A Process-Aware Framework to Support Process Mining from Blockchain Applications

Blockchain technology offers the ability of a trusted peer-to-peer exchange and automated execution of business contracts through smart contracts. This offer needs to be examined on the operational level to gain objective insights of workflow embedded within smart contracts. Several studies have been conducted to demonstrate the application of Process Mining (PM) techniques to blockchain application event data. However, research on process awareness of blockchain applications seems to be lacking. This study proposes a framework to support mining business processes from blockchain applications. The framework consists of two modules: Process Awareness Recognizer (PAR) and Event Log Generator (ELG). PAR is a rule-based classifier to assess the process awareness of a given blockchain application. ELG is an automated batch processing model consisting of three methods: 1) Extractor: an algorithm for event data retrieval from blockchain networks, 2) Decoder: a data decoding algorithm to transform the extracted event data to a human-readable format, and 3) Formatter: an algorithm to produce event log files in a format that is compatible with PM tools. The framework supports Ethereum-compatible applications. It was validated by implementing a proof-of-concept application with an input set of 201 real-world applications. The results approved the feasibility and applicability of the framework. This study aims to accelerate PM practices on blockchain event data by providing a methodology to assist in selecting, retrieving, and transforming event data of blockchain applications.