Project overview
The UMIS project investigated mechanisms for increasing user trust in Mobility-as-a-Service (MaaS) in an Internet of Things (IoT) ecosystem for next-generation transportation-systems.
IoT-enabled MaaS systems bring together multiple transport networks and services into a single cohesive user experience enabling citizens to use multiple modes of transport to find and complete their journeys. For a user to plan a journey, they will need to provide their travel plans (to the MaaS), and to make a journey they will need to supply payment credentials.
At the same time, end-users also need to consume data from the system.
Collaborative sharing and linking of safe, useful data between different stakeholders under secure and rights-respecting conditions will be vital for building a trustworthy process and making the service highly trusted.
Effective, appropriate, secure and privacy-preserving data usage, sharing, and re-usage requires well-defined data governance roles and processes.
This project aimed to create a data governance framework that is by-design trustworthy and compliant with UK data protection law facilitating legal and ethical data reusage between MaaS stakeholders.
The project developed models used to protect privacy of user data especially during data analytics, inferencing and exchange, resulting in a Privacy-preserving and Privacy-enhancing model for data governance for next-generation transportation systems.
IoT-enabled MaaS systems bring together multiple transport networks and services into a single cohesive user experience enabling citizens to use multiple modes of transport to find and complete their journeys. For a user to plan a journey, they will need to provide their travel plans (to the MaaS), and to make a journey they will need to supply payment credentials.
At the same time, end-users also need to consume data from the system.
Collaborative sharing and linking of safe, useful data between different stakeholders under secure and rights-respecting conditions will be vital for building a trustworthy process and making the service highly trusted.
Effective, appropriate, secure and privacy-preserving data usage, sharing, and re-usage requires well-defined data governance roles and processes.
This project aimed to create a data governance framework that is by-design trustworthy and compliant with UK data protection law facilitating legal and ethical data reusage between MaaS stakeholders.
The project developed models used to protect privacy of user data especially during data analytics, inferencing and exchange, resulting in a Privacy-preserving and Privacy-enhancing model for data governance for next-generation transportation systems.
Staff
Lead researcher
Other researchers
