Integrating Blockchain for Data Sharing and Collaboration Support in Scientific Ecosystem Platform

Coelho, Raiane
Braga, Regina
David, José Maria
Dantas, Mário
Stroele, Victor
Campos, Fernanda
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Nowadays, scientific experiments are conducted in a collaborative way. In collaborative scientific experiments, aspects such interoperability, privacy and trust in shared data should be considered to allow the reproducibility of the results. A critical aspect associated with a scientific process is its provenance information, which can be defined as the origin or lineage of the data that helps to understand the results of the scientific experiment. Other concern when conducting collaborative experiments, is the confidentiality, considering that only properly authorized personnel can share or view results. In this paper, we propose BlockFlow, a blockchain-based architecture with the aim of bringing reliability to the collaborative research, considering the capture, storage and analysis of provenance data related to a scientific ecosystem platform (E-SECO).
Collaboration for Data Science, blockchain, e-science., provenance, scientific collaboration
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