From Data Quality to Big Data Quality

Author:

Batini Carlo1,Rula Anisa1,Scannapieco Monica2,Viscusi Gianluigi3

Affiliation:

1. University of Milano-Bicocca, Italy

2. Italian National Institute of Statistics (Istat), Italy

3. École Polytechnique Fédérale de Lausanne, Switzerland

Abstract

This chapter investigates the evolution of data quality issues from traditional structured data managed in relational databases to Big Data. In particular, the paper examines the nature of the relationship between Data Quality and several research coordinates that are relevant in Big Data, such as the variety of data types, data sources and application domains, focusing on maps, semi-structured texts, linked open data, sensor & sensor networks and official statistics. Consequently a set of structural characteristics is identified and a systematization of the a posteriori correlation between them and quality dimensions is provided. Finally, Big Data quality issues are considered in a conceptual framework suitable to map the evolution of the quality paradigm according to three core coordinates that are significant in the context of the Big Data phenomenon: the data type considered, the source of data, and the application domain. Thus, the framework allows ascertaining the relevant changes in data quality emerging with the Big Data phenomenon, through an integrative and theoretical literature review.

Publisher

IGI Global

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3. Bauer, F., & Kaltenböck, M. (2012). Linked Open Data: The Essentials - A Quick Start Guide for Decision Makers. Vienna, Austria.

4. Berners-Lee. Tim. (2006, July 27) Linked Data - Design Issues. Retrieved from http://www.w3.org/DesignIssues/LinkedData.html

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