We study foundational and applied issues of reasoning that are motivated by the exploitation of information in a context of data-variety.
Our goal is to bring together techniques from knowledge representation, automated reasoning, database theory, and data management, to devise novel theoretical and practical tools.
Our main research axes are the following.
- Foundations of rule languages
- Fine-grained complexity of query answering
- Algorithms and optimizations for query answering
- Architectures for heterogeneous data integration
- Quality of knowledge-based data integration
In parallel with basic research, we are also involved in the development of software tools for reasoning on heterogenous and federated data.