The NetMob25 Dataset: A High-resolution Multi-layered View of Individual Mobility in Greater Paris Region
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arXiv
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| Autori principali: | , , , , , , , , , |
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| Natura: | Preprint |
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2025
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| author | Chasse, Alexandre Kouam, Anne J. Viana, Aline C. Stanica, Razvan Lobato, Wellington V. Ramos, Geymerson Deperle, Geoffrey Bouroudi, Abdelmounaim Bussod, Suzanne Molano, Fernando |
| author_facet | Chasse, Alexandre Kouam, Anne J. Viana, Aline C. Stanica, Razvan Lobato, Wellington V. Ramos, Geymerson Deperle, Geoffrey Bouroudi, Abdelmounaim Bussod, Suzanne Molano, Fernando |
| contents | High-quality mobility data remains scarce despite growing interest from researchers and urban stakeholders in understanding individual-level movement patterns. The Netmob25 Data Challenge addresses this gap by releasing a unique GPS-based mobility dataset derived from the EMG 2023 GNSS-based mobility survey conducted in the Ile-de-France region (Greater Paris area), France. This dataset captures detailed daily mobility over a full week for 3,337 volunteer residents aged 16 to 80, collected between October 2022 and May 2023. Each participant was equipped with a dedicated GPS tracking device configured to record location points every 2-3 seconds and was asked to maintain a digital or paper logbook of their trips. All inferred mobility traces were algorithmically processed and validated through follow-up phone interviews.
The dataset includes three components: (i) an Individuals database describing demographic, socioeconomic, and household characteristics; (ii) a Trips database with over 80,000 annotated displacements including timestamps, transport modes, and trip purposes; and (iii) a Raw GPS Traces database comprising about 500 million high-frequency points. A statistical weighting mechanism is provided to support population-level estimates. An extensive anonymization pipeline was applied to the GPS traces to ensure GDPR compliance while preserving analytical value. Access to the dataset requires acceptance of the challenge's Terms and Conditions and signing a Non-Disclosure Agreement. This paper describes the survey design, collection protocol, processing methodology, and characteristics of the released dataset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05903 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The NetMob25 Dataset: A High-resolution Multi-layered View of Individual Mobility in Greater Paris Region Chasse, Alexandre Kouam, Anne J. Viana, Aline C. Stanica, Razvan Lobato, Wellington V. Ramos, Geymerson Deperle, Geoffrey Bouroudi, Abdelmounaim Bussod, Suzanne Molano, Fernando Computers and Society Information Retrieval High-quality mobility data remains scarce despite growing interest from researchers and urban stakeholders in understanding individual-level movement patterns. The Netmob25 Data Challenge addresses this gap by releasing a unique GPS-based mobility dataset derived from the EMG 2023 GNSS-based mobility survey conducted in the Ile-de-France region (Greater Paris area), France. This dataset captures detailed daily mobility over a full week for 3,337 volunteer residents aged 16 to 80, collected between October 2022 and May 2023. Each participant was equipped with a dedicated GPS tracking device configured to record location points every 2-3 seconds and was asked to maintain a digital or paper logbook of their trips. All inferred mobility traces were algorithmically processed and validated through follow-up phone interviews. The dataset includes three components: (i) an Individuals database describing demographic, socioeconomic, and household characteristics; (ii) a Trips database with over 80,000 annotated displacements including timestamps, transport modes, and trip purposes; and (iii) a Raw GPS Traces database comprising about 500 million high-frequency points. A statistical weighting mechanism is provided to support population-level estimates. An extensive anonymization pipeline was applied to the GPS traces to ensure GDPR compliance while preserving analytical value. Access to the dataset requires acceptance of the challenge's Terms and Conditions and signing a Non-Disclosure Agreement. This paper describes the survey design, collection protocol, processing methodology, and characteristics of the released dataset. |
| title | The NetMob25 Dataset: A High-resolution Multi-layered View of Individual Mobility in Greater Paris Region |
| topic | Computers and Society Information Retrieval |
| url | https://arxiv.org/abs/2506.05903 |