The eScience group at the Federal Institute for Materials Research and Testing (Bundesanstalt für Materialforschung und -prüfung BAM) in Berlin/Germany focusses on the management of research data and develops algorithms, models and software with direct applications in analytical and materials sciences.
Our group develops and provides methods for integrating research data management (RDM) strategies in the whole research process from the creation of a scientific dataset to its preprocessing and integration with further data to its publication in a scientific repository. We aim to develop services and standards that empower researchers to describe, manage and track the provenance of research data from heterogeneous sources in a central RDM system in a standardized and interoperable manner in line with the FAIR principles for scientific data management (Wilkinson et al. 2016).
The data science team of our group focuses on developing novel informatic approaches (e.g. using machine learning and applied statistics) to accelerate the search and discovery of new materials and to better understand material structures and their relationship to material properties. The goal is to develop models that provide both accurate prediction and good interpretability to increase our understanding the link between structure and properties of a material.