Local models semantics, or contextual reasoning = locality + compatibility
Artificial Intelligence
Sweetening Ontologies with DOLCE
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
The description logic handbook
Pushing the envelope: challenges in a frame-based representation of human anatomy
Data & Knowledge Engineering
A reference ontology for biomedical informatics: the foundational model of anatomy
Journal of Biomedical Informatics - Special issue: Unified medical language system
Granularity, scale and collectivity: when size does and does not matter
Journal of Biomedical Informatics - Special issue: Biomedical ontologies
Biomedical ontologies: what part-of is and isn't
Journal of Biomedical Informatics - Special issue: Biomedical ontologies
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Guest editorial: Ontological foundations for biomedical sciences
Artificial Intelligence in Medicine
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Objective: Support for the symbolic representation of the physical structure of living organisms by an ontologically solid and logically sound foundation as a basis for formal reasoning. Methods: A set of canonical relations and attributes necessary for empirically adequate descriptions of biological entities is proposed. Results: It is shown how a broad range of biological organisms and their parts can be represented by cascading theories which are ordered by the dimensions of granularity, development, species, and canonicity. Conclusion: The proposed representation of biological objects is non-redundant and compatible with inter- and intra-species similarities, developmental stages and pathological deviations.