able expressing within each query user prefer- ences. Query expansion consists in the user query enrichment using preferences given in the user profile [31,34]. Both approaches deal with user preferences characterizing the desired data. They are not concerned by the adaptation to the user environment. However, the need of considering the user mobility and omnipresence [13] has imposed new considerations such as user location, the media used for the interaction, and many other features grouped in the concept of user context. A context is a set of features that describe the environment in which the user interacts with the information system, while a profile is a set of features characterizing user needs in terms of data and quality of these data. Many context-aware applications, such as smart-homes [47] or context-sensitive search engines [27], are able to adapt their processing and their services to the user context. Even if all applications agree with the importance to have a profile and a context, there is a lack of consensus in the definitions of these concepts. There are as many profile and context definitions as application domains and technologies. Thus, classifying, organizing, and structuring the knowledge describing the user and the context are the key elements to have a global vision on data personalization. The goal of this chapter is to provide a formal definition of a personalized access model (PAM) with its underlying notions of profile, context, and contextualiza- tion. The definition of such a PAM is driven by the following requirements: Define profile and context meta models that are generic enough to be adapted to a wide range of SDP applications and that are open to integrate specific knowledge not included in the initial modeling Service Delivery Platforms Define a set of services that can be used to personalize existing SDP applica- tions or to build new personalized applications Propose a generic PAM process that can be deployed over several personaliza- tion scenarios, depending on architect