Note: This is an automated translation (by DeepL) of the original german article.
The current COVID-19 epidemic impressively demonstrates that sustainable data processes (standardized, documented and reproducible) are an absolute must in order to be able to analyze and evaluate complex and networked systems and thus master their challenges. The two FFG-funded research projects DataPrepHealth and ReproHealth aim at exactly this problem: to make data processes documentable and reproducible. With the submission of the last interim report these DEXHELPP research projects enter their final year and thus the home stretch.
The exciting thing about these projects is their mutual complementarity. While DataPrepHealth deals with pure data preparation, ReproHealth builds on the data prepared and cleaned in this way. This data is used to make forecasts or to support decision-making processes. The goal of the overall project is therefore to first prepare raw data using the process of the first project and then to cast it into a suitable model with the help of the second project. This process also enables a uniform documentation of both steps and thus the entire process.
For both projects, the reproducibility and documentability of the individual steps is of central importance. Furthermore, both projects address the important additional requirements of the health care system (such as anonymization of data).
The projects are funded by the FFG Call "Industrienahe Dissertationen" and are carried out by Melanie Zechmeister (DataPrepHealth) and Nadine Weibrecht (ReproHealth).
Translation by DeepL