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.

翻译：数字资源已在包括人口学、社会学、地理学、城市学、犯罪学与工程学在内的广泛领域中推动了前所未有的数据驱动型大规模研究。然而，由于用户隐私与行业竞争方面的考量，移动网络运营商或服务提供商所收集数据的可靠性数字数据集可用性有限，成为创新发展的主要障碍。由此导致参考数据集的缺失不仅制约了新研究方法与成果的产出，也阻碍了研究结果的可验证性与可重复性。NetMob23数据集为多学科研究社群提供了罕见机遇，使其能够获取发达国家移动应用时空消耗的丰富数据。该数据集的生成过程树立了新的质量标准，提供了法国20个都市区中68个热门移动服务所产生需求的信息，这些信息以$100\times100$ $m^2$的高分辨率进行地理定位，并在2019年连续77天内持续监测。