Chemical Knowledge for the Semantic Web
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
Correctness of high-level transformation systems relative to nested conditions†
Mathematical Structures in Computer Science
Representing ontologies using description logics, description graphs, and rules
Artificial Intelligence
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
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Methods for automated classification of chemical data depend on identifying interesting parts and properties. However, classes of chemical entities which are highly symmetrical and contain large numbers of homogeneous parts (such as carbon atoms) are not straightforwardly classified in this fashion. One such class of molecules is the fullerene family, which shows potential for many novel applications including in biomedicine. The Web Ontology Language OWL cannot be used to represent the structure of fullerenes, as their structure is not tree-shaped. While individual members of the fullerene class can be modelled in standard FOL, expressing the properties of the class as a whole (independent of the count of atoms of the members) requires second-order quantification. Given the size of chemical ontologies such as ChEBI, using second-order expressivity in the general case is prohibitively expensive to practical applications. To address these conflicting requirements, we introduce a novel framework in which we heterogeneously integrate standard ontological modelling with monadic second-order reasoning over chemical graphs, enabling various kinds of information flow between the distinct representational layers.