Expand — Expanding the Reach of Ontology-Based Data Access: EXpressivity, exPlanation and Algorithms

ANR research project

Expanding the reach of ontology-based data access

EXPAND brings together a large part of the French community working on ontology-based data access to make it more expressive, more explainable and efficient in practice.

6

research sites across France

18

researchers from CNRS, Inria, INRAE and universities

3

research axes: expressivity, explanation and algorithms

The project

Why ontology-based data access?

In a data-driven society where decision-making depends on advanced data analysis, valuable information is often scattered across multiple sources. Moreover, raw data is rarely available in a directly usable form: various transformation operations are required, such as reformatting, changing description vocabulary, normalizing units or making inferences to complete information. This raises the challenge of providing an integrated view of multiple data sources to allow for intuitive and efficient querying by a stakeholder.

The EXPAND project aims to facilitate data access and integration through the Ontology-Based Data Access (OBDA) technology. In a nutshell, OBDA provides a principled way of integrating multiple data sources by adding an ontological layer on top of them.

This paradigm has several benefits. First, OBDA allows one to unify and enrich data sources by establishing explicit relationships between raw data and ontology terms. Second, OBDA enables users to query diverse data repositories using a high-level vocabulary provided by the ontology, disregarding the actual data formats, while leveraging logical inference to retrieve richer answers than classical evaluation techniques. Third, by providing a unified view of information across multiple datasets and inferring missing information, OBDA allows for querying even incomplete databases.

Research

Three research axes

EXPAND aims at enriching the current OBDA framework along three axes.

Expressivity

Support various query classes that are well studied and understood in database settings, such as navigational queries, aggregation queries and some very restricted forms of negation.

Explanation

Provide enough context to help users accept or discard the answers returned by the system, in particular by leveraging techniques from neighbouring fields (databases, knowledge compilation…). We will investigate how to provide explanations and how to explore large answer sets.

Algorithms

Develop optimization techniques to make an expressive OBDA framework applicable in practice.

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EXPAND is funded by the French National Research Agency (ANR) under grant ANR-25-CE23-1215. Coordinator: Michaël Thomazo (Inria, DI ENS).