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A Systematic review of blockchain technology for government information sharing

A Systematic review of blockchain technology for government information sharing

Zhang, Lu, Ma, Jiarong, An, Yuting, Zhang, Tianshuo, Ma, Jixin, Feng, Chen and Xiaoyi, Zhou (2022) A Systematic review of blockchain technology for government information sharing. Computers, Materials & Continua, 74 (1):49856. pp. 1161-1181. ISSN 1546-2218 (Print), 1546-2226 (Online) (doi:

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Government information sharing (GIS) refers to that act of required or provided for duty government information, commercial information and public welfare information, and it is a basic issue of government services. However, the existing GIS has low transparency and is lack of flexibility between different departments. Aiming at such problems, this paper takes blockchain as a solution, and systematically summarizes the development of digital GIS, the advantages and challenges of blockchain and its theoretical research and practical applications. Specifically, it reviews e-government interactive structure, big data and other solutions, analyses their imperfections, and puts forward blockchain-based solutions. The blockchain improves government service efficiency and data security, meanwhile it faces challenges in throughput and supervision. In order to meet these challenges, researchers propose solutions based on three data exchange scenarios: government-to-government, government-to-enterprise and government-to-individual. In addition to researches, blockchain-based GIS is put into use. The electronic licensing project of Nanjing (China) government is taken as an example to illustrate that blockchain has the ability to openly and securely verify, track, and exchange data, so as to improve management ability and public service level of government agencies.

Item Type: Article
Uncontrolled Keywords: blockchain; information sharing; government; cross-chain
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
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Last Modified: 27 Jun 2023 10:49

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