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The Data Web contains a wealth of knowledge on a large number of domains. Question answering over interlinked data sources is challenging due to two inherent characteristics. First, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain question. Second, constructing a federated formal query across different datasets requires exploiting links between the different datasets on both the schema and instance levels. In this dissertation, we present a question answering system, which transforms user supplied queries (i.e. either natural language sentences or keywords) into conjunctive SPARQL queries over a set of interlinked data sources. The contribution of this work is as follows: 1. A novel approach for determining the most suitable resources for a user-supplied query from different datasets (disambiguation). We employ a hidden Markov model, whose …