The NetMob26 Dataset: A High-Resolution Multi-Source View of Public Bus Mobility in Niter\'oi

TL;DR

The paper introduces the NetMob26 dataset, a detailed, multi-source high-resolution dataset of public bus mobility in Niterói, enabling advanced research on transit efficiency, demand, and external influences.

Contribution

It provides a comprehensive, preprocessed, and anonymized dataset combining GPS, ticketing, auxiliary, and socio-demographic data for urban mobility analysis.

Findings

Detailed view of transit supply and passenger demand.

Preprocessed and anonymized data ensuring privacy and reliability.

Supports research on transportation efficiency and external factors.

Abstract

The NetMob Data Challenge releases a comprehensive public transportation dataset from Niter\'oi, 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.