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A data cube model for analysis of high volumes of ambient data

Gui, Hao and Roantree, Mark (2012) A data cube model for analysis of high volumes of ambient data. In: 3rd Conference on Ambient Systems, 27-29 Aug 2012, Ontario, Canada.

Abstract
Ambient systems generate large volumes of data for many of their application areas with XML often the format for data exchange. As a result, large scale ambient systems such as smart cities require some form of optimization before different components can merge their data streams. In data warehousing, the cube structure is often used for optimizing the analytics process with more recent structures such as dwarf, providing new orders of magnitude in terms of optimizing data extraction. However, these systems were developed for relational data and as a result, we now present the development of an XML dwarf to manage ambient systems generating XML data.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:XML data; ambient information systems
Subjects:Computer Science > Information technology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17881
Deposited On:28 Mar 2013 15:49 by Mark Roantree . Last Modified 19 Jul 2018 14:58
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