dc.contributor.author | Martínez-Durive, Orlando E. | |
dc.contributor.author | Mishra, Sachit | |
dc.contributor.author | Ziemlicki, Cezary | |
dc.contributor.author | Rubrichi, Stefania | |
dc.contributor.author | Smoreda, Zbigniew | |
dc.contributor.author | Fiore, Marco | |
dc.date.accessioned | 2023-06-08T16:36:24Z | |
dc.date.available | 2023-06-08T16:36:24Z | |
dc.date.issued | 2023-05-24 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12761/1705 | |
dc.description.abstract | Mobile usage data have shown unprecedented potential for data-driven research in various fields such as demography, sociology, geography, urban studies, criminology, and engineering. However, the lack of reference datasets limits research methods, results, verifiability, and reproducibility of outcomes hindering innovation opportunities. We release a novel mobile usage dataset offering a rare opportunity for the multidisciplinary research community to access rich mobile data of the spatiotemporal consumption of mobile applications in a developed country. The generation process of the dataset forms a new quality standard, leading to information about the demands generated by 68 popular mobile services, geo-referenced at a high resolution of 100x100 m2 over 20 metropolitan areas in France and monitored during 77 consecutive days in 2019. | es |
dc.description.sponsorship | Comunidad de Madrid | es |
dc.description.sponsorship | French National Research Agency (ANR) | es |
dc.language.iso | eng | es |
dc.title | France Through the Lens of Mobile Traffic Data | es |
dc.type | conference object | es |
dc.conference.date | 26-29 June 2023 | es |
dc.conference.place | Naples, Italy | es |
dc.conference.title | IEEE Network Traffic Measurement and Analysis Conference | * |
dc.event.type | conference | es |
dc.pres.type | paper | es |
dc.type.hasVersion | VoR | es |
dc.rights.accessRights | open access | es |
dc.relation.projectID | 2019-T1/TIC-16037 | es |
dc.relation.projectID | ANR-22-CE25-0016 | es |
dc.relation.projectName | NetSense (Network Sensing) | es |
dc.relation.projectName | CoCo5G (Traffic Collection, Contextual Analysis. Data-driven Optimization for 5G) | es |
dc.subject.keyword | Remote sensing | es |
dc.subject.keyword | Big Data | es |
dc.description.refereed | TRUE | es |
dc.description.status | inpress | es |