Blockchain technology has fostered the advent of decentralised applications relying on smart contracts to encode business logic. In this context, it is particularly relevant to analyse data produced by smart contracts that can reveal valuable insights about applications and their execution. In recent years, process mining and, in particular, object-centric techniques have been considered to capture the complexity of blockchain applications and reveal their different perspectives. However, their adoption raises novel challenges related to the object-centric representation of blockchain data. To address this problem, in this work, we propose a mapping methodology guiding users to correlate blockchain data to an object-centric log without requiring advanced technical skills. The proposed methodology generates logs that are compatible with current tools and techniques, enabling in-depth analysis. The methodology was implemented as a web-based tool and its applicability was evaluated on three real-world applications together with a performance and usability assessment.
A Mapping Methodology Enabling Object-Centric Process Mining on Blockchain Applications
Corradini, Flavio;Marcelletti, Alessandro;Morichetta, Andrea;Re, Barbara;Verducci, Lorenzo
2025-01-01
Abstract
Blockchain technology has fostered the advent of decentralised applications relying on smart contracts to encode business logic. In this context, it is particularly relevant to analyse data produced by smart contracts that can reveal valuable insights about applications and their execution. In recent years, process mining and, in particular, object-centric techniques have been considered to capture the complexity of blockchain applications and reveal their different perspectives. However, their adoption raises novel challenges related to the object-centric representation of blockchain data. To address this problem, in this work, we propose a mapping methodology guiding users to correlate blockchain data to an object-centric log without requiring advanced technical skills. The proposed methodology generates logs that are compatible with current tools and techniques, enabling in-depth analysis. The methodology was implemented as a web-based tool and its applicability was evaluated on three real-world applications together with a performance and usability assessment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
