BlockFlow:对科学来源数据的信任

Raiane Coelho, Regina M. M. Braga, J. M. David, Fernanda Campos, Victor Ströele
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引用次数: 6

摘要

在科学合作中,数据共享、思想交流和成果交流对于促进知识和加速科学发展至关重要。在这种情况下,信任和可重复性是极其重要的。虽然在科学工作流程中,来源是可重复性的基础,但在协作环境中,有必要确保这些来源数据的完整性和可信度。已经出现并可以帮助解决这些问题的技术之一是区块链。基于区块链的协作科学实验溯源系统可以为科学实验带来一个值得信赖的环境。在这方面,本文提出了一个名为BlockFlow的体系结构规范,它为分布式来源数据提供信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BlockFlow: Trust in Scientific Provenance Data
In scientific collaboration, the data sharing, the exchange of ideas and results is crucial to promote knowledge and accelerate the development of science. Trust is extremely important in this context as well as reproducibility. Although in scientific workflow the provenance has been the basis for reproducibility, in collaborative environments it is necessary to ensure integrity and trustworthiness of this provenance data. One of the technologies that have emerged and can help to address these issues is blockchain. A blockchain-based provenance system for collaborative scientific experiments could lead to a trustworthy environment for scientific experimentation. In this vein, this paper presents the specification of an architecture, named BlockFlow, that provides trust for distributed provenance data.
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