SOC-PHCYMay 18

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

arXiv:2605.2026351.5
AI Analysis

Provides a rare high-quality, multi-source public transit dataset for researchers studying urban mobility and transportation systems.

The paper introduces the NetMob26 dataset, a high-resolution multi-source public bus mobility dataset from Niterói, combining GPS telemetry, 7.2 million ticketing transactions, and auxiliary data to support research on transit efficiency, demand forecasting, and accessibility.

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.

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