Visible to the public Blockchain Based Provenance Sharing of Scientific Workflows

TitleBlockchain Based Provenance Sharing of Scientific Workflows
Publication TypeConference Paper
Year of Publication2018
AuthorsChen, W., Liang, X., Li, J., Qin, H., Mu, Y., Wang, J.
Conference Name2018 IEEE International Conference on Big Data (Big Data)
Keywordsblockchain, blockchain based provenance sharing, centralized provenance sharing architectures, composability, Computer architecture, cryptocurrencies, data providers, Distributed databases, distributed research cooperation, distributed scientists, experiment reproducibility, experiment reproducibility verification, experiments backtracking, Human Behavior, metadata, Metrics, Provenance, pubcrawl, reliability, Resiliency, scientific information systems, scientific workflow, scientific workflow provenance, Task Analysis, Tools, transaction verification
AbstractIn a research community, the provenance sharing of scientific workflows can enhance distributed research cooperation, experiment reproducibility verification and experiment repeatedly doing. Considering that scientists in such a community are often in a loose relation and distributed geographically, traditional centralized provenance sharing architectures have shown their disadvantages in poor trustworthiness, reliabilities and efficiency. Additionally, they are also difficult to protect the rights and interests of data providers. All these have been largely hindering the willings of distributed scientists to share their workflow provenance. Considering the big advantages of blockchain in decentralization, trustworthiness and high reliability, an approach to sharing scientific workflow provenance based on blockchain in a research community is proposed. To make the approach more practical, provenance is handled on-chain and original data is delivered off-chain. A kind of block structure to support efficient provenance storing and retrieving is designed, and an algorithm for scientists to search workflow segments from provenance as well as an algorithm for experiments backtracking are provided to enhance the experiment result sharing, save computing resource and time cost by avoiding repeated experiments as far as possible. Analyses show that the approach is efficient and effective.
Citation Keychen_blockchain_2018