Big Data Analytics: A Classification of Data Quality Assessment and Improvement Methods

Abstract

The categorization of data and information requires re-evaluation in the age of Big Data in order to ensure that the appropriate protections are given to different types of data. The aggregation of large amounts of data requires an assessment of the harms and benefits that pertain to large datasets linked together, rather than simply assessing each datum or dataset in isolation. Big Data produce new data via inferences, and this must be recognized in ethical assessments. We propose a Classification of Data Quality Assessment and Improvement Methods The use of schemata such as this will assist decision-making by providing research ethics committees and information governance bodies with guidance about the relative sensitivities of data. This will ensure that appropriate and proportionate safeguards are provided for data research subjects and reduce inconsistency in decision making.