Discovering Functional Dependencies from Ontologies

Discovering functional dependencies is a fundamental step in the design of relational databases and in most system reengineering processes. Typically, this task has been performed over relational databases, at the logical or physical level. Those works addressing it at the logical level, often make some unrealistic assumptions (such as completeness of the data structures or similar names for semantically related attributes), while those addressing it at the physical level propose solutions that are computationally expensive, whose performance deteriorates with a large number of attributes or instances, and which cannot tolerate erroneous data. To overcome these limitations, while also better capturing data dependencies, we propose to rely instead on a conceptual representation of the domain of interest, specified in ER and formalized through a domain ontology expressed in the DL-Lite Description Logic. We propose an algorithm to discover functional dependencies from the domain ontology that exploits the inference capabilities of DL-Lite, thus fully taking into account the semantics of the domain. We also provide an evaluation of our approach in a real-world scenario.