  A sensor integration framework should be sufficiently general to accurately
represent all information sources, and also be able to summarize information in
a faithful way that emphasizes important, actionable information. Few
approaches adequately address these two discordant requirements. The purpose of
this expository paper is to explain why sheaves are the canonical data
structure for sensor integration and how the mathematics of sheaves satisfies
our two requirements. We outline some of the powerful inferential tools that
are not available to other representational frameworks.
