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.
Expand aims at enriching the current OBDA framework by:
- support various query classes well studied and understood in database settings, such as navigational queries, aggregation queries and some very restricted forms of negation;
- provide enough context to a user to help
them to accept or discard answers provided 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 - the development of optimization techniques to make an expressive OBDA framework applicable in practice.