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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 …