Many applications, ranging from cryptocurrencies to food supply chain management, drive consumer and industrial adoption of Blockchain technologies. As these applications proliferate, so does 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 the information sciences. In this invited paper, we provide a brief overview of Blockchain Data Analytics, focusing both on the emerging research challenges and on the novel applications – from Bitcoin price prediction to e-crime detection.

Public blockchains can be broadly categorized as unspent

transaction output (UTXO) based (e.g., Bitcoin, Litecoin),

In account based blockchains, an address can spend a

fraction of its coins and keep the remaining balance. In these

blockchains, a transaction has exactly one input and one output

address. Although address creation is free, mostly a single

address is used to receive and send coins multiple times.

Created in 2015, Ethereum [10] is currently the most valu-

able account based blockchain. Similar to Bitcoin, Ethereum

has a currency: Ether. However, the Ethereum project’s main

goal is to store data and software code on a Blockchain. The

code (a smart contract) is written in the proprietary coding

language Solidity, which is compiled to bytecode and executed

on the Ethereum Virtual Machine. Smart Contracts are self-

executing Turing complete contracts which contain code and

agreements. An analogy is the MYSQL snippets stored on a

database. However, Smart Contracts also ensure unstoppable,

deterministic code execution that can be verified publicly