Nowadays information systems manage huge amount of data. With the emergence of the Semantic Web, the amount of available ontological data (or instances) has increased. To allow personalized access to this information has become a crucial necessity. Users are overwhelmed by the numerous results provided in response to their requests. In order to be usable, these results must often be sorted and filtered. The capture and exploitation of user preferences have been proposed as a solution to this problem. However, the existing approaches usually define preferences for a particular application. Thus, it is difficult to share and reuse the handled preferences in other contexts. Our approach, which defines a sharable and generic model to represent user preferences, based on several models proposed in the Databases and the Semantic Web communities. It incorporates several types of preferences proposed in the literature, but are treated separately. Our idea is to address preferences of a modular way by linking them to ontologies for describing the semantics of the data, handled by the applications. It is thus to raise the treatment preferences of logic level (structure) to the ontological level. The novelty of our approach is that the defined preferences are attached to the ontologies, which describe the semantic of the data manipulated by the applications. The preference model is formally defined using the EXPRESS data modeling language, which ensures a free ambiguity definition. Moreover, the proposed model offers a persistence mechanism and a dedicated language; which is implemented using Ontology Based Databases (OBDB) system, that manages both ontologies and extended data instances, in order to support a semantic description of preferences. These databases are associated with explanation languages, supporting description, querying, etc. on both ontologies and data. Usually queries return a big amount of data that may be sorted in order to find the relevant ones. Moreover, in the current situation few approaches are considering user preferences, when querying has been developed. Yet this problem is fundamental for many applications, especially in the e-commerce domain. Our second approach, which defines preferences in terms of ontologies that describe the semantics of handled data, provides a mechanism for querying with preferences. Thus, an extension to existing ontology based query languages is proposed, for querying ontological data with preferences. The proposed extension has been implemented onto the OntoDB OBDB associated to the OntoQL query language and the approach is illustrated through a case study in the tourism domain.