Infrastructure and Services - Useable Data

The UK is home to a wide variety of different types of data, often with similar data held in different forms which makes bringing them together difficult. This programme will develop tools and approaches to bring that data together in standardised ways so that it is easier to use in health-related research, allowing researchers to work at larger scale and breadth to unlock new opportunities to improve health and wellbeing in the UK, for example through improving how new drugs and other approaches are tested through clinical trials.

This work is funded by the UKRI Medical Research Council, UKRI Engineering and Physical Sciences Research Council, UKRI Economic and Social Research Council, Department of Health and Social Care, National Institute for Health Research (England), Chief Scientist Office (Scottish Government), Health and Care Research Wales, Public Health Agency HSC (Northern Ireland), British Heart Foundation and Cancer Research UK

The Useable Data programme will develop the tools and data engineering capability that enable seamless access to FAIR data, including Phenomics and Prognostic Atlas capabilities (dataset search, classification, and efficient metadata browsing tools described via open dataset catalogues, common data models and data dictionaries), and transforming data, and providing resources for clinical trials. It will focus on alignment of approaches to data and metadata (including phenotypes) with the aim of developing and driving adoption of consistent standards and formats for data and metadata. The work follows a principle of ‘minimal restriction’ rather than mandating a particular standard or platform; increasing interoperability of studies and datasets; and transparency of standards or formats used. It will achieve this through building reuseable, open and extensible software infrastructure through workstreams in ‘Data Standards', ‘Phenomics and Prognostic Atlas’ and ‘Transforming Data for Trials’ which will support research across the data-to-analysis pipeline. With the overarching aim of increased interoperability, this programme will allow research to take place at a wider scale, across a greater breadth of datasets and modalities.