What standards are we adopting?
These standards have been selected based on relevance and prevalence to the research data infrastruture domain. Included below is a brief description of what these standards are and why they have been adopted.
Five Safes
- A set of principles to describe how decisions about granting access to data should be made. Covering Safe People, Data, Project, Outputs, Settings it is a set of interlocking principles
- HDR UK have been a major proponent of the adoption of these principles across the UK health data eco-system. It has become the default mechanism across most domains and is the governance framework in which access decisions are made for HDR UK and DARE UK.
Findable Accessible Interoperable Reusable (FAIR)
- A set of principles that describes guidelines to improve transparency, reproducibility, and reusability of data, metadata and infrastructure.
- Defines what information should be provided about the data in order to help that reuse, called metadata (data that describes data)
- Significant adoption with the open life sciences community
- Becoming the default requirement in all research programmes to ensure data is FAIR
For both HDR UK and DARE UK, FAIR is a key principle and both organisations are promoting FAIR as an essential requirement in the eco-system. They are funding programmes to understand what metadata is appropriate and possible to collect across secure data environments.
Global Alliance for Genomics and Health (GA4GH)
- A joint academic and industry programme
- Health Data Research UK and GA4GH have a strategic partnership
- Pre-competitive work to enable global analysis of genomic data
- Produced international standards
HDR UK and DARE UK have funded programmes to understand if the standards developed in GA4GH can be used in wider data environments, and especially within secure data environments for sensitive data.
The Federated Analytics programme in HDR UK and the TREvolution programme in DARE UK have MVPs to demonstrate the utility of these standards beyond health.
Task Execution Service (TES)
- Provides a standard mechanism for orchestrating complex analyses across different compute environments
Observational Medical Outcomes Partnership (OMOP)
- A standard that describes how health data should be grouped together in a set of common tables (a common data model)
- Created and maintained by Observational Health Data Sciences and Informatics (OHDSI)
- Adopted by NHS England Secure Data Environment programme
- Used as a global standard for real world data studies
HDR UK have supercharged the UK efforts in the adoption of OMOP, by funding the conversion of data to OMOP, helping to establish OHDSI UK, and by the establishment of the real-world evidence framework.
The Federated Analytics programme in HDR UK have open-source tools in production that support the conversion of data to OMOP and the discovery of OMOP datasets globally. These are being developed further in DARE UK to demonstrate how they can be deployed across multiple secure data environments.