The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Kepler: An Extensible System for Design and Execution of Scientific Workflows
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Future Generation Computer Systems
Automating Experiments Using Semantic Data on a Bioinformatics Grid
IEEE Intelligent Systems
IAAI'07 Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2
Scientific workflow infrastructure for computational chemistry on the grid
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
FaCT++ description logic reasoner: system description
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
A resolution-based decision procedure for SHOIQ
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
A survey of automated web service composition methods
SWSWPC'04 Proceedings of the First international conference on Semantic Web Services and Web Process Composition
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The Semantic Grid is a recent initiative to expose semantically rich information associated with Grid resources to build more intelligent Grid services [2]. Recently, several projects have embraced this vision and there are several successful applications that combine the strengths of the Grid and of semantic technologies [5,11,4]. However, Semantic Grid still lacks a technology, which would provide the needed scalability and integration with existing infrastructure. In this paper we present our on-going work on a semantic grid repository, which is capable of addressing complex schemas and answer queries over ontologies with large number of instances. We present the details of our approach and describe the underlying architecture of the system. We conclude with a performance evaluation, which compares the current state-of-the-art reasoners with our system.