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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.
JARVES launched its alpha phase during the 112th Bibliocon in Hamburg. Meanwhile, the underlying research process is published as a paper in ing.grid. Read more on JARVES, your digital data steward!
In his recently published doctoral thesis, Nico Brandt analyses various use cases from the engineering sciences and discusses the development of a suitable research data infrastructure.
In its last meeting on April 12th, the NFDI Consortia Assembly approved three further basic service initiatives NFDI4Ing is heavily involved in: DMP4NFDI, Jupyter4NFDI, KGI4NFDI.
You want to share High-Performance Computing (HPC) data with a colleague who doesn’t have access to German HPC facilities? You want to analyze and visualize data without downloading or transferring it? Then please try out the new NFDI4Ing-service MARGE – the Multi-Access Research Gateway for HPC Experts.
The next NFDI4Ing Community Meeting taking place in June will focus on ELLEN and her extensive & heterogeneous data requirements.
Scientists from all engineering communities were invited to learn about innovative tools and services that make it easier to find, use and develop research software and handle the associated data and metadata.
A new publication discusses possible future roles of Data Management Plans (DMPs), templates, and tools in the upcoming NFDI service architecture. This position paper summarises ideas developed and collected during interdisciplinary workshops of the Data Management Planning Working Group (infra-dmp), which is part of the section Common Infrastructures of the National Research Data Infrastructure (NFDI) in Germany.
Last year, we invited the engineering communities to topical community meetings, six in total. Starting with 2024, we switch from topical to “arche-topical” community meetings, representing the NFDI4Ing archetypes. We kick things off with BETTY, our archetype focused on engineering research software!
To fight the reproducibility crisis in science, the NFDI4Ing task area ALEX is developing PlotSerializer – a Python package for serializing scientific diagrams from popular libraries like matplotlib to json.
The NFDI4Ing Metadata Profile Service is a platform that facilitates creation, curation and sharing of metadata profiles. The profiles are based on the W3C recommendation SHACL and can be created in a graphical user interface by selecting suitable terms from existing ontologies.
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.
NFDI4Ing and NFDI4Chem signed a memorandum of understanding to expand their existing cooperation in the area of data management plans.
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.
SciKGTeX enables authors to create “FAIR-by-Design” publications by enriching them with FAIR information once and in parallel to the time of creation. This information is embedded into the PDF’s XMP metadata for persistent and long-term availability.