Findable, Accessible, Interoperable, & Reusable (FAIR) curated mental health data

This core activity supports the DATAMIND Hub to continuously catalogue and curate relevant UK mental health data rich datasets across the four nations. These datasets are within fields such as genomics, routine care, cohort and trials for research, development and innovation across academia, the NHS, third sector, policy makers and the industry.

A key element for FAIR curated mental health data is ensuring that data is discoverable by providing clear information on access protocols and data descriptions. The aim is to facilitate the discoverability of data and maximise its uptake, as well as minimise the investment of both time and costs spent by study teams, participants, and institutions.

To ensure that data is relevant and accessible, we are focusing on the following three infrastructure developments:

The Catalogue of Mental Health Measures, led by Louise Arseneault.

The Catalogue of Mental Health Measures is an online, publicly available, and searchable platform of existing measures of mental health and wellbeing in UK cohort and longitudinal studies. It supports DATAMIND by promoting the discoverability of their datasets that are FAIR.

To facilitate the use of UK data and promote mental health research, the Catalogue features information about these UK studies, their measures of mental health and wellbeing, and other related measures such as Covid-19 and administrative data. By providing these details, the Catalogue serves as a resource for researchers who may be:

  • Searching for datasets that include mental health and wellbeing measures,
  • Planning harmonisation studies, and/or
  • Planning further data collection.

The resource is also intended for users who may be less familiar with mental health or from other disciplines, such as demographers, economists, urbanist, and linguists. To support all users, the Catalogue also provides information about data access as well as additional training and support for conducting longitudinal mental health research.

The UK Longitudinal Linkage Collaboration (LLC) of the Longitudinal Health and Wealth Covid-19 National Core Study, led by Andy Boyd Building on both the Bristol MRC Pathfinder and the UK LLC infrastructural component, UK LLC provides a national, open, readily discoverable, supported access integrated data resource of longitudinal population studies (LPS) enhanced by linkage to health and social records.

Enhancing and enabling MH research with genetics, led by James Walters.

To improve the accessibility and usability of data for genetic research, the goal is to work with collaborators from the UK psychiatric genetics community to make discoverable and accessible the linked genetic and clinical datasets held in Scotland and wider UK. More specifically, the infrastructure will enhance the discoverability and ease of use of genetic research data across the UK by supplementing the Catalogue of Mental Health Measures and the HDR UK Innovation Gateway with details of the genetic data available in UK-based cohorts and studies.

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