Sweetening Ontologies with DOLCE
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
The structure of science information
Journal of Biomedical Informatics - Special issue: Sublanguage
Two biomedical sublanguages: a description based on the theories of Zellig Harris
Journal of Biomedical Informatics - Special issue: Sublanguage
Tile rewriting grammars and picture languages
Theoretical Computer Science - The art of theory
Methods in biomedical ontology
Journal of Biomedical Informatics - Special issue: Biomedical ontologies
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Guest Editorial: Special Issue on Auditing of Terminologies
Journal of Biomedical Informatics
A review of auditing methods applied to the content of controlled biomedical terminologies
Journal of Biomedical Informatics
Auditing associative relations across two knowledge sources
Journal of Biomedical Informatics
Relationship auditing of the FMA ontology
Journal of Biomedical Informatics
Alignment of the UMLS semantic network with BioTop
Bioinformatics
Decidability of SHIQ with complex role inclusion axioms
Artificial Intelligence
Hypertableau reasoning for description logics
Journal of Artificial Intelligence Research
Information visualization and its application to medicine
Artificial Intelligence in Medicine
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To help clinicians read medical texts such as clinical practice guidelines or drug monographs, we proposed an iconic language called VCM. This language can use icons to represent the main medical concepts, including diseases, symptoms, treatments and follow-up procedures, by combining various pictograms, shapes and colors. However, the semantics of this language have not been formalized, and users may create inconsistent icons, e.g. by combining the ''tumor'' shape and the ''sleeping'' pictograms into a ''tumor of sleeping'' icon. This work aims to represent the VCM language using DLs and OWL for evaluating its semantics by reasoners, and in particular for determining inconsistent icons. We designed an ontology for formalized the semantics of VCM icons using the Protege editor and scripts for translating the VCM lexicon in OWL. We evaluated the ability of the ontology to determine icon consistency for a set of 100 random icons. The evaluation showed good results for determining icon consistency, with a high sensitivity. The ontology may also be useful for the design of mapping between VCM and other medical terminologies, for generating textual labels for icons, and for developing user interfaces for creating VCM icons.