The Data Quality Challenge – February 2020

The Data Quality Challenge – February 2020

Due to the rapidly growing variety of techniques for the production, processing, and distribution of data, questions about their origin and quality become increasingly important. Particularly high standards are applied to data from scientific research. Good scientific practice demands quality throughout the entire data lifecycle. This paper highlights the task of scientific quality assurance and presents requirements for the enhancement of research data quality. These should be regarded as core methodological tasks in disciplinary research practices. Furthermore, the council gives recommendations for specific reputational rewards and incentives for engagement in research data quality issues via institutional and third-party funding.