Abstract
As Global Navigation Satellite Systems (GNSS) infrastructure expands and more satellites are launched, the number of signals and measurements available to users increases, resulting in a corresponding rise in data generation rates. GNSS receivers with the ability to process triple frequency measurements and multi-constellation reception, have been complemented with the massive deployment of connected, GNSS-enabled devices such as smartphones, wearables, and IoT sensors, triggering the growth of a highly dispersed cloud of GNSS data. This trend observed in other domains presents both challenges and opportunities for applications of GNSS technology.The scientific exploitation of GNSS data involves developing new concepts through the analysis of the aforementioned sources of information. Traditionally, the extraction of insights from GNSS data has relied on searching and downloading datasets from multiple repositories. These datasets provided by numerous organisations are scattered worldwide, containing gems of information difficult to track and discover. This approach hinders research productivity, as scientists are forced to shift their focus from data exploration, analysis, modelling, visualization, and realisation of conclusions to a long list of repetitive and manual tasks of little added value.The GNSS Science Support Centre (GSSC) hosts ESA’s innovative Digital Platform for GNSS, GSSC Now, which integrates a large GNSS repository with cutting-edge features for data exploration and analysis. The paper presents key functionalities of GSSC Now and highlights its value through case studies of real-world GNSS applications. This platform expands established computational limits, placing the data source side-by-side with cloud computing capabilities. The change of paradigm provides scientists with seamless execution of Machine Learning models, interactive algorithms and visualisation tools on a vast repository of GNSS data, removing barriers that hinder research productivity.
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