Abstract
Blockchain is a foundational technology that allows application paradigms to shift from trusting humans to trusting machines and from centralized to decentralized control. Along with its explosive growth, blockchain data analysis is getting increasingly important for both scientific research and commercial applications. The current blockchain analysis systems and frameworks have limitations and weaknesses; they have excessively focused on Bitcoin and a small set of features. This paper presents a framework for blockchain data analysis. The framework is general and can be applied to a wide range of data analyses. Our main contributions are as follows: (i) we formulate the requirements of the framework; (ii) we present the detailed design of the framework with multiple components to collect, extract, enrich, store, and do further processing with blockchain data; (iii) we implement the framework and evaluate its performance in a specific use case that analyzes token-transferring transactions. We also discuss the potential of the framework for a number of blockchain data analyses.
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Luu, A., Trinh, TD., Nguyen, VT. (2023). A General Framework for Blockchain Data Analysis. In: Nurcan, S., Opdahl, A.L., Mouratidis, H., Tsohou, A. (eds) Research Challenges in Information Science: Information Science and the Connected World. RCIS 2023. Lecture Notes in Business Information Processing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-031-33080-3_8
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