English

Towards a scientific blockchain framework for reproducible data analysis

Computers and Society 2017-07-24 v1 Cryptography and Security Quantitative Methods

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.

Keywords

Cite

@article{arxiv.1707.06552,
  title  = {Towards a scientific blockchain framework for reproducible data analysis},
  author = {C. Furlanello and M. De Domenico and G. Jurman and N. Bussola},
  journal= {arXiv preprint arXiv:1707.06552},
  year   = {2017}
}

Comments

8 pages, 1 figure

R2 v1 2026-06-22T20:53:02.300Z