4 research outputs found
Relaxing and Restraining Queries for OBDA
In ontology-based data access (OBDA), ontologies have been successfully
employed for querying possibly unstructured and incomplete data. In this paper,
we advocate using ontologies not only to formulate queries and compute their
answers, but also for modifying queries by relaxing or restraining them, so
that they can retrieve either more or less answers over a given dataset.
Towards this goal, we first illustrate that some domain knowledge that could be
naturally leveraged in OBDA can be expressed using complex role inclusions
(CRI). Queries over ontologies with CRI are not first-order (FO) rewritable in
general. We propose an extension of DL-Lite with CRI, and show that conjunctive
queries over ontologies in this extension are FO rewritable. Our main
contribution is a set of rules to relax and restrain conjunctive queries (CQs).
Firstly, we define rules that use the ontology to produce CQs that are
relaxations/restrictions over any dataset. Secondly, we introduce a set of
data-driven rules, that leverage patterns in the current dataset, to obtain
more fine-grained relaxations and restrictions
Relaxing and restraining queries for OBDA (extended abstract)
We investigate query reformulation rules in OBDA to obtain either more or less answers. We extend DL-Lite with complex role inclusions and define rules that produce query relaxations/restrictions over any dataset.We also introduce a set of data-driven rules to get more fine-grained reformulations