Proceedings of the VLDB Endowment (PVLDB), 2025
We propose graph-based techniques for interactive causal analysis over property graph databases, enabling efficient exploration of causal relationships in complex, interconnected data.
Recommended citation: A. Pachera, A. Bonifati, A. Mauri. WhatIf: Causal Analysis with Graph Databases. Proceedings of the VLDB Endowment (PVLDB), 2025. DOI: 10.14778/3749646.3749671
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Proceedings of the ACM on Management of Data (PACMMOD), SIGMOD 2025
An interactive, user-centric approach to repairing property graphs under denial constraints. It introduces a query-based inconsistency detection mechanism, a dependency graph for tracking violations, and an assignment algorithm enabling multi-user repairs via independent sets — outperforming interactive and non-interactive baselines by 30% on average, validated with a user study.
Recommended citation: A. Pachera, A. Bonifati, A. Mauri. User-Centric Property Graph Repairs. Proceedings of the ACM on Management of Data (PACMMOD), 2025. DOI: 10.1145/3709735
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ACM Transactions on Computing Education (ToCE), 2025
An empirical study of the common errors students make when formulating graph queries, providing insights for the design of graph database education tools.
Recommended citation: Understanding Students' Errors in Graph Query Formulation. ACM Transactions on Computing Education (ToCE), 2025. DOI: 10.1145/3743687
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ACM SIGMOD 2027 (To Appear)
A Graph Neural Network–based framework for interactive property graph repair that combines representation learning, optimization, and human expertise under budget constraints. The model learns to estimate repair difficulty and decides, within a fixed budget, which repairs to automate and which to route to human experts.
Recommended citation: A. Pachera, A. Bonifati, A. Mauri. Budgeted Interactive Property Graph Repair with Graph Neural Networks. ACM SIGMOD 2027 (to appear).
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IEEE 40th International Conference on Data Engineering Workshops (ICDEW), 2024
An early vision and problem formulation for user-centric, interactive repair of inconsistent graph data, combining automatic inference with human expertise.
Recommended citation: A. Pachera, A. Bonifati and A. Mauri, "Towards User-Centric Graph Repairs," in 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW), Utrecht, Netherlands, 2024, pp. 375-376, doi: 10.1109/ICDEW61823.2024.00057.
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PACMMOD — Demonstration, SIGMOD 2025
An interactive tool for human-in-the-loop repair of property graphs. Users upload datasets, define constraints in Cypher, and collaboratively correct inconsistencies; administrators monitor real-time statistics and oversee the repair process through an interactive dashboard.
Recommended citation: A. Pachera, A. Bonifati, A. Mauri. Grafixer: Enabling User-Centric Repairs for Property Graphs. PACMMOD Demonstration, SIGMOD 2025. DOI: 10.1145/3722212.3725105
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