DocumentCode :
1919531
Title :
Fast Data Analysis with Integrated Statistical Metadata in Scientific Datasets
Author :
Liu, Jialin ; Chen, Yong
Author_Institution :
Comput. Sci. Dept., Texas Tech Univ., Lubbock, TX, USA
fYear :
2012
fDate :
10-13 Sept. 2012
Firstpage :
602
Lastpage :
603
Abstract :
Scientific datasets, such as HDF5 and PnetCDF, have been used widely in many scientific applications. These data formats and libraries provide essential support for data analysis in scientific discovery and innovations. In this research, we present an approach to boost data analysis, namely Fast Analysis with Statistical Metadata (FASM), via data sub setting and integrating a small amount of statistics into datasets. We discuss how the FASM can improve data analysis performance. It is currently evaluated with the PnetCDF on synthetic and real data, but can also be implemented in other libraries. The FASM can potentially lead to a new dataset design and can have an impact on data analysis.
Keywords :
data analysis; libraries; meta data; statistical analysis; FASM; PnetCDF; data analysis; data formats; integrated statistical metadata; libraries; real data; scientific datasets; synthetic data; Atmospheric modeling; Computational modeling; Computer science; Data analysis; Libraries; Runtime; Temperature distribution; FASM; big data; data intensive computing; high performance computing; statistical techniques;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing Workshops (ICPPW), 2012 41st International Conference on
Conference_Location :
Pittsburgh, PA
ISSN :
1530-2016
Print_ISBN :
978-1-4673-2509-7
Type :
conf
DOI :
10.1109/ICPPW.2012.89
Filename :
6337537
Link To Document :
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