SeRP Data Portal: A Customisable TRE Portfolio

Main Article Content

Michael Bale
Simon Thompson

Abstract

Objectives
No sole product currently captures a TRE’s (Trusted Research Environment) data assets or makes them easily accessible. While data catalogues address some of this, they lack flexibility to incorporate other TRE outputs or allow users to maintain their organisation’s brand identity.


Methods
SeRP developed a system to address this gap, leveraging in-house developers. The Data Portal platform allows users to store, find, list, and display metadata. It is built around three core components: a form builder and import tool for data capture, a fast database to store and serve results, and a template engine to render those results. This architecture enables users to create a wide range of data asset types, including dataset definitions, releases, data quality reports, provisioning details, projects, and publications.


Results
The system has been deployed for multiple TREs, including the SAIL Databank and Dementias Platform UK (DPUK), which have very different needs, but the same tool is able to meet them both. The system provides users with an intuitive interface to search datasets based on specific criteria, view high-level overviews, and drill down to detailed variable levels. The platform also feeds information into the ADR (Administrative Data Research) UK Data Catalogue. This tool is being used for managing data assets, ensuring transparency for the public and auditors, supporting researchers, and serving as a reference for funding bodies.


Conclusion
With the Data Portal now deployed across various TREs, future enhancements will focus on refining customisation and ease of use. The aim is to continue developing the platform into a comprehensive solution for TRE management, collaboration, and transparency, while feeding crucial data into broader catalogues like ADR UK's Data Catalogue.

Article Details

How to Cite
Bale, M. and Thompson, S. (2025) “SeRP Data Portal: A Customisable TRE Portfolio”, International Journal of Population Data Science, 10(4). doi: 10.23889/ijpds.v10i4.3208.