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Authors: Milen S. Marev ; Ernesto Compatangelo and Wamberto W. Vasconcelos

Affiliation: Department of Computing Science, University of Aberdeen, Aberdeen, AB24 3UE, U.K.

Keyword(s): Data Quality, Intrinsic Data Quality, Data Quality Indicators, Pre-processing, Numerical Data Quality, Numerical Data Quality.

Abstract: This paper focuses on data quality indicators conceived to measure the quality of numerical datasets. We have devised a set of three different indicators, namely Intrinsic Quality, Distance-based Quality Factor and Information Entropy. The results of quality measures based on these indicators can be used in further data processing, helping to support actual data quality improvements. We argue that the proposed indicators can adequately capture in a quantitative way the impact of different numerical data quality issues including (but not limited to) gaps, noise or outliers.

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Paper citation in several formats:
Marev, M.; Compatangelo, E. and Vasconcelos, W. (2020). Intrinsic Indicators for Numerical Data Quality. In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS; ISBN 978-989-758-426-8; ISSN 2184-4976, SciTePress, pages 341-348. DOI: 10.5220/0009411403410348

@conference{iotbds20,
author={Milen S. Marev. and Ernesto Compatangelo. and Wamberto W. Vasconcelos.},
title={Intrinsic Indicators for Numerical Data Quality},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS},
year={2020},
pages={341-348},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009411403410348},
isbn={978-989-758-426-8},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - IoTBDS
TI - Intrinsic Indicators for Numerical Data Quality
SN - 978-989-758-426-8
IS - 2184-4976
AU - Marev, M.
AU - Compatangelo, E.
AU - Vasconcelos, W.
PY - 2020
SP - 341
EP - 348
DO - 10.5220/0009411403410348
PB - SciTePress

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