Graphs are widely used to model complicated data semantics in many applications (e.g. spacial databases, image databases,…). Querying graph databases is costly since it involves subgraph isomorphism testing, which is an NP-complete problem [7]. Most of the existing query processing techniques are based on the framework of filtering-and-verification to reduce computation costs. However, to the best f our knowledge, the problem of assembling graphs to provide an answer to a given query graph (i.e. information need) if it is not present in one single source, is not investigated. In this paper, we try to highlight the potential and the motivation that lies behind the graph aggregation query problem. We propose a first approach to support aggregated search in graph databases. We discuss the preliminary results from the algorithmic point of view.