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Authors: Arturs Zogla 1 ; Inga Meirane 2 and Edgars Salna 2

Affiliations: 1 National Library of Latvia, Latvia ; 2 Datorzinibu centrs JSC, Latvia

ISBN: 978-989-758-097-0

Keyword(s): Data Quality, Data Anomalies.

Related Ontology Subjects/Areas/Topics: Enterprise Information Systems ; Information Systems Analysis and Specification ; Requirements Analysis And Management ; Software Metrics and Measurement ; Tools, Techniques and Methodologies for System Development

Abstract: There are many reasons to maintain high quality data in databases and other structured data sources. High quality data ensures better discovery, automated data analysis, data mining, migration and re-use. However, due to human errors or faults in data systems themselves data can become corrupted. In this paper existing data quality problem taxonomies for structured textual data and several improvements are analysed. A new classification of data quality problems and a framework for detecting data errors both with and without data operator assistance is proposed.

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Paper citation in several formats:
Zogla, A.; Meirane, I. and Salna, E. (2015). Analysis of Data Quality Problem Taxonomies.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-097-0, pages 445-450. DOI: 10.5220/0005462604450450

@conference{iceis15,
author={Arturs Zogla. and Inga Meirane. and Edgars Salna.},
title={Analysis of Data Quality Problem Taxonomies},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2015},
pages={445-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005462604450450},
isbn={978-989-758-097-0},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Analysis of Data Quality Problem Taxonomies
SN - 978-989-758-097-0
AU - Zogla, A.
AU - Meirane, I.
AU - Salna, E.
PY - 2015
SP - 445
EP - 450
DO - 10.5220/0005462604450450

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