Cancer registry information systems need to deal with several data sets annotated with different coding systems. Designing, maintaining and linking these datasets involves dealing with semantic issues, tackling the shortcomings exhibited by coding systems as well as considering an appropriate computing infrastructure. We argue that biomedical ontologies and a Grid service infrastructure, together with a clear separation between semantic and coding models, can prove beneficial to cancer registries in terms of accuracy of knowledge modelling, interoperability and knowledge sharing with other registries and related data sources, automation of information retrieval. A real-life example is illustrated and a brief review of related projects is provided. We conclude that a formal semantic layer, which is the basis of large scale meaning-oriented projects such as the Semantic Web, is the key to the provision of a uniform, science-based view across cancer registries and related systems.