research-article

Anatomy of Metadata for Data Curation

Authors:

Larysa Visengeriyeva,

Ziawasch AbedjanAuthors Info & Claims

Journal of Data and Information Quality (JDIQ), Volume 12, Issue 3

Article No.: 16, Pages 1 - 30

https://doi.org/10.1145/3371925

Published: 13 June 2020 Publication History

Abstract

Real-world datasets often suffer from various data quality problems. Several data cleaning solutions have been proposed so far. However, data cleaning remains a manual and iterative task that requires domain and technical expertise. Exploiting metadata promises to improve the tedious process of data preparation, because data errors are detectable through metadata. This article investigates the intrinsic connection between metadata and data errors. In this work, we establish a mapping that reflects the connection between data quality issues and extractable metadata using qualitative and quantitative techniques. Additionally, we present a taxonomy based on a closed grammar that covers all existing metadata and allows the composition of novel types of metadata. We provide a case-study to show the practical application of the grammar for generating new metadata for data quality assessment.

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Index Terms

Anatomy of Metadata for Data Curation
1. Information systems
  1. Information systems applications
    1. Data mining
      1. Data cleaning

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cover image Journal of Data and Information Quality

Journal of Data and Information Quality Volume 12, Issue 3

On the Horizon and Regular Articles

September 2020

104 pages

ISSN:1936-1955

EISSN:1936-1963

DOI:10.1145/3404101

Editor:
Tiziana Catarci
Sapienza University of Rome, Rome, Italy

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Copyright © 2020 ACM.

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Publication History

Published: 13 June 2020

Online AM: 07 May 2020

Accepted: 01 November 2019

Revised: 01 August 2019

Received: 01 March 2019

Published in JDIQ Volume 12, Issue 3

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https://doi.org/10.2514/6.2024-1133
Serra FPeralta VMarotta AMarcel P(2024)Use of Context in Data Quality Management: A Systematic Literature ReviewJournal of Data and Information Quality10.1145/367208216:3(1-41)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3672082
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https://dl.acm.org/doi/10.1145/3637872
Le Deunf JKhannoussi ALecornu LMeyer PPuentes J(2024)Data Quality Assessment through a Preference ModelJournal of Data and Information Quality10.1145/363240716:1(1-21)Online publication date: 6-Mar-2024
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