Use of Context in Data Quality Management: a Systematic Literature Review

TL;DR

This paper systematically reviews recent research on how context influences data quality management, highlighting definitions, usage, and the integration of context in current approaches.

Contribution

It provides a comprehensive analysis of recent proposals, detailing how context is defined and incorporated into data quality management strategies.

Findings

Context significantly impacts data quality definitions and management.

Recent approaches increasingly incorporate context for improved data quality.

The review identifies gaps and future directions in context-aware data quality research.

Abstract

The importance of context in data quality (DQ) was shown many years ago and nowadays is widely accepted. Early approaches and surveys defined DQ as \textit{fitness for use} and showed the influence of context on DQ. This paper presents a Systematic Literature Review (SLR) for investigating how context is taken into account in recent proposals for DQ management. We specifically present the planning and execution of the SLR, the analysis criteria and our results reflecting the relationship between context and DQ in the state of the art and, particularly, how that context is defined and used for DQ management.