Many ways of dealing with large collections of linguistic information involve the general principle of mapping words, larger terms and documents into some sort of abstract space. The inherent structure of these spaces is often difficult to grasp directly. Visualisation tools can help to uncover the relationships between meanings in these spaces, giving a clearer picture of the natural structure of linguistic information. We demonstrate a variety of tools for visualising word-meanings in vector spaces and graph models, derived from co-occurrence information and local syntactic analysis. The tools presented in this demonstrated are all available for public use on our website. Related link: http://infomap.stanford.edu