Multi-TRE analysis : can a common governance model breaks data silos?#

Chair: Fatemeh Torabi (Swansea University)

Prompts#

Work from Swansea Unversity has shown that major UK TREs are operating on different governance models (Torabi et al. 2023). This breakout will discuss whether and how a common governance model can be achieved.

  • What percentage of the problem of data silos will be solved by a common governance model?

  • What can be incorporated in a common governance model, and what can’t?

  • How do governance models need to be updated to work for a multi-TRE network, rather than just individual TREs?

Summary#

The Swansea paper was referenced, highlighting how it found that the problem of multi-TRE analysis can be addressed.

The question was then asked - how do you get there, in a trustworthy and safe way?

It was discussed whether an entirely new framework was needed, or whether existing arrangements can be adapted, and whether solutions should exist within TREs, or new TREs shuld be built.

Many next steps were discussed, with a special focus on lobbying as a community to government, data providers and policy makers to move towards a more common, aligned approach to data provision and research.

Raw notes#

  • Variation in data governance arrangements result in silos, barrier to federated analysis across data held across multiple TREs

  • Review of TREs involved in federated collaborations (?) and their governance arrangement models: https://ijpds.org/article/view/2164

  • Conclusions of the paper: problem can be addressed considerably through adoption of a common governance model

  • How do you get there?

  • Changing existing models and cultures is hard

  • Participating with another legal entity the responsible party will still stay the responsible party

  • In a joint partnership the new model has to distribute the risk across the partnership group

  • MRC example by Paul Colville-Nash: accessing GPs in 4 nations, relationship between parties

  • Infrastructure requirements can be quite different, standardisation would need to encompass these

  • Old TREs have very similar model but different naming

  • How do we get there? and how it all works?

  • How do we think the world works? do we bring data to researchers or researchers to data?

  • What feels more trustworthy from data owners view

  • How safe are the existing TREs?

  • How a structure can enable multi-TRE collaboration

  • Are there examples where this has been done successfully?

  • Use-case with rare disease where large sample size needed (but needed complex sharing agreements)

  • COVID: federation was not solved

  • Funder looking at global population level

  • To what extent do we need a completely new framework, if changing existing arrangements is too hard? Ripping up existng governance arrangements carries risk of undermining trust.

  • should we moving with faster speed in this space? getting any type of data takes time and we may need to let time solve things

  • Funders would challenge establishment of a new TRE

  • the wave is changing to establishment of TREs inside TREs with shared governance models

  • the existing TRE is a free market, should we and do we want to introduce new ‘TRE products’ within existing trusted TREs, that are designed around ability to federate/carry out multi-TRE analyses. That way data providers benefit from the experience of the established host TRE. This can enable a gradual migration from one governance model to another without needing to rip up entire TRE governance model (analogous to a software migration). Can start with small number of such TRE2.0 products and expand more organically (land and expand).

  • traumatic brain injury hub is a secure dataset which is living in a separate hub within DPUK

  • is this a tailored access model per dataset? We need to separate out the data set from the access and analysis of them - SDE vs TRE. And then allow the existing IG to see how the new approach is a small acceptable growth.

  • TRE operators have to convince data providers not just to provide the data, but also to curate it and document it, repeated n times, all required before you can provide the data to a project. Onus on data owner not consistent, this is often done by the TRE. Very costly to undertake.

  • ‘Ground truth’ of datasets/versioning if multiple versions are held across different TREs?

Next steps#

  • Bringing the governance models close enough to each other to be harmonised enough to give FAIR data as the way forward

  • to build a communication line between the legal entities called ‘Data Owners’ giving their data to ‘Data Providers’ to facilitate a balanced risk and outcome delivery Primary objective in this model is to reach a balance and lower cost

  • Talk lines between TRE-community and government for implementation of regulations

  • For specific use cases we have achieved it, where to go next is how to expand the solutions to a more general population-wide use case in multi-TRE work

  • Streamline a repeated process for provisioning data via different paths

  • In some sense we have the opportunity it feels. ie Cloud based models offer a way of rebuilding new

  • Get rid of different instances of similar entities in a cloud environment

  • Adoptation of the existing models (or creation of a new one???)

  • We as a community need to be lobbying for a change of focus for data owners / controllers to make sure that they recognise that they have a purpose and responsbility to make the harder research problems possible, the time to research faster and the costs to do the research lower (time and £). If not this community then who? We need to act as a lobbying function into government policy makers.