||In this research, we are interested in investigating issues related to query evaluation and optimization in the framework of aggregated search. Aggregated search is a new paradigm to access massively distributed information. It aims to produce answers to queries by combining fragments of information from several sources. The queries search for objects (documents) that do not exist as such in the targeted sources, but are built from fragments extracted from the sources. The sources might not be specified in the query expression, they are dynamically discovered at runtime. In our work, we will consider data dependencies to design a framework to optimize query evaluation over distributed data sources.