Guidelines for Research Data Integrity (GRDI) - Gregor Miller; Elmar Spiegel (Scientific Data)
Ensuring the integrity of research data is crucial for the accuracy and reproducibility of any data-based scientific study. This can only be achieved by establishing and implementing strict rules for the handling of research data. Essential steps for achieving high-quality data involve planning what data to gather, collecting it in the correct manner, and processing it in a robust and reproducible way. Despite its importance, a comprehensive framework detailing how to achieve data quality is currently unavailable. To address this gap, our study proposes guidelines designed to establish a reliable approach to data handling. They provide clear and practical instructions for the complete research process, including an overall data collection strategy, variable definitions, and data processing recommendations. In addition to raising awareness about potential pitfalls and establishing standardization in research data usage, the proposed guidelines serve as a reference for researchers to provide a consistent standard of data quality. Furthermore, they improve the robustness and reliability of the scientific landscape by emphasising the critical role of data quality in research.