The DataPLANT consortium, a German National Research Data Infrastructure (NFDI), aims to provide plant researchers a robust and sustainable infrastructure for managing research data. Since the complexity of research data continues to grow, effective methods for managing, annotating, and sharing this data becomes increasingly important. DataPLANT integrates different established concepts for...
The collection and use of sensor data is crucial for scientists monitoring and observing the Earth's environment. In particular, it enables the evaluation of real natural phenomena over time and is essential for the validation of experiments and numerical simulations. Assessment of data quality beyond statistics includes knowledge and consideration of sensor state, including operation and...
The microstructure of materials is characterized by crystallographic defects, which ultimately determine the material properties. In computational materials science, methods and tools are used to predict and analyze defect structures. The increase of computational power has led to the generation of large amounts of complex and heterogeneous data, increasing the need for the implementation of...
