Explore Golo‘s work in field data management and Digital Twin Frameworks, aimed at optimizing data reusability in field environments.
The most recent NFDI4Ing Community Meeting 2023 took place online on 27 October. Talks and presentations were focused on giving an introduction to research data management and data management plans. The meeting was rounded off with interactive workshop sessions in which current research projects served as case studies. The workshops laid the foundation for NFDI4Ing to initiate application-related harmonisation and standardisation efforts.
The next NFDI4Ing Community Meeting of the materials science and engineering community will take place in a virtual format on Friday, 08 December.
The next meeting of the SIG QA&metrics is on 8 December at 09:00. By the end of the year, the current results of the SIG (DMP, FAIR, Quality dimensions) will be summarised and new topics for the upcoming meetings will be developed.
On November 23rd & 24th, the TU Darmstadt hosts the OPEN STRUCTURES conference on data, tools and cultures in research. The conference can be attended free of charge.
The next NFDI4Ing Community Meeting of the heat and process engineering community will take place in a virtual format on Friday, 27 October. The meeting will focus on the data lifecycle and data management plans.
In our base service “Repositories and Storage” (S-4) we have reached a couple of milestones during the last year, with many new developments in the storage and repositories domains.
The base service “research software development” 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. Currently, our main projects are a JupyterHub server for the NFDI4Ing-community, a knowledge base with best practices and examples for sustainable code development, and training courses for, e.g., GitLab.
The base service “Quality assurance in RDM processes and metrics for FAIR data” in NFDI4Ing includes the support of data management plans with RDMO, the development of maturity models for research data management processes and the provision and maintenance of FAIR data metrics. The common goal is to ensure the quality of research data management in engineering research through each individual service.
By ordering the RDM activities based on their occurrence in the engineering research process, Jarves provides a structure for RDM in engineering. Based on the research’s boundaries, Jarves offers information on the next steps and available tools.