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September 10, 2025Proceedings of the VLDB Endowment1 citations

Integrating Causal Analysis into Graph Databases Using Directed Acyclic Graphs

What If: Causal Analysis with Graph Databases

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Authors

APAmedeo PacheraMPMattia PalmiottoABAngela Bonifati

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Overview

This approach demonstrates scalable causal queries in graph databases, suggesting a new framework for causality-aware data management.

Key Points

  • Causal analysis can be effectively integrated with graph databases, improving decision-making processes.
  • The approach combines directed acyclic graphs, hypernodes, and causal reasoning to enhance data extraction methods.
  • By validating a proof-of-concept implementation, the study shows scalable handling of causal queries over DAGs.
  • This integration may enable new, personalized data-driven strategies across various scientific fields.

Cite This Study

Pachera et al. (2025) studied this question.

synapsesocial.com/papers/68c189d29b7b07f3a0613312https://doi.org/10.14778/3749646.3749671
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1What Is a Causal Graph?2024 · 1 citations
  2. 2DAGs: Directed Acyclic Graphs for Drawing Assumptions and Guiding Causal Inference2026
  3. 3Designing Causal Diagrams for Theoretical Reasoning and Measurement. Visualisations from Life-Course Research2026
  4. 4Invited commentary: where do the causal DAGS come from?2024 · 8 citations
  5. 5Causal clarity: directed acyclic graphs in medical research2026