Toward a New Quality Measurement Model for Big Data

Mandana Omidbakhsh; Olga Ormandjieva

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Paper

Toward a New Quality Measurement Model for Big Data

Topics: Data and Information Quality for Big Data ; Information Quality; New Data Standards

In Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1, 193-199, 2020

Authors: Mandana Omidbakhsh and Olga Ormandjieva

Affiliation: Department of Computer Science and Engineering, Concordia University, Montreal, Canada

Keyword(s): Big Data V’s, Goal-driven Hierarchical Quality Modeling, Big Data Standards.

Abstract: Along with wide accessibility to Big Data, arise the need for a standardized quality measurement model in order to facilitate the complex modeling, analysis and interpretation of Big Data quality requirements and evaluating data quality. In this paper we propose a new hierarchical goal-driven quality model for ten Big Data characteristics (V’s) at its different levels of granularity built on the basis of: i) NIST (National Institute of Standards and Technology) definitions and taxonomies for Big Data, and ii) the ISO/IEC standard data terminology and measurements. According to our research findings, there is no related measurements in ISO/IEC for important Big Data characteristics such as Volume, Variety and Valence. As our future work we intend to investigate theoretically valid methods for quality assessment of the above-mentioned V’s.

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Paper citation in several formats:

Omidbakhsh, M. and Ormandjieva, O. (2020). Toward a New Quality Measurement Model for Big Data. In Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-440-4; ISSN 2184-285X, SciTePress, pages 193-199. DOI: 10.5220/0009820201930199

@conference{data20,
author={Mandana Omidbakhsh. and Olga Ormandjieva.},
title={Toward a New Quality Measurement Model for Big Data},
booktitle={Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA},
year={2020},
pages={193-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009820201930199},
isbn={978-989-758-440-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA
TI - Toward a New Quality Measurement Model for Big Data
SN - 978-989-758-440-4
IS - 2184-285X
AU - Omidbakhsh, M.
AU - Ormandjieva, O.
PY - 2020
SP - 193
EP - 199
DO - 10.5220/0009820201930199
PB - SciTePress