The NetMob26 Dataset: A High-Resolution Multi-Source View of Public Bus Mobility in Niterói

Fuente: arXiv
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Autores principales: Domingos, Felipe, Marques-Neto, Humberto T., Pereira, Bruno, Celes, Clayson, Knoblauch, Steffen, Mota, Vinícius F. S.
Formato: Preprint
Publicado: 2026
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author Domingos, Felipe
Marques-Neto, Humberto T.
Pereira, Bruno
Celes, Clayson
Knoblauch, Steffen
Mota, Vinícius F. S.
author_facet Domingos, Felipe
Marques-Neto, Humberto T.
Pereira, Bruno
Celes, Clayson
Knoblauch, Steffen
Mota, Vinícius F. S.
contents The NetMob Data Challenge releases a comprehensive public transportation dataset from Niterói, addressing the lack of high-quality mobility and passenger demand data. Based on operational records from March 2026, the dataset combines four main sources: GPS telemetry from buses, approximately 7.2 million ticketing transactions, auxiliary transit data (routes, stops, and weather), and urban infrastructure and socio-demographic information. Together, these sources provide a detailed view of both transit supply and passenger demand. The data were preprocessed, cleaned, and anonymized to preserve privacy and improve reliability, including the removal of operational inconsistencies and anonymization of passenger identifiers. Access is restricted to challenge participants who accept the Terms and Conditions and sign an NDA. The paper describes the data collection and preprocessing pipeline, dataset organization, and mobility patterns observed in the system. The dataset supports research on topics such as public transportation efficiency, demand forecasting, accessibility analysis, service reliability, and the influence of external factors like weather on urban mobility.
format Preprint
id arxiv_https___arxiv_org_abs_2605_20263
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The NetMob26 Dataset: A High-Resolution Multi-Source View of Public Bus Mobility in Niterói
Domingos, Felipe
Marques-Neto, Humberto T.
Pereira, Bruno
Celes, Clayson
Knoblauch, Steffen
Mota, Vinícius F. S.
Physics and Society
Computers and Society
The NetMob Data Challenge releases a comprehensive public transportation dataset from Niterói, addressing the lack of high-quality mobility and passenger demand data. Based on operational records from March 2026, the dataset combines four main sources: GPS telemetry from buses, approximately 7.2 million ticketing transactions, auxiliary transit data (routes, stops, and weather), and urban infrastructure and socio-demographic information. Together, these sources provide a detailed view of both transit supply and passenger demand. The data were preprocessed, cleaned, and anonymized to preserve privacy and improve reliability, including the removal of operational inconsistencies and anonymization of passenger identifiers. Access is restricted to challenge participants who accept the Terms and Conditions and sign an NDA. The paper describes the data collection and preprocessing pipeline, dataset organization, and mobility patterns observed in the system. The dataset supports research on topics such as public transportation efficiency, demand forecasting, accessibility analysis, service reliability, and the influence of external factors like weather on urban mobility.
title The NetMob26 Dataset: A High-Resolution Multi-Source View of Public Bus Mobility in Niterói
topic Physics and Society
Computers and Society
url https://arxiv.org/abs/2605.20263