Data Science on Blockchains

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Abstract

Blockchain technology garners an ever-increasing interest of researchers in various domains that benefit from scalable cooperation among trust-less parties. As blockchains and their applications proliferate, so do the complexity and volume of data stored by Blockchains. Analyzing this data has emerged as an important research topic, already leading to methodological advancements in information sciences. In this tutorial, we offer a holistic view of applied Data Science on Blockchains. Starting with the core components of Blockchain, we will detail the state of art in Blockchain data analytics for graph, security, and finance domains. Our examples will answer questions, such as, how to parse, extract and clean the data stored in blockchains?, how to store and query Blockchain data? and what features we could compute from blockchains? We will share tutorial notes, collected meta-information, and further reading pointers on our tutorial website at https://blockchaintutorial.github.io/

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APA

Akcora, C. G., Kantarcioglu, M., & Gel, Y. R. (2021). Data Science on Blockchains. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 4025–4026). Association for Computing Machinery. https://doi.org/10.1145/3447548.3470800

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