The FAIRVASC Challenge and Opportunity
Rigorous clinical research relies upon analysis of a sufficiently large number of observations (patients, samples, experimental measurements, etc.) to allow reliable statistical inference. The low prevalence of rare diseases means that patient numbers are small in any given country. The resulting small cohort sizes represent a major barrier to such research. While national and local registries are emerging for many rare diseases, federating them so that they can be used as a single pool of data has three key challenges – finding the registry with the data needed (registry discovery), overcoming variations in the data held, how it is structured and the terminologies used (data normalisation) and legal, ethical and regulatory constraints on accessing and using the data (data governance). The FAIRVASC workplan consists of eight work-packages (WPs).
AAV: a model autoimmune rare disease, with applicability in other rare disease arenas: The challenge of fragmented and heterogeneous registries applies across many rare diseases in Europe and beyond. In FAIRVASC, we focus on the rare disease ANCA-associated vasculitis (AAV, ORPHA:156152 ) as a demonstrator of how to use RDF and semantic technologies to normalise and access registry data across borders.