A BioCommons infrastructure for UK life science researchers
BioFAIR is a UKRI funded federated digital research infrastructure (£34million over 5 years), due to launch this summer.
BioFAIR will deliver a step change in ‘Findable, Accessible, Interoperable and Re-usable’ (FAIR) research data management, providing end-to-end FAIR research data management & analysis capabilities along with the necessary support and training for UK researchers working in the life sciences.
Working with national Digital Research Infrastructures and related national and international data hubs, BioFAIR aims to improve productivity for researchers, raise the quality of data sets and analysis pipelines, and stimulate the uptake of standards and best practices in research data management.
Meet us at our 2024 Roadshow
Supporting the UK’s life science community with world class digital infrastructure for data driven bioscience.
Method Commons and Services
A shared Method Commons will enable institutes and research teams to access trusted and robust analysis platforms, workflows and tools, using their own and reference datasets, and contribute their own computational methods. Nationally hosted analytical resources will enhance the digital infrastructure available to UK life scientists, supporting reproducible data analytics for data driven bioscience.
Data Commons and Services
A shared Data Commons will enable researchers to prepare, analyse, share and manage FAIR research data across the data’s whole life cycle, from its collection to deposition and retention. A national DataHub will catalogue a distributed “data lake” of researcher governed data, and support will be given for: data collection, data analysis and the submission of data into community public archives.
People Commons and Services
A pooled community of professional data stewards and Research Software Engineers will support researchers, bioinformaticians, institutional /project developers and data stewards with their Data and Software Management Planning, data quality and data analytics, AI-readiness and open science practice.