Scalable semantics: The silver lining of cloud computing

Newman, Andre, Li, Yuan-Fang and Hunter, Jane (2008). Scalable semantics: The silver lining of cloud computing. In: Patrick Kellenberger, Proceedings: Fourth IEEE International Conference on eScience. eScience 2008. IEEE International Conference on e-Science and Grid Computing [e-Science], Indianapolis, IN, U.S.A., (111-118). 7-12 December 2008. doi:10.1109/eScience.2008.23

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Author Newman, Andre
Li, Yuan-Fang
Hunter, Jane
Title of paper Scalable semantics: The silver lining of cloud computing
Conference name IEEE International Conference on e-Science and Grid Computing [e-Science]
Conference location Indianapolis, IN, U.S.A.
Conference dates 7-12 December 2008
Convener Indiana University
Proceedings title Proceedings: Fourth IEEE International Conference on eScience. eScience 2008
Journal name Proceedings - 4th IEEE International Conference on eScience, eScience 2008
Place of Publication Los Alamitos, CA, U.S.A.
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Publication Year 2008
Sub-type Fully published paper
DOI 10.1109/eScience.2008.23
ISBN 9780769535357
0769535356
Editor Patrick Kellenberger
Start page 111
End page 118
Total pages 8
Language eng
Formatted Abstract/Summary
Semantic inferencing and querying across large-scale RDF triple stores is notoriously slow. Our objective is to expedite this process by employing Google's MapReduce framework to implement scale-out distributed querying and reasoning. This approach requires RDF graphs to be decomposed into smaller units that are distributed across computational nodes. RDF Molecules appear to offer an ideal approach - providing an intermediate level of granularity between RDF graphs and triples. However, the original RDF molecule definition has inherent limitations that will adversely affect performance. In this paper, we propose a number of extensions to RDF molecules (hierarchy and ordering) to overcome these limitations. We then present some implementation details for our MapReduce-based RDF molecule store. Finally we evaluate the benefits of our approach in the context of the Bio-MANTA project - an application that requires integration and querying across large-scale protein-protein interaction datasets.
© 2008 IEEE
Subjects E1
080505 Web Technologies (excl. Web Search)
080404 Markup Languages
060102 Bioinformatics
890299 Computer Software and Services not elsewhere classified
970106 Expanding Knowledge in the Biological Sciences
Keyword MapReduce
RDF
RDF molecules
Data integration
Distributed processing
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Mon, 13 Apr 2009, 23:52:22 EST by Donna Clark on behalf of School of Information Technol and Elec Engineering