The Henri Poincaré correspondence corpus is composed of around 2200 letters which constitute a rich source of information for historians of science. The following Semantic Web technologies have been chosen to represent and to exploit corpus data: the rdf model, the rdfs knowledge representation language and the sparql query language. Recently, the need of an exploration tool for this historical corpus has emerged. As a result, a navigation tool has been created to explore the correspondence by exploiting the similarities between the documents of the corpus. This system relies on the use of a sparql query transformation rule mechanism which can help to highlight unexpected relations between resources. This article presents the context of this work and illustrates the developed system through a concrete use case for the Henri Poincaré correspondence corpus. The system architecture and some reusability elements are presented, as the tool can be connected to other corpora, as long as underlying data is exposed through a public sparql endpoint.