Veracity is a critical dimension of Big Data, as it is related to the quality of data. Its role is even more important when Big Data are supposed to be a counterpart or a substitute of official data. While the former is usually unstructured and the collecting procedures are unsupervised, the latter is collected in accordance to strict and rigorous methodologies. Mobile phone traces, alternatively called Cellphone Big Data (CBD), can be ascribed among the most popular Big Data typology in transportation analyses, even if they are affected by some biases. This research effort is aimed to contribute to the discussion on Big Data and to shed light on the need of a rigorous assessment of the dataset quality. An in-depth evaluation process was carried out with the comparison of CBD to groundtruth data, namely traffic-related data collected by Anas S.p.A. – Gruppo Ferrovie dello Stato Italiane along a major Italian trunk road. What emerges from this paper is the sensitiveness of CBD to some variables related to both cinematic characteristics of traffic, mobile phone network characteristics and the traffic condition, namely the vehicle occupancy rate.
Nalin, A., Vignali, V., Lantieri, C., Cappellari, D., Zamengo, B., Simone, A. (2024). Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring. JOURNAL OF TRANSPORT GEOGRAPHY, 118, 1-11 [10.1016/j.jtrangeo.2024.103930].
Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring
Nalin, Alessandro
;Vignali, Valeria;Lantieri, Claudio;Simone, Andrea
2024
Abstract
Veracity is a critical dimension of Big Data, as it is related to the quality of data. Its role is even more important when Big Data are supposed to be a counterpart or a substitute of official data. While the former is usually unstructured and the collecting procedures are unsupervised, the latter is collected in accordance to strict and rigorous methodologies. Mobile phone traces, alternatively called Cellphone Big Data (CBD), can be ascribed among the most popular Big Data typology in transportation analyses, even if they are affected by some biases. This research effort is aimed to contribute to the discussion on Big Data and to shed light on the need of a rigorous assessment of the dataset quality. An in-depth evaluation process was carried out with the comparison of CBD to groundtruth data, namely traffic-related data collected by Anas S.p.A. – Gruppo Ferrovie dello Stato Italiane along a major Italian trunk road. What emerges from this paper is the sensitiveness of CBD to some variables related to both cinematic characteristics of traffic, mobile phone network characteristics and the traffic condition, namely the vehicle occupancy rate.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.