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2019 | OriginalPaper | Chapter

A Formal Taxonomy of Temporal Data Defects

Author : João Marcelo Borovina Josko

Published in: Data Quality and Trust in Big Data

Publisher: Springer International Publishing

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Abstract

Data quality assessment outcomes are essential for analytical processes reliability, especially when they are related to temporal data. Such outcomes depend on efficiency and efficacy of (semi-)automated approaches that are determined by understanding the problem associated with each data defect. Despite the small number of works that describe temporal data defects regarding to accuracy, completeness and consistency, there is a significant heterogeneity of terminology, nomenclature, description depth and number of examined defects. To cover this gap, this work reports a taxonomy that organizes temporal data defects according to a five-step methodology. The proposed taxonomy enhances the descriptions and coverage of defects with regard to the related works, and also supports certain requirements of data quality assessment, including the design of visual analytics solutions to support data quality assessment.

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Metadata
Title
A Formal Taxonomy of Temporal Data Defects
Author
João Marcelo Borovina Josko
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-19143-6_7

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