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Enabling Blockchain-Agnostic Process Mining: An Approach for Artifact-Centric Event Log Extraction
Rawya Mars, Saoussen Cheikhrouhou, Leyla Moctar M’baba, Mohamed Sellami, Slim Kallel

Enabling Blockchain-Agnostic Process Mining: An Approach for Artifact-Centric Event Log Extraction

Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

In the context of blockchain-based business processes, process mining benefits from the trustworthiness of data to provide valuable insights into user behavior, performance, and security for blockchain applications. However, raw blockchain data are inadequate for process mining techniques. This issue has been previously explored in literature for artifact-centric processes, ignoring the heterogeneity of blockchain platforms. To address this issue, we present a blockchain-agnostic approach for extracting Artifact-Centric Event Logs (ACEL) from multiple blockchains. This approach uses a configurable mapping to interpret on-chain transactions as artifact events and relationships, supporting various platforms (Ethereum, Hyperledger Fabric, etc.). Our approach is validated using the kitty use case deployed on both Ethereum and Hyperledger Fabric, demonstrating its effectiveness and the feasibility in supporting cross-platform process analysis.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Enabling Blockchain-Agnostic Process Mining: An Approach for Artifact-Centric Event Log Extraction
Author / Organization Rawya Mars, Saoussen Cheikhrouhou, Leyla Moctar M’baba, Mohamed Sellami, Slim Kallel
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2026
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-202014
Original Source Link Visit Source Page on hal.science »