Research Data Management
Research data management in engineering sciences is becoming increasingly essential. Storing, exchanging and making accessible large amounts of data, including the corresponding metadata and ontologies, is a major challenge. This is where research data management comes into play, the aim of which is to make research data digitally accessible according to the FAIR principles. Innovative concepts must be developed to simplify cooperations, enable the secure exchange of raw data and make the research data obtained available for re-use in the long term.
For this purpose, the Institute for Applied Materials - Computational Materials Science (IAM-CMS) is developing the Kadi4Mat software (Karlsruhe Data Infrastructure for Materials Science).
The following functions are the focus of development:
Data storage and simple, web-based data exchange
Publication and referencing of research data
Documentation and execution of heterogeneous and reproducible workflows
Development of tools for the handling of different data formats
Comparison of theoretical and experimental results
Integration of existing subject- and user-specific workflows and tools using a plugin infrastructure
Building a compendium of data science methods, especially machine learning
The data exchange and analysis platform Kadi4Mat is supposed to support a close cooperation between experimenters, theorists and simulators, especially in material sciences, and enable the acquisition of new knowledge and the development of novel materials.
Kadi4Mat is being developed as part of several research projects. These include:
A restricted prototype is available here.