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Objective Construct an innovative open-learning solution that provides comprehensive training specific to Trusted Research Environments (TRE) and the broader research community of administrative data users, irrespective of their proficiency levels. DOL offers training opportunities tailored to meet each user's unique learning needs, enabling them to utilise complex, linked administrative datasets confidently and effectively for meaningful research outcomes, thereby building capacity for sustainable national data infrastructure. Approach DOL’s innovative open-learning solution offers two learning formats: adaptive and experiential. Adaptive learning provides registered users with bitesize self-paced training based on Administrative Data Research UK's priorities. Experiential learning involves online workgroups with real-world context and practical application. They meet twice a year and are designed around specific topics with frequent guest speakers who are experts in their fields. Conclusion DOL’s innovative open-learning solution empowers TREs, such as SAIL Databank, to provide well-rounded learning that fosters community support, knowledge-sharing, and networking opportunities for its users, while gathering valuable user feedback. Users can personalise learning and test their knowledge in a flexible training environment, allowing them to take charge of their learning journey. Implication In response to the increasing demand for training services from novice to advanced users, SAIL Databank adopted DOL's dual learning approach by (1) developing training courses that cover access, process, methodology, integration, and analytical tools for SAIL TRE users, (2) engaging users in a series of workgroups focused on themed datasets including Justice, Environmental, Maternal, Education, and Core Health.

Background Not enough is known about how the family justice system is working, the children and families using these services, and their wider outcomes beyond their involvement with the family court. The Nuffield Family Justice Observatory (FJO) Data Partnership, comprising a bespoke analysis platform hosted within the Secure Anonymised Information Linkage (SAIL) Databank and analytical teams at Lancaster and Swansea Universities, has been established to address this knowledge deficit. Methods Family justice data is being deposited in the SAIL Databank. Data are acquired using a standardised split-file approach, stored in an anonymised format and made available to projects as linked data using a unique encrypted project anonymised linkage field. These data can be augmented with a wealth of available health, education and other governmental/social routinely collected datasets, and future data acquired from other sources, for a range of research projects. Results Children and Family Court Advisory and Support Service (Cafcass) Cymru data has been transferred to the SAIL Databank, and agreements to transfer the Cafcass England data are being finalised. Applications are now welcomed to use these data to enhance understanding of the family justice system and children and families involved with the family courts in public and private law. Access will be facilitated through the SAIL Databank, subject to relevant governance procedures. Conclusion We will discuss the rationale of the Nuffield FJO Data Partnership, and how it aims to a) increase capacity and capability of researchers and data scientists utilising family justice and other relevant administrative datasets, b) improve understanding about the family justice system using data from the Cafcass in England and Wales, c) demonstrate the complexities and value of data linkage, and d) assist future policy and practice development. We will discuss matching rates for the Cafcass Cymru data and linkages that have been made to other datasets within the SAIL Databank. We will also set out the support available from the partnership to those wishing to access and utilise family justice data.