With increase in the amount of data available through multiple data sources, the initiatives from governments to open data from multiple sources also led to an interesting question of combining data gathered and stored by different institutions. The availability of these large varieties of data sets led to an increasing need for systems that can store data from multiple sources, relationships between these sources and efficiently evaluate complex queries over large bodies of interlinked datasets. We propose to develop a model for capturing such heterogeneity in dataset using graph-based representation. New applications such as networked data management, user association in dynamic networks, automatic classification of heterogeneous and reusable information sources across can take advantage of such a system. The goals of this project include developing a representation framework for data from multiple sources, graph-based search mechanisms for query optimization, query processing.