Title: Towards a scientific blockchain framework for reproducible data analysis,
Abstract: Publishing reproducible analyses is a long-standing and widespread challenge
for the scientific community, funding bodies and publishers. Although a
definitive solution is still elusive, the problem is recognized to affect all
disciplines and lead to a critical system inefficiency. Here, we propose a
blockchain-based approach to enhance scientific reproducibility, with a focus
on life science studies and precision medicine. While the interest of encoding
permanently into an immutable ledger all the study key information-including
endpoints, data and metadata, protocols, analytical methods and all
findings-has been already highlighted, here we apply the blockchain approach to
solve the issue of rewarding time and expertise of scientists that commit to
verify reproducibility. Our mechanism builds a trustless ecosystem of
researchers, funding bodies and publishers cooperating to guarantee digital and
permanent access to information and reproducible results. As a natural
byproduct, a procedure to quantify scientists' and institutions' reputation for
ranking purposes is obtained.