An OWL-based decision support framework for PET trade-offs in MaaS data sharing

Résumé fourni par la source

Backend data-sharing in Mobility-as-a-Service (MaaS) ecosystems involves multiple business entities—including MaaS providers, mobility operators, payment processors, and regulators—coordinating real-time services across organizational boundaries [2–4]. Privacy-Enhancing Technologies (PETs) such as Federated Learning, Secure Multi-Party Computation, and Differential Privacy offer technical solutions for safeguarding sensitive data in these workflows, but they introduce complex trade-offs in performance, cost, utility, and compliance [2, 3]. Existing PET literature often emphasizes user-facing or cloud-level applications, leaving a gap in structured decision support for inter-organizational PET selection in B2B environments [7]. This paper presents an ontology-based framework for modeling PET trade-offs in MaaS backend flows [2]. Our contributions include: (1) the formalization of PET-related trade-offs and stakeholder priorities, (2) the development of a Web Ontology Language (OWL)-based ontology supporting PET reasoning, and (3) two use cases—’booking flow’ and ’federated coordination’—illustrating how the ontology enables structured decision support across stakeholder roles and data-sharing scenarios [2].This work addresses a gap identified in prior MaaS and PET literature: the absence of structured decision-support for backend, multi-stakeholder data sharing. The proposed ontology is intended as a foundation for simulation-based and empirical validation in future studies.

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