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The starting signal for the next round of the Data Train programme was given on 15 January 2025 in Bremen. During a celebratory kick-off event, the central importance of data competence for research was emphasised, particularly in the context of growing data volumes and Artificial Intelligence.
Data Train is a hybrid training programme designed to enhance the data literacy of researchers at all career stages. The course is a key component of the NFDI4Health FAIR Training. The Starter Track for beginners will commence on 15 January 2025 for its next round.
The national implementation of the European Health Data Space (EHDS) was the focus of a workshop held on 18 and 19 November 2024 in Berlin. The workshop concentrated on the collaboration of stakeholders, ensuring data quality, and the perspective of data users. Juliane Fluck and Iris Pigeot from NFDI4Health participated and discussed processes and responsibilities.
Electronic patient records, telemedicine and big data: the importance of data in the healthcare sector is growing. Since the coronavirus pandemic at the latest, it has become clear that this topic affects us all. In the latest episode of the Digital Public Health Podcast, Timm Intemann from NFDI4Health talks about how the handling of data in health research is changing.
The Base4NFDI consortium develops and operates central services for the National Research Data Infrastructures (NFDI), enabling the sustainable and secure management of research data. On 20 and 21 November 2024, the first Base4NFDI User Conference (UC4B) took place at Fraunhofer Fokus in Berlin, with NFDI4Health participating.
Collaboration and data sharing are key to advancing biomedical research, and five NFDI consortia are leading the way. NFDI4Health, GHGA, NFDI4BIOIMAGE, NFDI4Immuno, and NFDI4Microbiota came together in Heidelberg from 25 to 27 November 2024 for a cross-consortium workshop focused on research data management. This joint effort aimed to explore synergies, share knowledge, and strengthen collaboration within Germany’s National Research Data Infrastructure (NFDI).
FAIR – this term is familiar in everyday life, whether on the football pitch or in the chocolate section at the supermarket. Since 2016, people have also been talking about FAIR data in research. But when are data considered FAIR? Is there such a thing as UNFAIR data? And most importantly, how can I check my own data for FAIRness?
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