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Proposing a Blockchain-Based Open Data Platform and Its Decentralized Oracle

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Advances in Intelligent Networking and Collaborative Systems (INCoS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1035))

Abstract

Bitcoin has been attracted attention to issue digital currency and also to manage transactions in a decentralized and trustless way without assuming any reliable third-party organization. To enhance the potential of Bitcoin, blockchain technologies have been studied to find more applications to smart contract, identification, and certificate which is valid even after the original issuer disappears. On the other hand, mobile crowdsensing is known as a method to collectively gather and share local data with the help of many and unspecified participants having their portable devices with sensors like smartphones to extract useful information from them. Expectation-Maximization (EM) algorithm is considered to estimate true information from task results from many independent workers and to evaluate workers’ scores. By the combination of blockchain and mobile crowdsensing technologies, a open data platform to save true information into the blockchain and issue currency to workers based on their reliability scores. In this research, we explain how to create this open data platform to generate Big and Long-time Open Data (BaLOD) to certify events that occurred in reality and everyone can validate the events.

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Acknowledgement

This work was partially supported by the Japan Society for the Promotion of Science (JSPS) through KAKENHI (Grants-in-Aid for Scientific Research) Grant Numbers 17K00141 and 17H01742. The author thanks Dr. Shigeichiro Yamasaki and Dr. Hitoshi Okada for useful discussion and comments on the proposal.

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Correspondence to Akihiro Fujihara .

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Fujihara, A. (2020). Proposing a Blockchain-Based Open Data Platform and Its Decentralized Oracle. In: Barolli, L., Nishino, H., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2019. Advances in Intelligent Systems and Computing, vol 1035. Springer, Cham. https://doi.org/10.1007/978-3-030-29035-1_19

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