Achieving interoperability in mobility as a service: a data ecosystem leveraging Semantic Web Technologies

Essawy, Shams Khaled Elhosseny Ghazy (2024) Achieving interoperability in mobility as a service: a data ecosystem leveraging Semantic Web Technologies. PhD thesis, University of Nottingham.

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Abstract

As urbanization continues to accelerate worldwide, the need for efficient and interconnected transportation systems becomes increasingly critical. Mobility as a Service (MaaS) has emerged as a promising solution to address this challenge by integrating various modes of transportation into a seamless and user-centric experience. However, the success of MaaS hinges on achieving robust interoperability among stakeholders, a task fraught with complexities and disagreements.

This research delves into the heart of MaaS interoperability, aiming to design a solution that standardises the entry of transport operators into MaaS data ecosystems. Through a comprehensive qualitative study involving 65 diverse experts, this investigation identifies nine key areas of disagreement regarding MaaS implementation, shedding light on the underlying rationale behind these disputes. Two distinct mindsets, "Private car-first" and "Public transport-first," emerge as influential factors shaping these disagreements caused by the transportation challenges faced by the participants.

The study also unveils the current and desired levels of business and data interoperability within MaaS ecosystems, revealing the challenges and efforts taken to bridge the gap. The analysis results in a set of interoperability requirements for business and data including adhering to open standards, cross-mode interoperability, cross-domain interoperability, adaptive business models, standardised contracts, among others. The results contribute to policy and regulatory frameworks needed to foster interoperable MaaS ecosystems by offering an interoperability roadmap as a guidance tool.

At the heart of this research lies the innovative Mobility Profiles Taxonomy, a solution designed to standardize the entry of transport operators into MaaS data ecosystems. The taxonomy classifies the different types of operations into five core layers: Planning, Drivers, Booking, Ticketing, and Payment. Each layer consists of distinct cases which, when put together, encompass a complete operator’s data profile required to move a passenger from A to B. This taxonomy, marked by modularity, customization, and alignment features, promises to prevent the creation of silo-ed Mobility Data Spaces. While a machine-readable version remains a future endeavor, a demonstration of a data exchange process shows the practicality of applying the taxonomy, with the incorporation of Semantic Web Technologies, showcasing the potential of its use for automated data exchange. The development of these Mobility Profiles provides a structured framework for standardising Data Spaces but also enable the identification of vertical and horizontal gaps in interoperability across these operator profiles.

However, this journey is not without limitations, including the specific scope of the taxonomy and the need for further validation and quantification of the proposed solutions. Nonetheless, the research paves the way for future investigations, urging a deeper dive into regional intricacies, user profiles, and extended areas of interoperability.

By combining the proposed roadmap and taxonomy, this research offers a thorough guide for the development of Mobility as a Service ecosystems with a core focus on the maturity of interoperability. Setting the defined interoperability requirements as a target for ecosystems is expected to enable a better integration at a legal, organisational, semantic, and technical layer. The roadmap serves as a high-level reference for designing policies that address legal and organisational interoperability, whilst the taxonomy contributes to alleviating existing semantic and technical interoperability challenges. By addressing disagreements, defining requirements, and proposing an innovative taxonomy, the research lays the foundation for a more interconnected and efficient future of urban mobility.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Wong, Jing-Ying
Tang, Yu Hoe Ioannes
Colpaert, Pieter
Keywords: MaaS, mobility as a service, smart mobility, smart transportation, mobility data spaces, data interoperability, MaaS taxonomy
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculties/Schools: University of Nottingham, Malaysia > Faculty of Science and Engineering — Engineering > Department of Civil Engineering
Item ID: 77954
Depositing User: Ghazy Essawy, Shams
Date Deposited: 27 Jul 2024 04:40
Last Modified: 27 Jul 2024 04:40
URI: https://eprints.nottingham.ac.uk/id/eprint/77954

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