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Ontologies have been highly successful in applications involving annotation and data fusion. However, ontologies as the core of “Knowledge Driven Architectures” have not achieved the same influence as “Model Driven Architectures”, despite the fact that many biomedical applications require features that seem achievable only via ontological technologies --composition of descriptions, automatic classification and inference, and management of combinatorial explosions in many contexts. Our group adopted Knowledge Driven Architectures based on ontologies to address these problems in the early 1990s. In this paper we discuss first the use cases and requirements and then some of the requirements for more effective use of Knowledge Driven Architectures today: clearer separation of language and formal ontology, integration with contingent knowledge, richer and better distinguished annotations, higher order representations, integration with data models, and improved auxiliary structures to allow easy access and browsing by users.