Speaker
Description
The main goal of DAPHNE4NFDI is to increase FAIRness of data for the Photon and Neutron (PaN) user community to increase the scientific impact gained from this valuable data. Aims include improving data reusability, for example by providing annotated datasets for training of Machine Learning (ML)–based analysis tools. Research in the PaN community is performed at large-scale research facilities, where user groups conduct specialised experiments after competitive peer review. This shared access point gives DAPHNE4NFDI a unique opportunity to inform users, promote, and distribute research data management tools, provide services and implement FAIR principles in the community.
In its first funding period, DAPHNE4NFDI established and validated demonstrator data pipelines and databases across the following topics: TA1: Managing Data Production focuses on metadata standardization and collection during experiments for the subsequent data processing and analysis. TA2: (Meta)data Repositories and Catalogues aims to improve findability and accessibility of data via federated metadata catalogues and open data repositories. TA3: Infrastructure for Data and Software Reuse focuses on FAIR scientific software and analysis tools.
