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Unifying Graph Databases and Causal Models

Objective

Graphs are expressive data structures representing more effectively relationships in data and enabling complex data-intensive tasks. Graphs are also a widely adopted paradigm in causal inference focusing on causal directed acyclic graphs. Causal DAGs (Directed Acyclic Graphs) are manually curated by domain experts, but they are not validated, stored, integrated and versioned as data artifacts in a graph data system. In the GOY (pronounced GO Why) project, I focus on a radical shift towards causality-driven graph databases, addressing the development of solid theoretical foundations and a set of adequate tools underpinning causal graph operations. To date, these two paradigms, namely causality and graph data management, are developed by entirely separate communities with different motivations: one is interested in causal analysis and inference, realized by means of ad-hoc programs and scripts on empirically validated causal graphs, while the other is interested in collecting, validating, integrating and querying graph data by means of declarative languages. These two areas are investigated in isolation although combining them creates exciting possibilities. The present proposal aims at investigating these possibilities and focuses on laying the theoretical foundations of causality-driven graph data management, a completely novel approach to data management guided by the theory of causation. Causal graphs, either provided by domain experts or extracted from the underlying observational data, are further semantically enriched, disambiguated, reconciled and used in the downstream processes of the graph database for queries, updates and analysis. Following these goals, I investigate (1) a formal causal property graph model and the extension of graph query languages to support causal graph query operators and (2) the integration, consistency and (3) versioning of causal property graphs to assist domain experts in the execution of advanced causal processes.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-ADG

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Host institution

UNIVERSITE LYON 1 CLAUDE BERNARD
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 315 565,00
Address
BOULEVARD DU 11 NOVEMBRE 1918 NUM43
69622 Villeurbanne Cedex
France

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Region
Auvergne-Rhône-Alpes Rhône-Alpes Rhône
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Beneficiaries (1)

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