Alloy-Driven Verification of Object-Centric Event Data: From Temporal Logic to Knowledge Graphs

Fuente: arXiv
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Main Authors: Latif, Saba, Latif, Huma, Rehman, Touseef Ur, Rahman, Muhammad Rameez Ur
Format: Preprint
Published: 2025
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author Latif, Saba
Latif, Huma
Rehman, Touseef Ur
Rahman, Muhammad Rameez Ur
author_facet Latif, Saba
Latif, Huma
Rehman, Touseef Ur
Rahman, Muhammad Rameez Ur
contents Object-centric process mining addresses the limitations of traditional approaches, which often involve the lossy flattening of event data and obscure vital relationships among interacting objects. This paper presents a novel formal framework for Object-centric Event Data (OCED) that ensures the correctness of the meta-model and preserves native object-centric semantics prior to the system implementation. Our approach effectively leverages Alloy for precisely specifying temporal properties and structural relationships between objects and events. This guarantees thorough verification against predefined OCED constraints such as cross-object cardinality bounds and time-aware consistency rules, hence preventing common data integrity issues. We demonstrate the effectiveness of the proposed framework in discovering and validating implicit object dependencies in event logs, particularly when importing data into graph databases like Neo4j. This demonstrates how formal verification can avoid pitfalls that lead to data invisibility and improve knowledge graph creation, enrichment, and querying. To bridge theory and practice, our verified \emph{FOCED} is made accessible through automatically generated Python bindings, empowering industrial users without formal methods expertise. The code is available on GitHub \footnote{https://github.com/sabalati/FOCED}
format Preprint
id arxiv_https___arxiv_org_abs_2511_07263
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Alloy-Driven Verification of Object-Centric Event Data: From Temporal Logic to Knowledge Graphs
Latif, Saba
Latif, Huma
Rehman, Touseef Ur
Rahman, Muhammad Rameez Ur
Formal Languages and Automata Theory
Object-centric process mining addresses the limitations of traditional approaches, which often involve the lossy flattening of event data and obscure vital relationships among interacting objects. This paper presents a novel formal framework for Object-centric Event Data (OCED) that ensures the correctness of the meta-model and preserves native object-centric semantics prior to the system implementation. Our approach effectively leverages Alloy for precisely specifying temporal properties and structural relationships between objects and events. This guarantees thorough verification against predefined OCED constraints such as cross-object cardinality bounds and time-aware consistency rules, hence preventing common data integrity issues. We demonstrate the effectiveness of the proposed framework in discovering and validating implicit object dependencies in event logs, particularly when importing data into graph databases like Neo4j. This demonstrates how formal verification can avoid pitfalls that lead to data invisibility and improve knowledge graph creation, enrichment, and querying. To bridge theory and practice, our verified \emph{FOCED} is made accessible through automatically generated Python bindings, empowering industrial users without formal methods expertise. The code is available on GitHub \footnote{https://github.com/sabalati/FOCED}
title Alloy-Driven Verification of Object-Centric Event Data: From Temporal Logic to Knowledge Graphs
topic Formal Languages and Automata Theory
url https://arxiv.org/abs/2511.07263