Project description
Unlocking the potential of causal graphs in data analysis
Understanding cause-and-effect relationships is essential in many fields from healthcare to economics. Causal graphs, known as directed acyclic graphs, are powerful tools for representing these relationships. However, they are currently created manually by experts and lack proper systems for validation, storage and updates, which makes it difficult to effectively manage and analyse them. The ERC-funded GOY project aims to combine causal inference with graph database technology. The goal is to create a specialised database for causal graphs, where these graphs can be stored, validated and analysed. The system will allow experts to better manage and query causal data, opening up the possibility to advance understanding of complex cause-and-effect relationships in a structured way.
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.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-ADG
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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.
69622 Villeurbanne Cedex
France
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