This paper describes methods to allow spreading activation to be used on web-scale information resources. Existing work has shown that spreading activation can be used to model context over small personal ontologies, which can be used to assist in various user activities, for example, in auto-completing web forms. This previous work is extended and methods are developed by which large external repositories, including corporate information and the web, can be linked to the user's personal ontology and thus allow automated assistance that is able to draw on the entire web of data. The basic idea is to augment the personal ontology with cached data from external repositories, where the choice of data to fetch or discard is related to the level of activation of entities already in the personal ontology or cached data. This relies on the assumption that the working set of highly active entities is relatively small; empirical results are presented, which suggest these assumptions are likely to hold. Implications of the techniques are discussed for user interaction and for the social web. In addition, warm world reasoning is proposed, applying rule-based reasoning over activated entities, potentially merging symbolic and sub-symbolic reasoning over web-scale knowledge bases.