Background

Within clinical research institutions across the UK currently, only a small proportion of generated data is effectively being captured and safely stored long term; research efforts are fragmented and the challenges of multicentre collaboration are not yet overcome. A shared national initiative of accessible and secure bioinformatics solutions tailored to the needs of junior and senior clinical academics has the potential to address this unmet need and cardiovascular research provides a clear example.

Cardiovascular disease is a leading public health problem and a number one killer in the UK accounting for 40% of all national deaths and costing the UK economy £29 billion a year in healthcare expenditure and lost productivity. The UK spends more of its healthcare budget on cardiovascular disease and research than any other EU economy.1 ,2 Over the past 20 years, there has been an explosive growth in cardiovascular investigations, imaging and therapies across the National Health Service (NHS) underpinning clinical care but also the >£117 million annual research investment3 that creates expensive clinical cohorts.4 There is a pressing need to merge and curate (for at least 10 years) not only the large well-organised big cardiac science data sets5–8 but also the richly diverse and heterogeneous smaller cohort data sets produced by small groups and individual cardiologists, the so-called long-tail data9 (figures 1 and 2)—the large proportion of scientific data that falls into the long tail of the distribution curve,11 a product of the numerous small independent research efforts yielding a rich variety of specialty cardiac research data sets. The extreme right portion of the long tail includes unpublished dark data: siloed databases locked up in applications, null findings, laboratory notes, log archives, untagged image files, animal care records, etc.9 Dark data in cardiology can be illuminating but it is …