Parts, wholes, and part-whole relations: the prospects of mereotopology
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Part-whole relations in object-centered systems: an overview
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Mereotopological reasoning about parts and (w)holes in bio-ontologies
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Design of an Anatomy Information System
IEEE Computer Graphics and Applications
Consistency Checking of Semantic Web Ontologies
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
The PROMPT suite: interactive tools for ontology merging and mapping
International Journal of Human-Computer Studies
Pushing the envelope: challenges in a frame-based representation of human anatomy
Data & Knowledge Engineering
Guest editorial: Ontological foundations for biomedical sciences
Artificial Intelligence in Medicine
Artificial Ontologies and Real Thoughts: Populating the Semantic Web?
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
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Objective: In the context of the Semantic Web, ontologies have to be usable by software agents as well as by humans. Therefore, they must meet explicit representation and consistency requirements. This article describes a method for managing the semantic consistency of an ontology of brain-cortex anatomy. Method: The methodology relies on the explicit identification of the relationship properties and of the dependencies that might exist among concepts or relationships. These dependencies have to be respected for insuring the semantic consistency of the model. We propose a method for automatically generating all the dependent items. As a consequence, knowledge base updates are easier and safer. Result: Our approach is composed of three main steps: (1) providing a realistic representation, (2) ensuring the intrinsic consistency of the model and (3) checking its incremental consistency. The corner stone of ontological modeling lies in the expressiveness of the model and in the sound principles that structure it. This part defines the ideal possibilities of the ontology and is called realism of representation. Regardless of how well a model represents reality, the intrinsic consistency of a model corresponds to its lack of contradiction. This step is particularly important as soon as dependencies between relationships or concepts have to be fulfilled. Eventually, the incremental consistency encompasses the respect of the two previous criteria during the successive updates of the ontology. Conclusion: The explicit representation of dependencies among concepts and relationships in an ontology can be helpfully used to assist in the management of the knowledge base and to ensure the model's semantic consistency.