, specifically [38] presents a machine learning model and [63] a neural networks model.…”

Section: Review Resultsmentioning

confidence: 99%

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%

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

Serra¹,

Peralta²,

Marotta³

et al. 2022

Preprint

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show abstract

“…When it comes to quality, so far various aspects of data quality from the definition, types, dimensions, techniques, strategies, and multidimensional proposals have circulated [22,23]. In this respect, different frameworks for measuring data quality have been developed.…”

Section: A Existing Approaches and Toolsmentioning

confidence: 99%

Application-based Framework for Analysis, Monitoring and Evaluation of National Open Data Portals

Raca¹,

Velinov²,

Cico³

et al. 2021

IJACSA

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Open Government Data (OGD) portals are considered of significant national importance towards transparency and accountability improvement. The continuous publication of data in OGD portals introduces the need for highquality data and the qualitative portal itself. This paper aims to address the data quality issues through a framework composed of several components aimed at measuring and monitoring the OGD portals in an automated way. Through this proposed framework, is intended to monitor and evaluate OGD quality, respectively OGD portals, and to show their progress/regress based on accumulated scores for different periods. The advantage of the proposed framework is the compatibility with any OGD Portal due to its flexibility of integration. The integration interface consists of only a few basic metrics but is necessary that almost the OGD portal possesses and can produce very compressive results. The other advantage is the possibility of extraction of collected data for further analysis and the introduction of artificial intelligence (AI) for prediction purposes to point out how the OGD portals will stand in the next period.

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“…Finally, we also studied other works from which we obtained relevant results, but we do not detail here [59] …”

Section: How Contexts May Be Used For Assessing Dq In Dw?mentioning

confidence: 99%

Context-based Data Quality Metrics in Data Warehouse Systems

Serra¹,

Marotta²

2017

CLEIej

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The fact that Data Quality (DQ) depends on the context, in which data are produced, stored and used, is widely recognized in the research community. Data Warehouse Systems (DWS), whose main goal is to give support to decision making based on data, have had a huge growth in the last years, in research and industry. DQ in this kind of systems becomes essential. This work presents a proposal for identifying DQ problems in the domain of DWS, considering the different contexts that exist in each system component. This proposal may act as a first conceptual framework that guides the DQ-responsible in the management of DQ in DWS. The main contributions of this work are a thorough literature review about how contexts are used for evaluating DQ in DWS, and a proposal for assessing DQ in DWS through contextbased DQ metrics.

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Extending contexts with ontologies for multidimensional data quality assessment

Cited by 12 publications

References 16 publications

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

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

Application-based Framework for Analysis, Monitoring and Evaluation of National Open Data Portals

Context-based Data Quality Metrics in Data Warehouse Systems

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