Ideally, researchers can incorporate existing, established and tested research software into their own work. BETTY tries to help researchers in finding existing software suitable for their needs, developing new software, and publishing software artifacts in a sustainable and reproducible way.
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Text and data mining methods offer the potential to gain new insights from publications. The NFDI4Ing base service automated data and knowledge discovery in engineering literature is developing the legal and technical basis for making engineering literature accessible for this purpose.
Providing Research Data Management (RDM) support and education is a central goal of NFDI4Ing. That is why we are developing a learning platform for RDM with a special focus on engineering sciences. The challenge is to design it subject-specific and attractive for motivated, self-paced learning. To meet this requirement, we need your input!
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.
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.
