Smart City Gnosys

Smart city article details

Title Bike Sharing Systems Data Interoperability By A Unified Station Status Concept And Big Data Solutions
ID_Doc 12177
Authors Márquez-Saldaña F.; Aranda-Corral G.A.; Borrego-Díaz J.
Year 2025
Published Journal of Traffic and Transportation Engineering (English Edition), 12, 2
DOI http://dx.doi.org/10.1016/j.jtte.2024.06.003
Abstract The impact of bike sharing systems (BSS) on urban mobility, and their study as part of the overall transport system in smart cities, has attracted significant academic interest in recent years. However, the lack of historical and standardized data in current service tools hinders the analysis and improvement of these platforms, i.e. by reusing technical data-based solutions. Big data nature (in volume, variety and velocity) of collecting BSS historical information must be also addressed, in order to take an integrated perspective. This paper describes an integrated solution to this challenge by (1) proposing a unified station status concept for recording historical information, based on the identification, study and unification of common relevant fields found in almost all BSS data warehouses, and (2) implementing a big data-inspired ETL infrastructure together with a storage optimization, methodology which not only allows to access and collect previous defined concepts but also overcomes existing big data challenge when storing BSS information. The system also consumes other external relevant information, such as weather factors, which have been aggregated, enhancing stored knowledge, with KPIs and statistics. The developed solution illustrates how it can manage over seven years of data from twenty-seven BSS, serving not only machine-to-machine communication but also human-computer communication and enabling data-driven solutions. © 2025 Periodical Offices of Chang’an University
Author Keywords Big data in mobility; Bike sharing platforms; Data acquisition; ETL


Similar Articles


Id Similarity Authors Title Published
44225 View0.899Magura Á.; Zichar M.; Tóth R.Re-Usable Workflow For Collecting And Analyzing Open Data Of ValenbisiElectronics (Switzerland), 14, 13 (2025)
39969 View0.878Tomaras D.On Urban Data Analytics And Applications In The Big Data EraProceedings - IEEE International Conference on Mobile Data Management (2024)
31459 View0.871He S.; Shin K.G.Information Fusion For (Re)Configuring Bike Station Networks With CrowdsourcingIEEE Transactions on Knowledge and Data Engineering, 34, 2 (2022)
37370 View0.869Shir B.; Prakash Verma J.; Bhattacharya P.Mobility Prediction For Uneven Distribution Of Bikes In Bike Sharing SystemsConcurrency and Computation: Practice and Experience, 35, 2 (2023)
26705 View0.868Avignone A.; Napolitano D.; Cagliero L.; Chiusano S.Flowcasting: A Dynamic Machine Learning Based Dashboard For Bike-Sharing System Management18th IEEE International Conference on Application of Information and Communication Technologies, AICT 2024 (2024)
20781 View0.868Ali A.; Salah A.; Bekhit M.; Fathalla A.Divide-And-Train: A New Approach To Improve The Predictive Tasks Of Bike-Sharing SystemsMathematical Biosciences and Engineering, 21, 7 (2024)
54328 View0.866Neilson A.; Indratmo; Daniel B.; Tjandra S.Systematic Review Of The Literature On Big Data In The Transportation Domain: Concepts And ApplicationsBig Data Research, 17 (2019)
33149 View0.863Rühmann S.; Leible S.; Lewandowski T.Interpretable Bike-Sharing Activity Prediction With A Temporal Fusion Transformer To Unveil Influential Factors: A Case Study In Hamburg, GermanySustainability (Switzerland) , 16, 8 (2024)
39708 View0.86Namiot, D; Sneps-Sneppe, MOn Bikes In Smart CitiesAUTOMATIC CONTROL AND COMPUTER SCIENCES, 53, 1 (2019)
18245 View0.859Yang X.; Xu Y.; Zhou Y.; Song S.; Wu Y.Demand-Aware Mobile Bike-Sharing Service Using Collaborative Computing And Information Fusion In 5G Iot EnvironmentDigital Communications and Networks, 8, 6 (2022)