The overall challenge of the project is to investigate how best to enable more data-driven decision making by policy stakeholders e.g., local government. A specific example is about local governments that sit on a huge wealth of extremely informative micro-mobility data, generated as a byproduct of e-bike and e-scooter rental schemes. Rarely, however, do these authorities have the expertise, resources or infrastructure to make the most of this data. A lack of understanding of the potential benefits, coupled with a fear of the (very real) consequences should something go wrong, could also hold back data sharing.
Our project aims to overcome these challenges by 1) demonstrating ways such data can be used to inform policy making and 2) building a model Trusted Research Environment (TRE) required to handle such shared data safely. Having demonstrated the effectiveness of this approach, we then consider 3) how we can scale up TREs to support other stakeholders and include other data sets. As a national facility DAFNI can be a key enabler of these objectives both by facilitating the creation of TREs and by supporting their scale up. As part of this project, we investigate the pathways this could be realised.