Toward a New Quality Measurement Model for Big Data

Mandana Omidbakhsh, Olga Ormandjieva

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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