Evaluating ontological decisions with OntoClean
Communications of the ACM - Ontology: different ways of representing the same concept
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Managing Semantic Content for the Web
IEEE Internet Computing
RDF data exploration and visualization
Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience
From domain ontologies to modeling ontologies to executable simulation models
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Ontology generation for large email collections
dg.o '08 Proceedings of the 2008 international conference on Digital government research
SPARQLeR: Extended Sparql for Semantic Association Discovery
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Towards an automatic fuzzy ontology generation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Glycobrowser: a tool for contextual visualization of biological data and pathways using ontologies
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Ontology consolidation in bioinformatics
APCCM '10 Proceedings of the Seventh Asia-Pacific Conference on Conceptual Modelling - Volume 110
Web Wisdom: An essay on how Web 2.0 and Semantic Web can foster a global knowledge society
Computers in Human Behavior
Supporting interoperability using the discrete-event modeling ontology (DeMO)
Winter Simulation Conference
Engineering use cases for modular development of ontologies in OWL
Applied Ontology - Modularity in Ontologies
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The field of BioInformatics has become a major venue for the development and application of computational ontologies. Ranging from controlled vocabularies to annotation of experimental data to reasoning tasks, BioOntologies are advancing to form a comprehensive knowledge foundation in this field. With the Glycomics Ontology (GlycO), we are aiming at providing both a sufficiently large knowledge base and a schema that allows classification of and reasoning about the concepts we expect to encounter in the glycoproteomics field. The schema exploits the expressiveness of OWL-DL to place restrictions on relationships, thus making it suitable to be used as a means to classify new instance data. On the instance level, the knowledge is modularized to address granularity issues regularly found in ontology design. Larger structures are semantically composed from smaller canonical building blocks. The information needed to populate the knowledge base is automatically extracted from several partially overlapping sources. In order to avoid multiple entries, transformation and disambiguation techniques are applied. An intelligent search is then used to identify the individual building blocks that model the larger chemical structures. To ensure ontological soundness, GlycO has been annotated with OntoClean properties and evaluated with respect to those. In order to facilitate its use in conjunction with other biomedical Ontologies, GlycO has been checked for NCBO compliance and has been submitted to the OBO website.