Project overview

Soul Paint is an immersive, virtual reality platform that enables people to visualise emotions, bodily sensations, and lived experiences through expressive 3D artwork. As the platform evolves towards use in healthcare and research settings, new challenges emerge around patient data ownership, consent, privacy, identity management and secure data sharing.

This secondment will develop a research-informed framework for the governance and technical architecture of Soul Paint data. The project will explore privacy-preserving infrastructure, consent models, regulatory compliance requirements, and future integration with healthcare systems. This will support the development of a foundation for responsible deployment within research and clinical environments.

Objectives and deliverables

The project addresses several TIPSS challenges in the collection and use of sensitive emotional, behavioural and creative XR data.

Objectives:

1. Map the legal, ethical, technical, and governance requirements for storing and sharing Soul Paint data across research and healthcare environments.

2. Explore person-centred approaches to data ownership, consent, and data sharing from a Responsible Research and Innovation perspective.

3. Explore privacy-preserving architectures, including federated approaches, local data hosting models and secure institutional infrastructure.

4. Assess future mechanisms for data withdrawal, deletion and machine learning across potential use cases.

Deliverables:

1. Soul Paint TIPSS risk and governance assessment.

2. Infrastructure architecture framework (technical architecture framework describing secure deployment options for Soul Paint data across academic, healthcare and research environments. It will compare centralised, federated and hybrid infrastructure models. It will also identify benefits, risks, implementation and governance implications.)

3. Guidance for future integration models grounded in responsible research and innovation (e.g. consent models, data withdrawal and participant rights mechanisms, recommendations for future AI integration, and accountability models).