Schema matching is a fundamental issue in many database applications, such as query mediation, database integration, catalog matching and data warehousing. In this thesis, we first address hot to match catalogue schemas. A catalogue is a simple database that holds information about a set of objects, typically classified using terms taken from a given thesaurus. We introduce a matching approach, based on the notion of similarity, which applies to pairs of thesauri and to pairs of lists of properties. We then describe matchings based on cooccurrence of information and introduce variations that explore certain heuristics. Lastly, we discuss experimental results that evaluate the precision of the matchings introduced and that measure the influence of the heuristics. We then focus on the mre complex problem of matching two schemas that belong to an expressive OWL dialect. We adopt an instance-based approach and, therefore, assume that a set of instances from each schema is available. We first decompose the problem of OWL schema matching into the problem of vocabulary matching and the problem of concept mapping. We also introduce sufficient conditions guaranteeing that a vocabulary matching induces a correct concept mapping. Next, we describe OWL schema matching technique based on the notion of similarity. Lastly, we evaluate the precision of the technique using data available on the Web. Unlike any of the previous instance-based techniques, the matching process we describe uses similarity functions to induce vocabulary matchings in a non-trivial, coping with an expressive OWL dialect. We also illustrate, through a set of examples, that the structure of OWL schemas may lead to incorrect concept mappings and indicate how to avoid such pitfalls.