Data processing is usually not a single task, but in general relies on a chain of tools. To achieve transparency, adaptability, and reproducibility of (computational) research, the FAIR principles must therefore be applied to all components of the research process. This includes the tools (i.e. any research software) used to analyze the data, but also … Continued
From its inception, members of NFDI4Ing have been working on a concept for the publication and organization of standards in the field of research data. By now, the concept is quite advanced and ready for the next step. The working group “Standardisation” (CC-5) is looking for interested persons from the community to support the work and to get the implementation underway.
ield experiments mostly take place under difficult conditions. Due to the large number of sensors and computers, large amounts of data are usually generated, and data acquisition can be affected by small errors or external events. For further processing and analysis of field data, verification of data quality is essential. To assist researchers, TA Golo has documented a website – the Data Quality Metrics Website.
The recently published “Guidelines zum Text und Data Mining für Forschungszwecke in Deutschland” describe under which conditions text and data mining may be carried out for scientific purposes and what risks exist. An online workshop, “Urheberrechtliche Fragestellungen bei der Gestaltung von Dienstleistungen zum Text und Data Mining” will take place on April 25th to address copyright issues in designing services to support text and data mining.
NFDI4Ing cordially invites you to participate with a contribution on this years conference! The motto of the NFDI4Ing conference 2023 is “Innovation in Research Data Management: Bridging the gaps between disciplines and opening new perspectives for research in engineering science”.
The international online journal ing.grid is now accepting submissions addressing FAIR data management in engineering sciences. With an open access policy, the journal bridges a gap in the field, offering a platform and recognition for sound scientific practice in generating research data, developing reusable tools for processing that data and curating the data to make it findable, accessible, interoperable, and reusable (FAIR).
Getting and staying in touch with the community is the essence of NFDI4Ing. That’s why the consortium offers a broad variety of exchange formats like community meetings, conferences, and workshops. To meet the needs of the community, we continuously work to improve our engagement processes.
It was a close contest, but in the end two nominees prevailed in the NFDI4Ing Awards 2022 against 41 other contributors. We happily congratulate the winners, Wendy (Pengyin) Shan from the University of Alberta Library in Canada, and Rory Macneil from Edinburgh, Scotland. The awards were endowed with 500€ each, sponsored by the WZL Aachen Stiftung.
Virtually all scientific output is communicated through text publications, only suitable for humans and precluding searches beyond simple text matching. By contrast, SciMesh disseminates results as machine-actionable, comprehensive knowledge graphs.
The NFDI4Ing Task Area DORIS designs transferable research-data management concepts and tools for data from high-performance measurement and computation (HPMC), enables, and supports the community to apply these solutions. In order to standardize and facilitate RDM for our peer group, we provide support for the complete data life cycle.