Research Data Management


In research today, many digital results arise from experiments, simulations or measurements. Often, however, only the most important data are stored for the long term, for example, if they are part of a scientific publication. The software Kadi4Mat makes it technically possible to store as much data as possible in such a way that a benefit can be derived from it. On the one hand, the simple and mostly automatic acquisition of the data is particularly important, while, on the other hand, the correct storage of the information is also very important: The more data is stored, the more important the correct cataloguing and classification of the data does become, which later prevents you from looking for the needle in the haystack. For this reason, software like Kadi4Mat is required to store information in a meaningful way, to make it available in the long term and to relate it to one another. This is the only way to efficiently search, analyse, visualise and compare the accumulated data, in order to maximise the information gained from scientific work.

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 - Microstructure Modelling and Simulation (IAM-MMS) 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:

The working group also shows strong activities in the establishment and networking towards a national research data infrastructure through participation in NFDI4Ing.

More information can be found here.