We are pleased to announce the first stable 1.0 release of the open source virtual research environment Kadi4Mat. This version marks the culmination of several years of work and improvements since the initial release of Kadi4Mat and also includes the first stable version of its application programming interface.
We incorporated comments and feedback from the NFDI4ING community into this updated version to better support data management planning and make use of new features in RDMO.
We are once again looking for researchers in the engineering sciences to share with us their experiences and needs for handling research data.
NFDI4Ing’s Special Interest Groups (SIGs) are the place for exchange between NFDI4Ing and interested experts from the community. In the SIG “RDM Training”, we work together on reviewing and improving RDM trainings.
By utilizing large language models to provide an automated method for extracting knowledge from a vast amount of literature and integrating it with the research data management platform, users will be offered more intelligent data management and analysis methods.
GOLO’s Field Database Platform (FDP) redefines field data management with digital twin technology. It offers real-time visualization, interactive analysis, and efficient filtering, turning complex sensor data into actionable insights and enhancing research efficiency.
The transparent and sustainable scientific exchange of methods, results and findings along the FAIR principles is one of the greatest challenges facing science today. To show how these challenges can be met with innovative technologies, the most recent NFDI4Ing Community Meeting presenting the work of our archetype ELLEN took place on June 6th.
NFDI4Ing provides infrastructure, best practices and templates to make research software and its development more replicable and reproducible while improving the quality of the written code. For the further improvement of the our RDM knowledge base and our JupyterHub prototype, we are looking for your collaboration and input!
For the quality assurance of research data management, NFDI4Ing has developed maturity models that enable researchers to assess the implementation of data management in their research projects.
With our benchmark suite we investigated object storages. Based on the results, we compiled usage guidelines to improve transfer speeds and continuously monitor connection quality.
