  Digital sources have been enabling unprecedented data-driven and large-scale
investigations across a wide range of domains, including demography, sociology,
geography, urbanism, criminology, and engineering. A major barrier to
innovation is represented by the limited availability of dependable digital
datasets, especially in the context of data gathered by mobile network
operators or service providers, due to concerns about user privacy and
industrial competition. The resulting lack of reference datasets curbs the
production of new research methods and results, and prevents verifiability and
reproducibility of research outcomes. The NetMob23 dataset offers a rare
opportunity to the multidisciplinary research community to access rich data
about the spatio-temporal consumption of mobile applications in a developed
country. The generation process of the dataset sets a new quality standard,
leading to information about the demands generated by 68 popular mobile
services, geo-referenced at a high resolution of $100\times100$ $m^2$ over 20
metropolitan areas in France, and monitored during 77 consecutive days in 2019.
