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Interactive visualization of big data leveraging databases for scalable computation

Author(s)
Battle, Leilani Marie
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Michael R. Stonebraker and Samuel R. Madden.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate. Instead of running the original query, ScalaR inserts aggregation, sampling or filtering operations to reduce the size of the result. This thesis presents the design and implementation of ScalaR, and shows results for two example applications, visualizing earthquake records and satellite imagery data, stored in SciDB as the back-end DBMS.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 55-57).
 
Date issued
2013
URI
http://hdl.handle.net/1721.1/84906
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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