Evaluation and Harmonization of Data Quality Criteria: Insights from Expert Interviews for Legal Application

Authors: Louis Sahi

ABSTRACT

This article presents a framework for assessing data quality, highlighting its growing importance in today’s data-driven organisations. With the emergence of regulatory frameworks such as the GDPR and the EU’s Open Data Regulation, the need for robust data quality standards has never been more important. The study begins by addressing the inconsistencies in current data quality criteria (DQCs) and proposes a unified list, derived from an extensive literature review. By aligning these standards with the broader context of data processing, including governance and lifecycle management, the research aims to create a coherent approach to data quality. Expert interviews were conducted with data management and legal professionals to validate the framework. This involvement not only consolidates the DQCs, but also ensures their compliance with EU regulations. The findings underline the need for collaborative data processing (CDP) in decentralised environments, such as the European Common Data Spaces, and highlight the importance of trust, legal compliance and reliability of shared data. Ultimately, this research contributes to bridging the gap between academic methodologies and practical industrial applications of data quality assessment, fostering a more secure and efficient data landscape. 

Keywords: Data Quality Criteria – Collaborative Data Processing – Trust– Reliability – Compliance

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