Rail Transit Data Architecture-A Case Study of The Bangkok Rail Transit System

dc.contributor.authorSamitiwantikul L.
dc.contributor.authorWeerawat W.
dc.contributor.authorNorrman A.
dc.contributor.correspondenceSamitiwantikul L.
dc.contributor.otherMahidol University
dc.date.accessioned2025-11-29T18:28:36Z
dc.date.available2025-11-29T18:28:36Z
dc.date.issued2025-01-01
dc.description.abstractUrban railway systems play an important role in creating sustainable cities, especially in megacities where they serve as the backbone of mass transit. Providing connection information for urban rail systems is essential to ensure continued use of public transport by passengers. However, metro systems can be operated by different service providers, creating challenges in connecting information which may lead to reduced public transport use. Data exchange is required, therefore, to allow information to be shared with agencies responsible for passenger information. Standard data exchange enables data from several service operators to be integrated into a common data structure enhancing comprehensive connection information to support smooth travel. For Bangkok rail transit, there are three different government agencies which currently provide ten rail lines. In this case, rail transit data is individually provided leading to separate railway passenger information, and there is a lack of rail overview planning. This paper deals with the question, what data structure is required to standardize and integrate Bangkok's urban rail data? We demonstrated a rail data architecture design and data visualization analysis in the context of the Bangkok rail transit system. A data visualization tool has been used to represent the analysis results derived from the designed data structure. The results show the concept design of the data architecture for Bangkok's rail data center and the data visualization to be applied to the common rail data set.
dc.identifier.citation8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025 (2025) , 960-966
dc.identifier.doi10.1109/ICTIS68762.2025.11214963
dc.identifier.scopus2-s2.0-105022484481
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/113296
dc.rights.holderSCOPUS
dc.subjectMathematics
dc.subjectEnergy
dc.subjectSocial Sciences
dc.subjectEngineering
dc.titleRail Transit Data Architecture-A Case Study of The Bangkok Rail Transit System
dc.typeConference Paper
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105022484481&origin=inward
oaire.citation.endPage966
oaire.citation.startPage960
oaire.citation.title8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025
oairecerif.author.affiliationLunds Universitet
oairecerif.author.affiliationMahidol University

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