Evaluating ontological decisions with OntoClean
Communications of the ACM - Ontology: different ways of representing the same concept
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Managing Semantic Content for the Web
IEEE Internet Computing
Creating Semantic Web Contents with Protégé-2000
IEEE Intelligent Systems
Semantic web applications to e-science in silico experiments
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
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WWW '05 Proceedings of the 14th international conference on World Wide Web
Framework for a protein ontology
TMBIO '06 Proceedings of the 1st international workshop on Text mining in bioinformatics
Extraction and search of chemical formulae in text documents on the web
Proceedings of the 16th international conference on World Wide Web
SwetoDblp ontology of Computer Science publications
Web Semantics: Science, Services and Agents on the World Wide Web
RDF data exploration and visualization
Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience
Ontology-Driven Provenance Management in eScience: An Application in Parasite Research
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part II
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
Web Wisdom: An essay on how Web 2.0 and Semantic Web can foster a global knowledge society
Computers in Human Behavior
Editorial: ANEMONE: An environment for modular ontology development
Data & Knowledge Engineering
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High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantification of a structurally diverse collection of biomolecules. The ability to share, compare, query for and most critically correlate datasets using the native biological relationships are some of the challenges being faced by glycobiology researchers. As a solution for these challenges, we are building a semantic structure, using a suite of ontologies, which supports management of data and information at each step of the experimental lifecycle. This framework will enable researchers to leverage the large scale of glycoproteomics data to their benefit.In this paper, we focus on the design of these biological ontology schemas with an emphasis on relationships between biological concepts, on the use of novel approaches to populate these complex ontologies including integrating extremely large datasets ( 500MB) as part of the instance base and on the evaluation of ontologies using OntoQA [38] metrics. The application of these ontologies in providing informatics solutions, for high throughput glycoproteomics experimental domain, is also discussed. We present our experience as a use case of developing two ontologies in one domain, to be part of a set of use cases, which are used in the development of an emergent framework for building and deploying biological ontologies.