From Measurement to Impact: FAIR² Data Articles in Antennas and Propagation

FAIR principles are increasingly being adopted within the field of antennas and propagation to ensure that data is findable, accessible, interoperable and reusable. From antenna radiation patterns and S-parameter measurements to channel propagation models and electromagnetic simulation datasets, research data in this field is rich, complex and highly valuable - yet for too long it has remained siloed, poorly documented and undiscoverable. Currently, up to 90% of research data is lost because it is challenging to share it effectively.We have removed barriers to effective data sharing with the launch of FAIR² Data Management.- Your FAIR² Data Article will be published and indexed like any other scientific paper, so that citations count and you get recognition for your data.- Frontiers FAIR² Data Management Service organizes, cleans and curates your data so that you don’t have to.- A FAIR² Data Article, published alongside an interactive data portal and AI-ready data package, ensures that your data is discoverable, reusable and gains impact.Antenna design, propagation modelling, beamforming, metamaterials, MIMO systems, reconfigurable surfaces, and near-field/far-field measurements all generate datasets that are costly and time-consuming to produce. Making these datasets available in a structured, AI-ready format accelerates reproducibility, enables benchmarking, and opens the door to data-driven design and machine-learning-assisted optimization across the electromagnetics community.This Research Topic welcomes FAIR² Data Articles that showcase high-quality, reusable, AI-ready datasets relevant to antennas and propagation. Topics of interest include, but are not limited to:- Antenna measurement datasets (radiation patterns, gain, impedance, S-parameters)- Channel propagation and path-loss measurement campaigns- Electromagnetic simulation datasets (full-wave, ray-tracing, FDTD)- Metamaterial and metasurface characterization data- MIMO and massive MIMO channel datasets- Reconfigurable intelligent surface (RIS) measurement data- Near-field and far-field scanning datasets- Radar cross-section and scattering measurements- AI/ML training datasets for antenna design and optimization- Benchmarking datasets for computational electromagnetics solvers Topic editors: Francisco Falcone Source: https://www.frontiersin.org/research-topics/80092/from-measurement-to-impact-fair2-data-articles-in-antennas-and-propagation