Abstract
For many years, the role played by domain knowledge in all stages of knowledge discovery has been recognized by authors in the field. However, the real-world semantics em- bedded in data is often still not fully considered in traditional data mining methods and techniques. In this paper, we de- fend that the quality of data mining results is directly re- lated to the extent that they reflect important properties of real-world entities represented therein. Analysing and characterising the nature of these entities is the very busi- ness of the area of Formal Ontology. We briefly elaborate on two particular types of artefacts produced by this area:Foundational Ontologies and Ontology-Driven Conceptual Mod- eling languages grounded on them. We then elaborate on the benefits they can bring to several activities in a Data Mining process.