Providing Research Data Management (RDM) support and education is a central goal of NFDI4Ing. Together, the Base Service measure S-6, the Community Cluster measure CC-2, and the Special Interest Group “RDM Training and Education” are introducing new trainings on RDM with special focus on engineers. Illustration: Available learning materials The general objective of Base Service … Continued
While experimental data and methods are commonly reported as “best outcome” figure of merits, the systematic process parameters (while being crucial for achieved outcome, in particular in combination and chains of different process steps) are often neglected or buried in hard-to-access lab books and similar sources. This complicates and prolongs process optimization, especially when different printing and post-processing steps need to be combined for a specific application. The project ReCIPE aimed at setting up a tool for researchers and users of printed electronics that can grow into a broad open database on process parameters and connected outcomes for the wider academic and industry-based community.
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.